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Here are twitter's best strategic options going forward.

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The memo below outlines potential strategic decisions Twitter could make going forward, and evaluates four strategic options to see how they could impact the company’s user base and average revenue per user – and consequently its revenues and earnings. In a recent note, we detailed how the social media company is struggling to monetize its platform, as growth in its user base appears to have stagnated . While Twitter has been able to develop a niche for itself in the extremely competitive social media industry, it has not seen great success in the online advertising market, which is dominated by Google and Facebook . In this note, we have put together a strategic analysis regarding Twitter’s path forward in the face of secular headwinds.

Executive Summary: Doubling down on its focus on being the go-to app for real-time news and information should allow Twitter to turn things around going forward, at least to an extent. The company has mentioned that live streaming is also an area of focus – and rightly so, given the secular tailwinds driving massive growth in live streaming. However, we expect that the company would run into trouble trying to compete head-to-head with the likes of Amazon, Facebook and Snap in live-streaming sports and entertainment-related events. Rather, Twitter is incredibly well-positioned to improve its position as a news and information provider by introducing more live-streaming news services (in addition to those that have already been announced) and introducing new features making it easier to use the app as a primary news source.

If executed well, this strategy could allow the company to accelerate its user growth, while avoiding the significant content-related costs that are associated with live-streaming sports and entertainment-related events. We estimate that this could lead to 6% annual revenue growth in the short term, with the potential for further growth in the future (versus our current forecast of under 1% for our base case model). This translates to annual EBITDA growth exceeding 10% over 2016-2020, as opposed to around 6% under our base case scenario.

Below, we present a comparison of four feasible strategic options for Twitter: 1) Continue the Current Model; 2) Content-Focused Approach; 3) News-Focused Approach; and 4) Data-Focused Approach.

Strategy 1 : Continue Current Model

– Twitter’s core user base in the U.S. will slow down, and U.S. ARPU figures will remain under pressure

In our base case scenario , the trends we forecast for Twitter’s revenue and cost drivers going forward are as follows:

• U.S. active user base will stagnate : We expect Twitter’s U.S. active user base to grow marginally over the next couple of years before settling around 72 million users.
• Average advertising revenue per U.S. user to improve marginally : Twitter’s considerably smaller user base compared to competitors like Facebook, coupled with a projected slowdown in user base growth, will likely limit growth in advertising revenues going forward.
• Data licensing revenues to grow steadily : The revenue Twitter generates in the form of access fees to its database of tweets is expected to grow at more than 10% annually over the foreseeable future.
• Gross margins will trend lower : While we expect Twitter’s strategy of monetizing its social networking platform in its current form to result in stagnating revenues, its cost of revenues are likely to nudge slightly higher each year – resulting in gross margin compression over the coming years.

Strategy 1 – Base Case Scenario: Key Trends

The table below highlights our forecast for key operating metrics at Twitter under the base case scenario.

Strategy 1 – Base Case Scenario Projections

Strategy 2 : Content-Focused Approach

– Strong improvement in revenue potential, but substantially higher content costs could eliminate gains

Twitter has expanded its social networking platform of late to include live-streaming capabilities – a move that is clearly aimed at making the most of the growing popularity of online streaming services. There has been a noticeable shift in the manner in which people consumer entertainment, thanks to the proliferation of smartphones, the return of unlimited data plans in the U.S., and the popularity of various online viewing platforms. As a result, many households are doing away with traditional cable TV plans altogether (cord-cutting).

Under our content-focused scenario for Twitter , we forecast the company’s financial performance if it were to target growth primarily by live-streaming sports and other entertainment events and programs. This is largely along the lines of what Twitter sought to do by streaming Thursday Night Football on its platform last year . Twitter reportedly paid $10 million to acquire exclusive streaming rights to the 10 NFL games, and generated revenues by selling spots to stream advertisements before and during the event. Twitter did fairly well too – especially due to its ability to customize ads by location as well as user preferences thanks to its core social networking platform.

But a content-focused approach to growth has a significant drawback: this model really only works well if a company has exclusive broadcasting or streaming rights to a particular event. And the more popular the event, the more expensive those rights will be. The high level of competition in the streaming space only inflates these costs further. Twitter learned this firsthand when its attempt to acquire exclusive streaming rights to Thursday Night Football again this year were thwarted by the much larger Amazon . Notably, Twitter’s bid for these streaming rights were placed along with industry giants like Google and Facebook , before Amazon closed the deal for $50 million (a 400% increase from the figure for last year’s deal).

As we pointed out earlier, Twitter has yet to turn profitable, and also has comparatively little cash on hand. This puts it in an extremely weak position compared to deep-pocketed competitors who are also keen on grabbing a sizable share of the live-streaming market. At the same time, Twitter’s attempt to differentiate its streaming service from other players by integrating a live tweet-stream with the event has been met with mixed reviews – with many users complaining that the constantly updating tweet feed distracts them while watching the main content. This issue could limit the number of users that will use Twitter to watch live content – putting the company at a very real risk of not being able to generate enough advertising revenues to cover the costs incurred to acquire streaming rights.

Strategy 2 – Content-Focused Approach: Key Trends vs. Base Case

To better understand how Twitter’s revenues and profits are affected purely due to a content-focused approach as opposed to the base case, we forecast the number of Twitter users added directly due to content-streaming as well as the advertising revenues generated per newly added user. The resulting content-specific revenues are, therefore, in addition to what we model under Twitter’s base case scenario. Further, we separately capture the additional costs that accompany this strategy, which include content costs as well as additional infrastructure costs (such as new servers) needed to support streaming. The key trends we forecast for Twitter’s revenue and cost drivers under the “Content-Focused Approach” scenario are as follows:

• Initiative-specific active users : We forecast the average number of users drawn to Twitter purely to watch its live-streaming events to grow rapidly to around 30 million by 2020 and to exceed 40 million by 2023.
• Initiative-specific average advertising revenue per user : The exclusive nature of live-streaming content will allow Twitter to generate higher advertising revenues per user compared to its base platform. We forecast these figures to be roughly $22.50 per live-streaming user in 2020, and we expect it to increase steadily over our forecast period.
• Additional initiative-related costs : As we pointed out earlier, this strategy would attract considerable content costs which will have to be borne by Twitter upfront. We forecast a steep increase in content costs year after year over the forecast period.

Based on these assumptions, we believe that Twitter’s revenues could grow by almost 7% annually over coming years under this scenario. However, the higher content costs result in the company’s EBITDA growth figure shrinking from over 6% in the base case to 5.5% under this scenario.

Strategy 2 – Content-Focused Scenario Projections vs. Base Case

Strategy 3 : News-Focused Approach

– Lower revenue potential compared to content-focused approach, but lower content costs and better alignment with base existing platform can meaningfully boost bottom line

Under our news-focused scenario for Twitter , we forecast the company’s financial performance if it targets growth focusing on better delivery of news. Twitter has been working along this front over recent months, and has announced deals with several news providers including Bloomberg Media, The Verge, BuzzFeed News and Cheddar to live-stream news content on its platform. We believe this strategy complements the strength of Twitter’s social networking platform, which is used by a large number of users as a primary source of news and current events.

The news-focused approach would likely generate much lower revenues per user compared to the content-focused approach, because of the revenue-sharing agreements between Twitter and any news provider. However, we believe that Twitter would also be able to attract more users by focusing on news – something that would partially mitigate the impact of lower advertising revenues per user on the top line compared to the content-focused approach. More importantly, the cost of producing news content would be much lower than for sports and other entertainment events. And even these lower costs would be split between Twitter and the news partners. This implies that a bulk of the revenue generated from streaming news will accrue to the bottom line, as opposed to the content-focused approach where extremely high content costs can potentially erode profits (as detailed above).

Strategy 3 – News-Focused Approach: Key Trends vs. Base Case

Below we forecast the number of Twitter users added directly due to news-streaming as well as the advertising revenues generated per newly added user – similar to the manner described in the content-focused strategy above. As in the previous scenario, we also include a separate forecast for additional costs that accompany this approach. The key trends we forecast for Twitter’s revenue and cost drivers under the News-Focused Approach scenario are as follows:

• Initiative-specific active users : We believe that the news-focused approach is a natural extension to Twitter’s base social networking business model, and Twitter will be able to draw more users by streaming news compared to streaming sports or other entertainment content. We forecast the average number of users added by Twitter purely due to news streaming to reach about 54 million by 2020 and to exceed 70 million by 2023.
• Initiative-specific average advertising revenue per user : As we mentioned above, as advertising revenues will be shared with the news provider, Twitter’s advertising revenues per user will be lower than the figure for the content-focused approach. We forecast these figures to be roughly $10 per viewer as opposed to $22.50 per viewer assumption for the previous approach.
• Additional initiative-related costs : A news-focused strategy has the advantage of lower content costs. Also, these costs will be incurred by Twitter on a regular basis, as opposed to the upfront content costs in case of streaming rights for sports events.

Based on these assumptions, we believe that Twitter’s revenues can grow by almost 6% annually over coming years under this scenario. While this is lower than the 7% revenue growth in the previous scenario, the lower content-related costs could help the company’s EBITDA growth figure jump to over 10% annually from a much lower 5.5% under the content-focused approach.

Strategy 3 – News-Focused Scenario Projections vs. Base Case

Strategy 4 : Data-Focused Approach

– Unlock full revenue potential of tweet database, with cost of revenues likely to grow along with revenues

Another strategic path Twitter can explore is one that focuses on monetizing its tweet database. Twitter has amassed trillions of tweets since it was founded, and over the years analytics firms have tapped into this data to identify trends that can be used by organizations ranging from multinational companies to political parties to news agencies to environmental groups. Currently, Twitter grants companies access to its tweet database for a fee, and also charges interested parties for basic data analytics services. But we believe the company is leaving money on the table by not implementing a more in-depth data analytics platform along the lines of many third-party vendors. While this would make Twitter a direct competitor to many vendors who buy access to its database, there is significant upside potential for the company if it can become a one-stop shop for all tweet-related analytics.

This approach does have a notable issue, though. There are already concerns being raised among Twitter users about third-party access to the tweet database on the grounds of security and privacy. Twitter’s attempts to monetize this aspect of its business could therefore backfire, and could actually lead to a reduction in user engagement due to these concerns. That said, an advantage Twitter has here over data analytics firms is that a single company managing and analyzing the tweets in-house is a more secure option from a user’s point of view.

Strategy 4 – Data-Focused Approach: Key Trends vs. Base Case

Under the data-focused approach, if Twitter chooses to grow organically over coming years, then we forecast that its data licensing revenues can grow at almost 30% each year as opposed to the ~11% growth figure under the base case. Notably, a potential way forward for Twitter to expand its data business could be to acquire one of the medium-sized established data analytics firms, which could further accelerate growth in these revenues.

In the Data-Focused scenario, our analysis shows a 4% annual growth in revenues for Twitter – something that stems from the fact that data licensing is responsible for around 10% of the company’s total revenues. But overall operating expenses in this scenario are well below the figures for the other two approaches, leading to a nearly 10% increase in EBITDA annually.

Strategy 4 – Data-Focused Scenario Projections vs. Base Case

To conclude, a News-Focused strategy could potentially help Twitter improve earnings at a better rate than a Content-Focused, and with less uncertainty than a Data-Focused strategy. While Twitter is currently testing the waters with live sports, entertainment as well as news content, we believe that the company will do best to concentrate its efforts on news and information content going forward.

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Elon Musk’s Twitter Takeover: Lessons in Strategic Change

Brian Kenny:

On March 10, 1874, Alexander Graham Bell launched a new era in communications with the memorable but mundane phrase, "Mr. Watson, come here, I want you." 132 years later, in March of 2006, Jack Dorsey launched another communications revolution with the uninspiring and perhaps even less memorable phrase, "just set up my twitter." All lowercase. By the way, that first-ever tweet sold at auction for 2.5 million in 2021, proving that someone was in fact inspired.

Few would've predicted in 2006 the impact that this clunky social platform with 140-character limit would have in the world. And looking back, no one can deny how profoundly it has altered the media landscape and public discourse. But in the public square that Twitter aspires to be, everyone has a megaphone, including those who seek to spread disinformation. These days, Twitter finds itself on both sides of the battle between free speech and censorship, all while trying to sustain a profitable business model. Which begs the question, who on earth would want to manage that?

Today, on Cold Call , we welcome Professor Andy Wu and his co-author, Goran Calic, to discuss their case entitled, “Twitter Turnaround and Elon Musk.” I'm your host, Brian Kenny, and you're listening to Cold Call on the HBR Podcast Network.

Andy Wu's research focuses on how technology entrepreneurs organize and mobilize resources to achieve scale for competitive advantage. Goran Calic teaches at the DeGroote School of Business at McMaster University, and his research focuses on understanding why some individuals are more creative and some organizations are more innovative than others. And you both wrote this case together. Thanks for joining me.

Thanks for having us, Brian.

Goran Calic:

Yeah, it's great to be here.

Great to have you on Cold Call . Andy, you're a repeat customer, so thanks for coming back. Obviously, this case is somewhat ripped from the headlines. I mean, these are all recent developments and I think all of our listeners have probably been following the story and there's been salacious details and who knows what Elon Musk is up to. So the case really delves into some of why he chose to do this and what are some of the options that he has in terms of trying to turn Twitter around. So why don't we just dig right in and start with telling us what the central issue is in the case and what the cold call is that you use to start the discussion in class.

So the central issue of this case is managing strategic change in a technology company with network effects. And given the current economic environment, there's a lot of technology companies out there that are in a situation like Twitter that really need to transform themselves and find profitability or find a new direction for the company. And I like to start this class with the very basic question of: If you were Elon Musk, would you have acquired Twitter for 44 billion dollars? Yes or no? And we dive right in.

I bet that there's probably a lot of interesting perspectives on that one. Why was it important to you to write the case?

So first is that we want to make sure that students understand that we are in a phase of technology where businesses need to transform themselves oftentimes into a more profitable mode from the growth phase that they're previously in. And then that process is very, very difficult. There's issues of culture, there's issues of technology, and we want students to explore those kinds of issues. Second, I think that the Twitter case is a real microcosm for understanding the future of the media and information environment. I think watching what's happening here can tell us a lot about the future of social media, the future of mainstream media, and so forth.

Do you guys both tweet, I'm curious?

Very rarely, but yes. Browse more than tweet.

Yeah, I tweet occasionally, but not enough.

I joined the platform in 2008, so shortly after it launched, and like everybody else, I was trying to figure out what is this thing all about, how is it going to be used. And I was thinking about it more from a branding perspective. I represent the HBS brand and how should HBS responsibly use it. And I guess my question is, why would Elon Musk care so much about this, enough to buy it for 44 billion dollars?

Well, we can only speculate what's going on in his mind here, but I think the situation here does have some clear interest to Musk. First, just to set the baseline, I think the reason you're asking the question is that the reality is that very few people actually use Twitter. There's more people that use Snapchat than Twitter, and there's 10 social media platforms younger than Twitter that have more users than Twitter now. So why do we care here? Well, if you look at Twitter, in fact, there's definitely segments of elite users that very, very intensely use Twitter. I'm thinking about academia, I'm thinking about finance. But for your interest, Brian, I think we should talk about journalists. And so what was amazing about the data here is just the contrast. 13 percent of the regular US population uses Twitter to get news. 69 percent of journalists use Twitter as their top one or two social media platform for their job. And 83 percent of journalists between 18 and 29 use Twitter as their top one or two social media platform for their job.

So that's pretty remarkable. And that does speak to the way it's sort of recreated the media landscape. I mean, that's the channel that they're using now to get their news out there.

Absolutely. Yeah. And so you can think about politicians and business leaders that want to communicate with journalists and journalists that want to communicate with each other-- Twitter is where that happens.

Yeah. I mentioned Jack Dorsey's opening tweet; uninspiring opening tweet (all in lower case). Can we talk a little bit about the history of Twitter? Because I'm sure for a lot of our listeners, they just assume it's always been around and it started in 2006, so it's not that old.

No, it's not. And as you correctly mentioned, it happened in 2006 and it was quite informal. Like a lot of tech startups, if you can imagine, Jack Dorsey had no idea what it would eventually develop into, and he initially didn't develop it as a startup in its own right. So Twitter was originally developed as a messaging service for a podcasting startup that Jack Dorsey was only a part of, eventually grew quite a lot more successful. And between 2006 and 2012, there were dozens of other third-party developers and startups using Twitter data for their own purposes for different startups. So it had actually grown quite a bit larger than Jack Dorsey and the other founders had initially expected.

And there were a lot of third party apps that were developed to make Twitter more usable and more effective in some ways. Can you describe a few of those?

Yes. So this is part of the history of Twitter that most people are not familiar with. So most people don't know that the Twitter bird was not invented by Twitter. The term “tweeting” was not invented by Twitter. Both of these were invented by Twitterrific, and at some point in time, so let's say pre-2010, most of the innovations that we're familiar with in 2022 and 2023 were developed by these third-party apps. Just to give you one other example, some eyes invented search. So a lot of the initial innovation and changes in things that we find familiar with Twitter were not developed by Twitter itself. So the innovation happened outside Twitter.

Which is really interesting because if you think about that as being contributing in some way to their growth and the way that they scaled, they eventually turned to that spick it off. They shut those third parties out. Why would they do that?

So 2010 again to 2012, Twitter decided they wanted to make money from tweeting, and they thought the best way to do this was through advertising, which we just briefly discussed. The problem was that most people that access Twitter data through Twitter itself did it online through twitter.com. Initially. When the iPhone was released and smartphones more generally, people started moving their usage of Twitter to mobile applications. Most people then started moving to third party app developers, which meant that control over the revenue model was outside Twitter. So what Twitter, in order to capture most of this revenue did was acquire the most successful third-party app developer, which was Tweetie. However, they still face a lot of competition. You had all these Twitter applications which were capturing users, and then Twitter started doing something which was very interesting. First, they limited the number of users that could be acquired by these third party apps to about a hundred thousand people. And then they started closing access to some of these third party apps for dubious terms of service violations. Until eventually, most third party app developers decided, well, we can't really reliably make money from the Twitter database, and they just started shutting down, and the rest is history. Twitter now has a monopoly in how everybody accesses the Twitter database, whether you're doing it through twitter.com or through a mobile application.

And that could be good or bad as we'll talk about a little bit further on in the discussion. You pointed out something really interesting there, Goran, which is that the release of Twitter predated the release of the iPhone. So I didn't even think about that before, but that's the way that we all access our social networks and our social apps these days, which I guess leads me to the question about how have they grown in comparison to some of the other social networks that are out there and that are active these days?

So Twitter certainly had a burst of growth in its very early days, but since the mid 2000 tens, Twitter has certainly had very slow growth compared to most of the competition in social media. Now, this I would say comes down to two things. One is that to Twitter's positive benefit, they actually have heavily dominated the segments that they do well in. So for example, journalism and finance. But at the same time, the lack of innovation has limited their ability to appeal to the broader population. So as we know from Instagram and TikTok video and photos are quite important to the general population, and Twitter's been held back on that.

I can remember on many occasions, particularly as we were trying to figure out as a brand how to use Twitter, we would oftentimes go to log in and it would be shut down. You'd get that little ... they had the icon of the sad bird, I think it was shut down. So they had a lot of technical issues early on. They had a pretty unstable platform. What were some of the things that were plaguing them as they tried to scale?

Absolutely. So there's both organizational and technical challenges here. So organizationally, they've had a lot of leadership turnover through the years, and that's been made it difficult to be consistent about the company. I think on the technological front that you pointed out ... so internally and publicly, people refer to this as the fail whale. And so we have to keep in mind that the original base Twitter infrastructure, database and all those systems actually date back to the early 2010s. And so they're using actually quite even today, quite antiquated and fragile infrastructure that doesn't scale well as opposed to technologies that are built cloud-native for today.

So the case goes into some detail about the risk averse nature of the way they operate. But it seems like in the space that they're in, that is not necessarily always the best approach and it may have hindered their ability to succeed a little bit. Can you talk about what was at the root of some of that risk-averse culture?

So I think we can look at the risk aversion both from the perspective of the employees as well as at the level the board of the directors. And so for the employees, I think there's two things driving the risk aversion. The first is that the employees were inspired by the outsized role that Twitter had in the world at large, and they didn't want to take any chances breaking that system. They just wanted to keep it functioning as is. And a core characteristic of, at least in the early and middle days of the company, of what they believed made that work was the simplicity of the product and simplicity of the business, which is to say that any innovation, any risk-taking are things that make the business less simple. And so these are things that we would naturally want to work against. And then if we turn now to the board of directors, I think this is a really interesting situation where the board, looking at it now, seems particularly risk-averse because they are very, very scared of public backlash from any kinds of changes they can make to the business. And here's one way to think about it, Twitter is where investors go to complain about public companies. And so if you make a change that impairs that experience, you're going to get directly complained at on your own business, on your own platform.

Yeah. But is that a way to run a social media network? You think about fast-moving industries. I mean, I think this is one of the fastest out there.

Absolutely. And I think that we would probably advise against doing that. Look, we're sympathetic to the employees and to the board about why they were in that situation. But certainly, there's plenty of innovation opportunities that are pretty obvious in retrospect that they actually tried. So many things like podcasting and video and everything. They actually either acquired companies or tried building these themselves and they just wouldn't bring it to market. Looking back now, I think it's clear they should have done that.

Yeah, you talked about the leadership changes and Jack Dorsey came and went already, so he's been there twice in a leadership role. And it reminded me a little bit of when Steve Jobs came back to save Apple, it was sort of riding in. And even Dorsey I think at some point thought, "This isn't working. I can't fix this." So they've got a CEO in there now, Agarwal, I forget his first name.

Parag Agarwal.

Yeah. Thank you. I guess what kind of condition was the firm in when he stepped in to take the role and what were some of the things that he's tried to do to get it unstuck?

Yeah, so I think it's important to remember that at this point in time, Twitter had been underperforming, not just the competition and not just traditional competition, the New York Times, but the S&P 500 for very many years. And you had large investors like Elliot Management who were obviously very unhappy with this. You have this money stuck in a company you expect will do extremely well, and it's not even performing as well as a diverse portfolio of firms. So they were agitating for change. And having brought Jack Dorsey in a second time, they realized he wasn't really the change they were looking for. Jack Dorsey was spending a lot of time on his other startups or just away from the firm, and it looks like they were looking for a much more hands-on manager. And this is where Agarwal comes in. So he replaces Jack Dorsey, end of 2021, and starts quite radical changes for Twitter at the beginning of 2022. And it's important to keep in mind at this point that he isn't the first to try this. Others have tried and failed. So just to give you kind of an impression of what he tried to do is he started with a really broad reorganization of Twitter by restructuring it in a way where he removed the chief design officer, head of security, chief information officer, head of engineering, head of communications, head of HR.

So he comes in, makes these drastic changes, and he explicitly says, "My vision for Twitter is a bold one." And what does that mean? So it means he wants to make Twitter open for development again. Like we mentioned early on, a lot of initial innovation came to these third party apps, which we're were competing to capture users-- doesn't exist anymore. Twitter's the only one. So he wants to open it up for development and more innovation. He also wants to integrate crypto. A lot of people are doing tipping on or through Twitter. He wants this now to be done through Twitter itself to capture some of these exchanges. He also is thinking about creating an open protocol where Twitter could connect more seamlessly to LinkedIn, to Facebook, to Instagram. And he doesn't have very much time to implement this. So he's not CEO for very long, but he had a bold vision for the company.

Yeah. What was the firm's business model at that time? What were some of the things that they were doing to generate revenue?

Twitter's primary business is selling advertising. So that's about 89 percent of the revenue. And then it also makes some amount of revenue from selling its data. So let's start with the advertising. So the advertising business is been a challenge for Twitter, even though it is its primary revenue source. And it's a challenge because Twitter just cannot, or will not have some of the same advantages that say Facebook and Meta have in advertising, which is to say Facebook and Meta is a leader in what we call direct response advertising, which is to say you can use data to directly target a specific customer and then get that customer to immediately buy a pair of shoes or download an application. In contrast, Twitter has primarily been relying on brand advertising. And so this is companies like Nestle, Unilever, Verizon, who want to generally put out a brand image, but there's not an obvious return on that investment, I mean as the challenge with general marketing would always be. But the problem is that that is a less valuable form of advertisement than direct response advertising. I should also mention there is a business here in selling data. This is quite a high-margin business. So what Twitter did and still does is license data to hedge funds and market analytics firms for supporting their research and their investment activities.

One of the moves that Agarwal made that, I don't know if he ended up regretting it, was that he invited Elon Musk to be on the board of Twitter. How did that play out?

So he had some private conversations which eventually became public through this messaging app, Signal, with Elon Musk. I think the frustration that a lot of people have had with Twitter was that it wasn't very innovative. And the idea was if we bring on Elon Musk, if we placate him, maybe even to some extent, he might bring some innovation to the firm, some change, but he also won't be entirely destructive. Now, Agarwal had invited Elon Musk to the board, an invitation Elon Musk had first implied he would take, and then literally over that weekend he decided against it and on Monday had filed an amendment to his 9 percent acquisition of Twitter, stating that he was interested in acquiring a much larger strategic stake in the company. So it seems that over the weekend, he had made the change from 9 percent ownership to "it's possible that I want buy the entire company."

Which sounds perfectly on brand for Elon Musk as we've now come to know him.

Yes, very much Elon.

One thing that we did not touch on were some of the content management issues that not just Twitter is dealing with Facebook and other platforms are dealing with them as well, but content moderation has become increasingly important, particularly as we look at some of the misinformation that's been spread on a lot of these platforms. How was Twitter managing the content moderation part of what they do?

So Brian, I think it's important at this point to really emphasize how extremely difficult content moderation is. So Jack Dorsey is on record along with a number of people to say that content moderation at scale, which is really what Twitter is doing, is literally impossible. And the reason for that is setting any kind of hard and fast rule, let's say automation, which is required when you have hundreds of millions of monthly active users is difficult when those content moderation rules are applied not just within a heterogeneous country like the United States, which has a lot of different and diverse views, but also across countries. We have to remember that 75 percent of Twitter users are outside America. So content moderation is hard. So how does Twitter do it? Generally speaking, Twitter along with Facebook, and other social media platform, start with some form of automation where either an algorithm or an AI will flag content and then the flagged content, if it's egregious enough, could be removed immediately by this algorithm. But most of the time that doesn't happen. That flagged content then reaches the eyes and ears of actual human beings who look through it, read through it, and in circumstances of where it clearly violates the terms of service, that content is removed. But unfortunately, there is a portion of content that fits in this gray zone where really people are not that sure whether to remove it or not. So then you have these live discussions where decisions to moderate content happen in real time. And generally speaking, Twitter wasn't great at doing this in a sense that on the one hand, there were people asking for much more moderation to remove much more content. And on the other hand, there were people saying that, look, we want more stuff kept on, we're being banned and we don't even know why. And the reason is, like I explained, sometimes content moderation happens in real time and people make decisions in real time, which are sometimes opaque and not quite clear.

And there's subjectivity involved there obviously.

That's right.

And that's AI is not infallible as we've come to realize with ChatGPT.

Absolutely.

So that's got a long way to go before you can completely rely on that. As we think about the board itself with the invitation out to Elon to join them, how was the board composed and what was the composition of the salary structure of some of the senior executives at Twitter?

So a couple of interesting things about the board's composition is the board didn't have as large of an equity stake in Twitter as we would normally expect, and probably even more surprisingly, at the time of case writing. This would be several months after Elon Musk's acquisition, remember people started speaking up, there was pushback from the board itself, we found that the Twitter board did not use Twitter very much. And we would've expected that the Twitter board would be very active. I mean, there are board members that have tweeted zero times to the point of case writing. Now, when it comes to compensation, I think an interesting thing to highlight is that Twitter used stock-based compensation, the short form, which is SBC for many of their employees. And what this really means is compensating people not with a direct salary, but with ownership in the firm. And as we discussed earlier, Twitter's value kept declining, which in practice meant that people had to be incentivized, be issued more stock, which then continued to decline. So more than other firms in tech industry, which granted do use stock-based compensation to a large extent, Twitter relative to them used it quite a bit more. So employees relied heavily on stock ownership for compensation at Twitter.

Which you think would be a motivating force, but in this case it doesn't sound like it necessarily was with that entrenched culture of risk aversion. Musk used Twitter, though, he used it a lot, he was a pretty active voice on Twitter. Is that fair to say?

Definitely fair to say, he might even be the most active person in terms of what he is willing to say out there among the top people on Twitter.

At one point, the case alludes to the fact that Musk thought about starting his own social platform like, "I'm done with Twitter, I'm just going to create something from scratch." And he talked to Jack Dorsey and I thought it was interesting what Jack's advice was on starting a social platform. What did he advise him?

So, we have to remember here that through Dorsey's leadership and his departure from the firm, I think there's a real sense of regret on Dorsey's part, and he really, I think takes a lot of time to reflect on what could have gone differently at Twitter. And so as a result of that, Dorsey's advice to Musk is actually that Twitter shouldn't even really be a business. What we really need out there is an open source protocol similar to the messaging app, Signal where we just have a protocol for information transfer. And from Dorsey's perspective, the key advantage of that is that is the kind of protocol and platform that can't be controlled by advertisers and can't be controlled by governments. And that's something that I think Dorsey looks really regretfully upon about where Twitter has gone.

That also poses all kinds of complications from a business perspective because how do you make that a revenue generating enterprise, right?

Absolutely. The open source, of course is difficult to monetize. And on top of that, the truth is free speech is actually difficult to monetize. So we have the most free speech today in, for example, if you're on a message group in WhatsApp with your friends or you're on the forum, 4chan. However, advertisers and a whole bunch of other parties don't want anything to do with that. And it's hard to bring that money in.

So how did the board react to Musk's takeover bid?

So the board definitely resisted the takeover bid at first. I think some people have thought there was a better valuation out there, and I think they didn't quite say this publicly, but I would suspect that some of them also thought it would not be a good future for humanity for Musk to be owning Twitter. Now after that point, a couple different things happened. I mean, the first is that the company and the board did go out to shop the company around to other possible acquirers, and they ended up being declined by Disney, Google and Microsoft.

They did have an opportunity at one point though to probably walk away from Musk because he was really equivocating about his decision. I always wondered why they didn't take that if they were so concerned about him stepping in and taking over.

And Brian, this is I think a real quirk of history here, as you know and we all know that beginning in that time period, there's a real decline in the technology stock market valuations for Twitter and all kinds of technology companies. And it became clear at that point in the time period that, in the summer of 2022, that in reality Twitter's valuation was much lower in the public markets than it would be for the acquisition price that Elon Musk had probably overbid on earlier that spring. And so this became financially the right decision, I think for the shareholders. And it's a really funny situation to see Musk and the board switching their own positions on whether or not they want to do this. And I think it's pretty clear from what happened in that summer of 2022 that Musk knew he had overpaid and was trying to dig himself out of it.

So here he is walking in with the kitchen sink into the lobby last summer of with that sort of obscure reference to let this sink in. I think that was what he was trying to get across with people. And he finds himself in a situation, what are some of the options that he has to think about as he looks at the situation he's inherited here?

And so as Musk has taken over the company, he had to borrow a lot of money in order to do so. So, the cloud that is hanging over him right now is over a billion dollars in interest payments a year. And so we have to do something to make sure the business can make those interest payments. And of course, we have to think about revenue options. And there's at least three revenue options that we know Musk and his team have been debating. And so the first option is to maintain or improve the advertising business. And again, this is something that Twitter has struggled with in the past, but there's definitely possibilities in how do they can do it better. But at the same time, as we know from Musk's personal interest, he's not particularly interested in having advertising be his big segment of the revenue. One, because it conflicts with his notion of free speech. The advertisers do want a safe environment of content. The second is that it also conflicts with his ability to self-aggrandize on the platform. And so advertising is important, but I think they want to get out of it. The second revenue opportunity that Musk is particularly excited about is the notion of premium user memberships. And there's different ways this could be structured, but you can imagine the idea here is that users would pay $8 a month or more and get a set of premium features. I think one of the hallmarks of that our listeners might be aware of is the famed-up blue check-mark and the idea that we could sell people verification in the blue check-mark as part of that premium membership. I think there's other possibilities of really making a premium membership stand out. For example, if you have a premium membership, they might be able to boost your tweets above other people that don't. And you could imagine what else they’d do. But again, in the past, in other businesses and for Twitter itself, getting people to pay for a social media account is not something that historically works. And again, it directly works against the network effects you need to make the business work. Third, and again, another thing Musk is particularly excited about is the notion of turning Twitter into an everything app. And you can use, for example, WeChat in China as a model, but the idea here is Twitter could, for example, go into financial services, peer-to-peer payments and monetize in that direction. The interesting part of the history here for that option is that remember that Musk was a founder of x.com, which was joined up with PayPal, and remember that Musk was actually an executive that was fired from PayPal. And so this is a chance if he could do the financial services thing, this is a chance for him to achieve what he had failed to do at the very, very beginning of his career. There's one fourth option I want to mention here, Brian, and this is not something Elon Musk says, but it's something that we ask our students about as a possibility. The final possibility here is to break up the company. And so the idea here is that you would separate the social graph and database part of the business from the front-end user-facing advertising-facing application. And so the idea is that the API would be provided by the backend business to the front-end business and the front end business would pay for the right to use that API and maintain ongoing application activity. Now, the reason this is interesting and we want students to debate about it, is that this opens up the possibility that backend social graph business could actually re-license the API to other new third-party applications. And really this is the idea of taking Twitter back to the pre-2010, the pre-Tweetie days.

Yeah, back in the good old days as it were. It seems also just to the casual observer of which we'll call myself, that Elon has taken a step backwards in terms of being so forthright about his ideas for the company. I think he was waffling on the blue check-mark thing, and I think he was making people nervous, frankly, and he seems to have recognized that and sort of taken a step back and is allowing others to come forward as the sort of business minds around where he's taking Twitter. Is that fair to say?

I think that the early days of what we've seen in Musk leadership here are kind of symbolic of the broader leadership style he has, which is one definitely of risk taking. And I just want to remind our listeners here that Musk comes from a culture say of SpaceX where they can blow up a hundred million dollar rockets and you just move on with your life and it's fine. So I have to imagine from his perspective, messing up the blue check-mark is not that big a deal.

Not a big deal.

That's right. It's a risk he can take. And so I think they're ready to take risks, but I do think he has recognized progressively that he really needs to be conscious of the stakeholders. I think in his early days he was much more antagonistic to advertisers, but once he took over, he reached out to the advertisers saying, look, I want to keep you guys along, we'll keep things safe around here.

And pretty antagonistic to his employee base too. I mean that it has not been a comfortable place to be an employee for the last year or so.

Certainly not from the perspective of the people that used to work at Twitter. And so he's been very aggressive about imposing in terms of what he calls an extremely hardcore culture, and that is unusual to how Twitter operates, that's unusual also to how say Google operates, but that is actually how he operates Tesla and SpaceX and that kind of very, very intense environment. And it seems to work okay there. Although again, lots and lots of turnover in those companies as well.

Right. So you've got probably one of the biggest risk-takers in business taking over one of the most risk-averse companies in tech. Interesting.

That's exactly right.

Yeah, it could work. It could be destructive.

Hey, this has been a great conversation. I have one more question and I'll let each of you respond to it in your own way, but I'm wondering if there's one thing you want listeners to remember about the Twitter case, what would it be?

Many technology companies today, Twitter especially, but there's others too, need to go through serious strategic change in order to make those businesses work, both in terms of reigniting growth or in terms of shifting to profitability. We want our students and our listeners here to look at this Twitter situation as an opportunity to learn about the right and possibly wrong way of managing strategic change. And so what we advise people to do is to start by looking forward at a vision. So where do you want the company to go? And then to reason back to the things you want to preserve in the business and the things you want to change and how quickly you want make those changes.

Yeah, Goran.

I think the big takeaway that Andy had mentioned this is thinking about the speed of change. So one thing Elon Musk clearly highlighted, the moment he took the company over and fired half the employees was he wants to move really fast. And I think the initial reaction is "that was way too fast." He could have taken longer. He potentially had to rehire some of the people he'd let go. But I think the question we'd like students to think about is: what is the right speed? We know that his resources are limited. We know he has a billion-dollar interest payment to do. We know the company probably has more employees than it can handle at the moment. We see Meta is now letting people go; same with Amazon. So the question is, if you don't want to fire people, where will the revenue come from? And if you do, how long does it take? Is it 90 days? Is it 30 days? Is it a hundred days? It probably isn't on the first day. So I think the speed of change really is an interesting takeaway from this case.

Well, it's a great case. It's been a great conversation. Andy Wu, Goran Calic, thank you for joining me on Cold Call .

Thank you, Brian.

It was a pleasure. If you enjoy Cold Call , you might like our other podcasts, After Hours , Climate Rising , Deep Purpose , Idea Cast , Managing the Future of Work , Skydeck , and Women at Work . Find them on Apple, Spotify, or wherever you listen, and if you could take a minute to rate and review us, we'd be grateful. If you have any suggestions or just want to say hello, we want to hear from you. Email us at [email protected] . Thanks again for joining us. I'm your host, Brian Kenny, and you've been listening to Cold Call , an official podcast of Harvard Business School and part of the HBR Podcast Network.

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Examples of Strategic Management: Learn from Industry Leaders

Welcome to the world of strategic management, where businesses navigate the complex landscape of competition, innovation, and growth. In this comprehensive guide, we’ll delve into the fascinating realm of strategic management by exploring real-world examples of how some of the most successful companies and organizations have used strategic thinking to achieve remarkable results.

Strategic management is the art and science of formulating, implementing, and evaluating cross-functional  decisions that enable an organization to achieve its long-term objectives. It’s a critical aspect of business leadership, driving sustainable success and ensuring that companies not only survive but thrive in dynamic markets.

Our journey will take us through various sectors, from technology giants and automotive pioneers to startups, nonprofits, and government entities. By examining both successes and failures, you’ll gain valuable insights into the principles and practices of strategic management, allowing you to apply these lessons to your professional endeavors.

So, without further ado, let’s embark on this enlightening exploration of strategic management through the lens of remarkable examples from the business world.

Strategy Management

Strategy management is the systematic process of formulating, implementing, and evaluating strategies to achieve organizational goals and sustain a competitive advantage.

Understanding Strategic Management

Before we dive into the captivating examples of strategic management, let’s establish a solid understanding of what strategic management entails.

Strategic management is the comprehensive process of defining an organization’s direction,  making decisions  decisions on allocating its resources to pursue this direction and guiding the implementation of these  decisions .

It’s not a one-time task but rather an ongoing, dynamic process that aligns an organization’s internal capabilities with the demands of its external environment.

Key Components of Strategic Management

• Setting Clear Objectives: Strategic management begins with establishing clear, specific, and measurable objectives. These objectives provide a sense of purpose and direction for the entire organization.
• Environmental Analysis: Understanding the business environment is crucial. This includes analyzing industry trends, competitive forces, market dynamics, and potential risks and opportunities.
• Strategy Formulation: Once the organization’s objectives are defined and the external environment is assessed, the next step is developing a strategy. This involves determining how the organization will achieve its objectives, often considering factors like differentiation, cost leadership, or niche focus.
• Strategy Implementation: Formulating a strategy is only the first step; implementing it is equally important. This phase involves aligning the organization’s structure, processes, people, and culture with the chosen strategy.
• Evaluation and Control: Continuous evaluation and control mechanisms are necessary to ensure that the chosen strategy is producing the desired results. If not, adjustments may be required.

Now that we have a solid foundation in place, let’s explore how these principles are put into action with real-world examples of strategic management across diverse industries.

Strategic Management Frameworks and Tools

Strategic management involves the use of various frameworks and tools to analyze, plan, and execute strategies effectively. Understanding these tools is essential for any business professional.

Here are some of the most commonly used ones:

1. SWOT Analysis: A framework that helps organizations identify their Strengths, Weaknesses, Opportunities, and Threats. It’s a fundamental tool for  strategic planning .

2. PESTEL Analysis: This tool evaluates the Political, Economic, Sociocultural, Technological, Environmental, and Legal factors that can impact an organization.

3. Porter’s Five Forces: Developed by Michael Porter, this framework assesses the competitive forces within an industry, helping organizations determine their competitive position.

4. BCG Matrix: It’s a portfolio analysis tool that helps organizations assess their product offerings and allocate resources effectively. Products are categorized as Stars, Cash Cows, Question Marks, or Dogs.

5. Balanced Scorecard: This performance measurement framework considers financial and non-financial factors, allowing organizations to track progress toward their strategic goals.

6. Scenario Planning: In an uncertain environment, scenario planning involves creating multiple future scenarios to prepare for various outcomes.

7. Key Performance Indicators (KPIs): These are specific metrics that organizations track to measure progress toward strategic objectives.

The 5 Phases of the Strategic Management Process

Strategic management is a comprehensive and iterative process that guides organizations in making informed  decisions , formulating strategies, implementing them effectively, and evaluating their outcomes.

Understanding the various phases of the strategic management process is essential for achieving strategic objectives.

Let’s delve into each phase:

Examples of Strategic Management in Action

In this section, we’ll delve into captivating examples of strategic management from various sectors. These case studies offer valuable insights into how organizations leverage strategic thinking to thrive in competitive markets, innovate, and adapt to changing circumstances.

Stay tuned as we explore the strategic moves and  decisions made by industry leaders that have shaped their success.

1. Strategic Management at Apple Inc.

Our first stop on this tour of strategic management excellence is none other than Apple Inc. Founded in 1976, Apple has become a household name synonymous with innovation and cutting-edge technology.

Apple’s Strategic Vision: Apple’s co-founder, Steve Jobs, was known for his visionary approach to product development. He famously said, “Innovation distinguishes between a leader and a follower.”

Apple’s strategic management has been deeply rooted in this philosophy, focusing on creating products that are not just technologically advanced but also beautifully designed and user-friendly.

Key Strategic Moves:

• Product Diversification: Apple started as a computer company, but it didn’t stop there. The introduction of the iPod, iPhone, iPad, and Apple Watch showcased Apple’s ability to diversify its product portfolio strategically.
• Ecosystem Integration: Apple’s ecosystem is a prime example of strategic management. The seamless integration between devices, software (iOS, macOS), and services (Apple Music, iCloud) fosters customer loyalty and increases brand stickiness.
• Retail Strategy: Apple’s retail stores are strategically positioned in high-traffic locations, offering not just products but experiences. The design of Apple Stores, along with well-trained staff, creates a unique customer journey.
• Supply Chain Mastery: Efficient supply chain management allows Apple to deliver products to customers promptly. The company’s ability to source components globally and assemble them on time is a strategic advantage.
• Brand Image: Apple has meticulously cultivated its brand image as an innovator that challenges the status quo. This strategic positioning has helped Apple command premium prices for its products.

Takeaway: Apple’s strategic management demonstrates the importance of a clear vision, innovation, diversification, and a relentless focus on the customer experience.

2. Toyota: Pioneering Operational Excellence

Our next example hails from the automotive industry, and it’s none other than Toyota. Toyota’s approach to strategic management has revolutionized manufacturing processes and set new standards for operational efficiency.

Toyota’s Strategic Vision: Toyota’s vision revolves around “delivering better products and better services.” Its strategic management is grounded in the philosophy of “continuous improvement” or Kaizen.

• Lean Manufacturing: Toyota pioneered the concept of lean manufacturing, aiming to reduce waste, increase efficiency, and improve quality. The Toyota Production System (TPS) is a renowned example of strategic management focused on operational excellence.
• Global Expansion: Toyota strategically expanded its operations globally, becoming one of the largest automakers in the world. Its diverse product range caters to different markets and customer segments.
• Innovation in Hybrid Technology: Toyota’s introduction of the Prius, the world’s first mass-produced hybrid car, showcased its strategic commitment to sustainability and innovation.
• Quality Control: Toyota’s relentless pursuit of quality and its “stop the line” policy emphasizes its commitment to delivering exceptional products.
• Supply Chain Resilience: Toyota’s strategic management includes building a resilient supply chain. This was evident when the company navigated supply chain disruptions caused by Japan’s 2011 earthquake and tsunami.

Takeaway: Toyota’s strategic management teaches us the importance of operational excellence, continuous improvement, and a long-term commitment to quality and sustainability.

3. Airbnb: Disrupting the Hospitality Industry

Our final example brings us to the world of sharing economy and disruptive innovation—Airbnb.

Airbnb’s Strategic Vision: Founded in 2008, Airbnb’s strategic vision is to “create a world where anyone can belong anywhere.” It disrupted the traditional hospitality industry by leveraging technology to connect travelers with hosts offering unique accommodations.

• Platform-Based Model: Airbnb’s strategic management centers on its platform-based business model. It doesn’t own properties but provides a marketplace for hosts and guests to transact.
• Global Expansion: Airbnb strategically expanded its presence to become a global platform with listings in nearly every country. This expansion was supported by localization efforts and strategic partnerships.
• User-Centric Design: Airbnb’s focus on user experience and design thinking has been a strategic advantage. The platform is user-friendly, with features like reviews, secure payments, and personalized recommendations.
• Community Building: Airbnb strategically built a sense of community among hosts and guests through its branding and initiatives like host meetups and the “Airbnb Community Center.”
• Diversification: Over time, Airbnb strategically diversified its offerings beyond accommodations to include experiences and adventures, further enhancing its value proposition.

Takeaway: Airbnb’s strategic management illustrates the power of disruptive innovation, platform-based models, user-centric design, and the importance of building a strong community.

4. Amazon: Mastering Customer-Centricity

Amazon, the e-commerce giant founded by Jeff Bezos, epitomizes strategic management in the digital age. Its relentless focus on customer-centricity has propelled it to the forefront of the global retail industry.

Amazon’s Strategic Vision: Amazon’s vision is “to be Earth’s most customer-centric company, where customers can find and discover anything they might want to buy online.” Their strategic management revolves around leveraging technology to enhance customer experience.

• eCommerce Dominance: Amazon strategically disrupted the retail industry by pioneering e-commerce. They focused on providing customers with vast product selections, competitive prices, and convenient delivery options.
• Amazon Prime: The introduction of Amazon Prime, a subscription service offering free shipping and access to streaming services, was a strategic move that boosted customer loyalty and retention.
• Innovation Hub: Amazon’s strategic management includes heavy investments in innovation. They introduced the Kindle e-reader, Amazon Web Services (AWS), and Amazon Echo, expanding their reach into various tech sectors.
• Marketplace Model: Amazon’s strategic  decision to allow third-party sellers on its platform broadened its product offerings and created a win-win situation for sellers and customers.
• Supply Chain Optimization: Amazon’s strategic brilliance extends to supply chain management, allowing them to fulfill orders efficiently. This includes investments in robotics and a vast distribution network.

Takeaway: Amazon’s strategic success highlights the significance of customer-centricity, innovation, and adaptability in today’s dynamic business landscape.

5. Coca-Cola: Branding Mastery

Coca-Cola, a global beverage giant, is renowned for its strategic management in brand building and marketing. It’s a classic example of how a company can turn a product into an iconic global brand.

Coca-Cola’s Strategic Vision: Coca-Cola’s vision is “to refresh the world in mind, body, and spirit.” Their strategic management revolves around creating an emotional connection with consumers through their brands.

• Brand Portfolio: Coca-Cola strategically expanded its brand portfolio beyond Coca-Cola to include a variety of beverages such as Diet Coke, Fanta, and Sprite, catering to diverse consumer preferences.
• Global Reach: Coca-Cola’s strategic global expansion made its products available in over 200 countries. This extensive reach bolsters its brand recognition and market presence.
• Marketing and Advertising: Coca-Cola’s iconic marketing campaigns, including the “Share a Coke” campaign and memorable Super Bowl ads, showcase its strategic emphasis on advertising and brand promotion.
• Sponsorships and Partnerships: Coca-Cola’s strategic partnerships with major sporting events like the FIFA World Cup and the Olympics demonstrate their commitment to associating their brand with positive experiences.
• Product Diversification: Recognizing evolving consumer preferences, Coca-Cola has strategically diversified its product offerings to include healthier options and reduced-sugar beverages.

Takeaway: Coca-Cola’s strategic management illustrates the power of branding, marketing, and diversification in building a globally recognized and cherished brand.

6. Netflix: Pioneering Digital Streaming

Netflix, the global streaming giant, is a prime example of a company that strategically disrupted the entertainment industry by transitioning from DVD rentals to digital streaming.

Netflix’s Strategic Vision: Netflix’s vision is “to become the best global entertainment distribution service, licensing entertainment content around the world.” Their strategic management focuses on providing high-quality content to subscribers.

• Content Creation: Netflix strategically shifted from being a content distributor to a content creator. Their original content, like “House of Cards” and “Stranger Things,” has garnered critical acclaim and subscriber loyalty.
• Global Expansion: Netflix strategically expanded globally, making its streaming service available in over 190 countries. This global reach is a testament to their strategic vision of becoming a global entertainment powerhouse.
• Data-Driven Personalization: Netflix’s strategic use of data analytics enables it to personalize content recommendations for each user, enhancing the viewing experience and subscriber retention.
• Subscription Model: Netflix’s strategic  decision to adopt a subscription-based model allows it to generate steady revenue and invest heavily in content creation.
• Technology Investment: Netflix’s strategic investment in streaming technology ensures a seamless and high-quality streaming experience for subscribers.

Takeaway: Netflix’s strategic management highlights the significance of content creation, global expansion, data-driven personalization, and subscription-based revenue models in the digital entertainment industry.

7. Google: Dominating Online Search and Advertising

Google, led by Larry Page and Sergey Brin, is a strategic management powerhouse that transformed online search and digital advertising.

Google’s Strategic Vision: Google’s vision is “to provide access to the world’s information in one click.” Their strategic management revolves around organizing information and making it universally accessible and useful.

• Search Engine Dominance: Google’s strategic focus on delivering highly relevant search results and a user-friendly interface made it the world’s leading search engine.
• Advertising Model: Google’s strategic monetization through pay-per-click advertising, primarily through Google Ads (formerly AdWords), revolutionized digital advertising.
• Android Ecosystem: Google strategically developed the Android operating system, powering a significant portion of the world’s smartphones and expanding its ecosystem.
• Cloud Services: Google Cloud, part of Alphabet Inc. (Google’s parent company), is strategically positioned to compete in the cloud computing market.
• Innovation Ventures: Google’s strategic approach to innovation includes projects like Google X, focusing on moonshot technologies like self-driving cars, and Project Loon for internet connectivity in remote areas.

Takeaway: Google’s strategic management highlights the importance of search engine dominance, advertising revenue models, ecosystem development, and moonshot innovation.

8. Facebook (Meta Platforms): Connecting the World

Meta Platforms, formerly Facebook, under Mark Zuckerberg’s leadership, is a strategic management example that transformed social networking and digital communication.

Meta Platforms’ Strategic Vision: Meta’s vision is “to give people the power to build community and bring the world closer together.” Their strategic management centers on connecting people globally.

• User Base Expansion: Meta strategically expanded its user base by acquiring platforms like Instagram and WhatsApp, diversifying its social media portfolio.
• Advertising Monetization: Meta’s strategic monetization primarily relies on targeted advertising, offering advertisers extensive user data for precise targeting.
• Virtual Reality (VR) and Augmented Reality (AR): Meta is strategically investing in VR and AR technologies, envisioning a future of interconnected virtual experiences.
• Metaverse: The strategic focus on building the metaverse, a collective virtual shared space, aims to redefine digital interactions and experiences.
• Data Centers and Connectivity: Meta’s strategic investments in data centers and internet connectivity infrastructure support its global operations.

Takeaway: Meta Platforms’ strategic management emphasizes user engagement, advertising-driven revenue models, innovation in VR and AR, and the vision of a metaverse future.

9. Nike: Mastering Branding and Innovation

Nike, led by visionary figures like Phil Knight and Mark Parker, showcases strategic brand management and innovation in the sportswear industry.

Nike’s Strategic Vision: Nike’s vision is “to bring inspiration and innovation to every athlete in the world.” Their strategic management revolves around innovation, athlete endorsements, and brand identity.

• Iconic Branding: Nike’s strategic branding includes the creation of the famous “Swoosh” logo, making it one of the world’s most recognizable brands.
• Endorsement Deals: Nike’s strategic partnerships with athletes like Michael Jordan, LeBron James, and Serena Williams bolster brand recognition and aspiration.
• Innovation in Footwear: Nike’s strategic focus on footwear innovation, such as Air Max and Flyknit technologies, sets industry standards.
• Marketing Campaigns: Nike’s strategic marketing campaigns, like “Just Do It,” resonate with consumers and reinforce the brand’s message.
• Sustainability Initiatives: Nike’s strategic commitment to sustainability includes efforts like “Reuse-A-Shoe,” recycling old athletic shoes into sports surfaces.

Takeaway: Nike’s strategic management underscores the power of iconic branding, athlete endorsements, product innovation, emotionally resonant marketing, and sustainability in the sportswear sector.

10. Tesla: Revolutionizing Electric Vehicles

Tesla, spearheaded by visionary entrepreneur Elon Musk, represents a paradigm shift in the automotive industry and strategic management.

Tesla’s Strategic Vision: Tesla’s vision is “to create the most compelling car company of the 21st century by driving the world’s transition to electric vehicles.” Their strategic management revolves around sustainability, innovation, and disruption.

• Electric Vehicle (EV) Leadership: Tesla’s strategic focus on electric vehicles disrupted the automotive industry and accelerated the transition to sustainable transportation.
• Autonomous Driving: Tesla’s strategic integration of autonomous driving features, such as Autopilot, showcases a commitment to innovation and safety.
• Gigafactories: Tesla’s strategic establishment of Gigafactories globally ensures efficient EV production and battery technology development.
• Direct-to-Consumer Sales: Tesla’s strategic approach of selling directly to consumers disrupted traditional dealership models.
• Energy Solutions: Tesla’s strategic diversification into solar energy and energy storage with products like Solar Roof and Powerwall demonstrates a broader vision beyond EVs.

Takeaway: Tesla’s strategic management exemplifies the transformative power of innovation, sustainability, direct sales models, and diversification into complementary industries.

Examples of Strategic Failures

1. nokia: missed opportunities in the smartphone era.

Nokia, once an undisputed leader in mobile phones, serves as a notable example of strategic failure. While they had a strong market presence, Nokia failed to adapt to the smartphone revolution effectively.

Strategic Missteps:

• Lack of Innovation: Nokia was slow to innovate and adapt to changing consumer preferences. They stuck to their traditional mobile phone models while competitors were developing smartphones.
• Ignoring the Ecosystem: Nokia underestimated the importance of a robust app ecosystem, an area where Apple’s iOS and Google’s Android thrived.
• Ineffective Leadership: Frequent changes in leadership and organizational restructuring led to a lack of focus and direction.

Takeaway: Nokia’s downfall underscores the importance of innovation, adaptability, and staying attuned to market trends, even for industry leaders.

2. Blockbuster: Failing to Embrace Digital Streaming

Blockbuster, a giant in the video rental industry, faced a catastrophic strategic failure due to its inability to embrace digital streaming.

• Lagging Technology: Blockbuster was slow to adopt digital streaming technology and underestimated its potential.
• Failure to Adapt: While Netflix was disrupting the industry with its subscription-based streaming service, Blockbuster clung to its brick-and-mortar rental model.
• Missed Opportunities: Blockbuster had the chance to acquire Netflix early on but declined, which proved to be a costly  decision .

Takeaway: Blockbuster’s demise highlights the critical importance of staying ahead of technological trends and being open to strategic partnerships.

3. Kodak: Missed the Digital Photography Wave

Kodak, a pioneer in photography, failed to adapt to the digital photography revolution, leading to a decline in its market presence.

• Overreliance on Film: Kodak was heavily reliant on film-based photography and underestimated the shift toward digital photography.
• Failure to Innovate: While they did develop digital camera technology, Kodak didn’t effectively commercialize it due to concerns about cannibalizing their film business.
• Lack of Vision: The company failed to envision a future where digital photography would dominate.

Takeaway: Kodak’s story emphasizes the importance of continuously innovating and not being afraid to disrupt your business model when necessary.

4. Blackberry: Ignoring the Smartphone Revolution

Blackberry, once synonymous with secure mobile communication, faltered when it failed to adapt to the rise of touchscreen smartphones.

• Innovation Gap: Blackberry’s failure to innovate and transition to touchscreen devices left it behind competitors like Apple and Samsung.
• Inadequate App Ecosystem: Blackberry’s app ecosystem couldn’t compete with the iOS App Store and Google Play Store.
• Complacency: Blackberry’s leadership was slow to recognize the competitive threat posed by touchscreen smartphones.

Takeaway: Blackberry’s decline underscores the need for established companies to remain agile and innovative in the face of evolving technologies and consumer preferences.

5. Xiaomi: Expanding Too Quickly

Xiaomi, a Chinese smartphone manufacturer, experienced a strategic setback when it expanded too rapidly into international markets.

• Overseas Expansion: Xiaomi aggressively expanded into markets outside China, including India and Europe, which stretched its resources.
• Supply Chain Issues: Rapid expansion led to supply chain challenges, including shortages of products in key markets.
• Brand Awareness: Xiaomi faced challenges in building brand awareness and trust outside China.

Takeaway: Xiaomi’s experience emphasizes the importance of measured, sustainable international expansion and the need for strong supply chain management.

These examples of strategic failures serve as cautionary tales, illustrating the significance of adaptability, innovation, foresight, and market awareness in the world of strategic management.

Lessons Learned from Strategic Management Examples

1. innovation is a game-changer.

• Key Lesson: Innovating in products, services, or business models can disrupt industries and create new market leaders.
• Examples: Apple’s continuous innovation in consumer electronics, Tesla’s pioneering electric vehicles, and Dollar Shave Club’s subscription-based razor service.

2. Customer-Centric Approach Pays Off

• Key Lesson: Prioritizing customer needs and preferences can lead to strong brand loyalty and business growth.

Examples: Amazon’s customer-centric e-commerce, Airbnb’s focus on user reviews and trust, and Warby Parker’s “Home Try-On” program.

3. Adaptability is Crucial

• Key Lesson: Being adaptable to changing market conditions and consumer trends is essential for long-term success.
• Examples: Netflix’s shift from DVD rentals to streaming, Slack’s evolution as a workplace collaboration platform, and Airbnb’s expansion into experiences.

4. Effective Marketing Matters

• Key Lesson: Creative and effective marketing strategies can generate significant attention and customer acquisition.

Examples: Dollar Shave Club’s viral marketing video, Airbnb’s storytelling approach, and Apple’s iconic advertising campaigns.

5. Ecosystem Development Drives Growth

• Key Lesson: Building an ecosystem of products, services, or partnerships can enhance value for customers and drive business growth.

Examples: Apple’s ecosystem of devices and services, Slack’s third-party integrations, and Tesla’s Supercharger network.

6. Sustainability is a Competitive Advantage

• Key Lesson: Incorporating sustainability and environmental responsibility into business strategies can attract socially conscious consumers and enhance brand reputation.

Examples: Tesla’s commitment to sustainable transportation, Airbnb’s Green Hosting program, and Patagonia’s eco-friendly practices.

7. Digital Transformation is Inevitable

• Key Lesson: Embracing digital technologies and online platforms is crucial in today’s business landscape.

Examples: Amazon’s digital retail dominance, Netflix’s streaming platform, and Tesla’s over-the-air software updates.

8. Diversification Reduces Risk

• Key Lesson: Diversifying product or service offerings can mitigate risk and expand revenue streams.

Examples: Tesla’s expansion into solar energy and energy storage, Amazon Web Services (AWS), and Apple’s ecosystem diversification.

9. Trust and Transparency Build Loyalty

• Key Lesson: Establishing trust through transparent practices and customer reviews can foster loyalty and credibility.

Examples: Airbnb’s user review system, Tesla’s commitment to safety and quality, and Amazon’s customer feedback-driven improvements.

10. Long-Term Vision is Essential

• Key Lesson: Maintaining a clear and ambitious long-term vision guides strategic decisions and sustains business growth.
• Examples: Amazon’s focus on long-term value over short-term profits, Tesla’s mission to accelerate the world’s transition to sustainable energy, and Apple’s dedication to innovation.

These lessons illustrate the diverse strategies and approaches employed by successful companies across various industries.

By studying these examples and applying the core principles to your own business, you can develop more effective strategic management practices and enhance your organization’s competitiveness and growth prospects.

In this comprehensive exploration of strategic management, we’ve dissected a multitude of examples, both successes and failures, from diverse industries. Through these cases, we’ve unearthed invaluable lessons that can guide businesses towards prosperity and sustainability.

Key takeaways include the paramount importance of innovation, adaptability, customer-centricity, and sustainability.

It’s not enough to merely acknowledge these lessons. To thrive in today’s competitive landscape, businesses must actively apply strategic management principles. Whether you’re a startup seeking growth, a corporate giant aiming to stay agile, or an organization striving for a brighter, more sustainable future, strategic management offers the compass to navigate these endeavors.

Lastly, it’s crucial to understand that strategic management is not static; it evolves alongside technology, market trends, and consumer behaviors. The examples we’ve examined serve as beacons of innovation and adaptation.

As we move forward, new case studies will emerge, reshaping our understanding of effective strategic management. Stay vigilant, stay adaptable, and continue learning from the ever-changing landscape of strategic management.

Tumisang Bogwasi

2X Award-Winning Entrepreneur | Empowering Brands to Generate Leads, Grow Revenue with Business Strategy and Digital Marketing | Founder, CEO of Fine Group

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Elon Musk & Twitter: The case study of all case studies

By Rebecca Zucker Partner, Next Step Partners

Leadership Lessons on what NOT to do: Elon Musk & Twitter

In the few weeks since Elon Musk took over Twitter, many of us have been on the sidelines watching a business school case study unfold that will be taught for decades…and waiting to see what he does next. First, he cut half of Twitter’s 7,500 employees and then promptly realized he needed some of them, asking some to come back. Whoops. 

Elon then issued an ultimatum that remaining employees would need to commit to a “hardcore” Twitter or leave. He said, “This will mean working long hours at high intensity,” continuing that “only exceptional performance will constitute a passing grade.” Employees were given 24 hours to decide. 

Simultaneously, he revoked the company’s policy that allowed employees to work remotely on a permanent basis and required employees to work onsite (never mind that many employees who opted into this remote policy moved out of commuting range to Twitter’s offices). He has since walked back on this edict. He then cut off badge access for everyone, accidentally locking himself out. Whoops again. 

Where do I even begin in breaking down this epic failure in leadership? There is so much wrong here it’s mind-blowing. Here are 7 leadership failures fueling this colossal dumpster fire that we can all learn from:

Hardcore isn’t motivating

First, let’s start with the word “hardcore.” More than just a poor choice of words, it reeks of insecure bravado. I can’t think of a more “tech bro” term that would instantly turn people off and alienate them – even actual tech bros. Despite an economy that’s in the process of shifting from an employee to employer market, after a pandemic and the great resignation where people have been exhausted and depleted, looking for improved work-life balance and more meaningful work where they can feel valued, I don’t think most people would be excited to opt into a “hardcore” work environment, or hardcore anything for that matter. Turnarounds and restructurings require hard work, but hard work doesn’t have to mean “hardcore.” It’s a marathon, not a sprint.

No inspirational vision

Without an inspiring vision for where Elon plans to take the company (or any vision, for that matter) – and clear communication of said vision – employees are left scratching their heads in confusion around not only what’s happening in the present, but also having no picture painted for them of where the company is ultimately headed, versus being enrolled and motivated to pursue something big and exciting, where they’d want to – or would even consider, for that matter – working long hours or to strive for “exceptional” performance. One employee who opted out, when given the choice last week, tweeted that he left because “I no longer knew

what I was staying for…There was no vison shared with us. No 5-year plan like at Tesla…There were rumors that the new vision might be radically different…And there was no communication from leadership to dispel them or set the vision.” 

Impossible and ambiguous standards

Now, let’s address Elon’s seemingly impossible, ambiguous, and highly subjective standard of “ exceptional performance.” What does this actually mean? If something is the exception, then it’s not the norm. Does this mean you need to rate as an A+ player to stay on as an employee? Be in the top 10%? Top 2%? If these are the passing grades, then most will fail. That’s not exactly motivating. How will employees’ contributions be evaluated? Are there actual, measurable goals? Do they have a say in creating those goals? Do they have the resources to achieve those goals? All totally unclear. When he says, “only exceptional performance will constitute a passing grade,” it sounds more like a vague threat where, let’s face it, Elon could fire someone because he doesn’t like the socks they wore that day. 

Corporate bullying

While Elon has technically given his remaining employees a choice – a very binary choice – he made them choose under duress with a ridiculously tight deadline. No one likes to be strong-armed or bullied into a decision or to have their livelihood or career toyed with. Bullies are inherently insecure people who pick on others more vulnerable than them to feel stronger or better about themselves. An estimated 1,200 of his remaining employees left as a result of his ultimatum and this number will likely continue to tick up. A good number of those who chose to stay likely did so because they either needed the paycheck or their work visas would be in jeopardy if they opted out. Either way, his bullying behavior invokes a sense of powerlessness or loss of agency or control in the remaining employees. You want people to feel like they want to be there, and not like they have to be there.

Impulsive and reckless decision-making

I’m all for being decisive and taking swift action, but not without being informed. There’s value to be had in soliciting the input of those closest to the actual work. Elon’s impulsive and reckless decisions, such as immediately firing the whole accessibility engineering team, its curation team that helps address misleading or false claims, and content moderators who track hate on the platform, have caused real problems. In the days since his takeover and following these firings, I personally noticed the floodgates open, unleashing antisemitic, racist, and vulgar content that seemed to come out of nowhere. It was noticed by advertisers, too, many of whom left as a result, jeopardizing the 90% of company revenues that come from advertising. Mostly, his extreme haste shows a fundamental lack of curiosity and desire to listen, a lack of humility and an abundance of hubris. This combination doesn’t tend to work out well for anyone.

Destruction of psychological safety

In firing those who publicly and privately disagreed with him – going as far as tasking his team members with combing through tweets to look for employees who didn’t agree with him – he sent a clear message of “If you disagree with me, you will be fired.” That somehow, disagreement was a personal betrayal or treasonous in some way. Firing people who disagree with you is more than enough to instill a culture of fear, shut people down, and have them not speak up when there’s a real problem – which will, in turn, result in more problems. Guaranteed. Being able to openly dissent and engage in constructive conflict – and engage in collaborative problem solving – are critical elements of high-performing teams. Lack of psychological safety is not only a culture killer, but also is likely to amplify and multiply problems down the road.

Un-inclusive and illegal actions

Elon’s actions were not only un-inclusive, but also illegal. His initial firing of half of the company’s workforce violated regulations that require large companies to provide 60 days’ notice. Further, demanding that employees work intensely for long hours is discriminatory to disabled workers, workers with children or other caregiving responsibilities (most likely to be women), etc. 

While Elon Musk’s modus operandi may be to “move fast and break things,” he may very well break the whole company and the limited number of employees he has left. The silver lining here is that Elon Musk has given us multiple leadership lessons to examine and learn from – most notably on what not to do – and there will likely be more to come.

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Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

• Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
• Fifty four percent of raw case users came from outside the U.S..
• The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
• Twenty-six of the cases in the list are raw cases.
• A third of the cases feature a woman protagonist.
• Orders for Yale SOM case studies increased by almost 50% compared to 2020.
• The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

6 Twitter Marketing Case Studies To Inspire Your Brand

Last Updated: Jan 4th, 2023

Twitter is one of the most popular social media channels for marketing your business. And that’s for some good reasons:

• High Virality & Reach Potential
• The short-form content is relatively easy to create
• You can include links in the content

But how do YOU make the most of it?

In this article, we’ll look at six successful examples of Twitter marketing from companies such as Wendy’s, Sony PlayStation, McDonald’s, and more so you can replicate their success.

Through these case studies, you will gain insights into how each company used creative strategies to increase engagement on the platform and maximize its impact on users. So let’s get started!

You can go through the entire article or you’d jump directly to sections if you prefer.

• Using Humor to Connect with Customers
• Taking Advantage of Influencer Marketing
• Leveraging User-Generated Content
• Creating Custom Hashtags
• Fostering Brand Advocacy
• Aldi vs. Marks and Spencer’s

Twitter Marketing FAQs

Final thoughts, twitter marketing case studies.

Here are 6 Twitter marketing case studies to inspire your Twitter marketing strategy.

1. Wendy’s: Using Humor to Connect with Customers

Wendy’s Twitter Humor is basically the godfather of all funny brand social media campaigns.

Almost every single fast-food chain started doing it now. But Wendy’s is by far the most memorable and the funniest.

Their unique and often edgy jokes help engage followers, gain recognition and foster customer loyalty.

They use their platform to make people laugh while taking digs at their competitors like McDonald’s or Burger King.

In addition, their lighthearted approach to content can make a lasting impression on consumers, putting them at the forefront of the competition.

Here are just some of the funny tweets we found from Wendy’s:

2. Sony PlayStation: Taking Advantage of Influencer Marketing

To promote the launch of its new PS4 Slim console, Sony PlayStation turned to influencers for help.

By partnering with social media personalities and creating engaging content, they were able to reach a broader audience and increase engagement during the product launch.

This strategy was an effective way for the company to showcase the console and generate excitement around it.

Plus, as all the influencers created discussions around the launch, Twitter picked up terms like “PS4”, “PS4 sold out, and tons of others into the trending section.

This gave PlayStation a ton of more visibility as a promoted hashtag costs $200,000 per day, but Sony did it organically through influencers.

3. McDonald’s: Leveraging User-Generated Content

McDonald’s ran a campaign that encouraged customers to submit pictures of themselves at one of its restaurants in exchange for a chance to win free food.

By asking users to share actual photos of themselves enjoying McDonald’s meals, they were able to create an authentic connection between consumers and their brand, which ultimately drove more engagement and loyalty towards their products.

4. Coca-Cola: Creating Custom Hashtags

Coca-Cola developed custom hashtags like #ShareACoke and #TasteTheFeeling, which have been used worldwide by millions of people who enjoy their beverages or want to express support for the company through these designated terms.

The hashtags helped build recognizable brands that increased awareness among potential customers, making them more likely to pick Coca-Cola over other beverage options when shopping.

They also paired this with the names on the bottles, which made it even more likely for users to upload a pic to show off their name on the coke bottle.

5. Nike: Fostering Brand Advocacy

Nike has used Twitter to foster brand advocacy among its active customers by encouraging them to share stories about how they embody the “Just Do It” spirit through running or other physical activities.

This helps create an online community filled with loyal Nike fans eager to spread positive messages about the company on social media channels such as Twitter, helping boost its reputation further within this space.

It also creates a sense of community.

6. Aldi vs. Marks and Spencers

This case study is from the UK grocery store Aldi, but it’s pretty cool…

Backstory : Marks and Spencers (M&S) decided to sue Aldi because their caterpillar cake design was similar.

Aldi took it to social media to “troll” M & S, which led to the crazy engagement, and even influencers picking up the topic organically.

Oh, and the entire public was on Aldi’s side.

These posts reached millions across Facebook and Twitter and made the public feel more positively toward Aldi.

We’re not sure what the lawsuit’s outcome was, as the two stores reached a “Confidential agreement”, but from a PR perspective, Aldi clearly won.

Is Twitter still good for marketing?

Yes, Twitter is still a powerful platform for marketing. With its large user base and focus on real-time content sharing, it offers many opportunities for brands to connect with customers and build their presence in the digital landscape.

What makes Twitter unique for marketing?

One of the key benefits of Twitter for marketing is its real-time nature and the short attention spans that it caters to. This makes it an ideal platform for sharing news, promotions, and other time-sensitive content in a way that grabs the attention of users and drives engagement.

How has Twitter changed the marketing industry?

Here are three ways Twitter has changed the marketing industry:

• Twitter has made it easier for brands to go viral
• Twitter has made it easier for customers to reach brands
• Twitter has made it easy to have real-time discussions around trending topics

Why is Twitter good for advertising?

Advertising on Twitter is effective because the ad placements are easily visible, and the platform has excellent targeting tools. In addition, it can sometimes be cheaper than Facebook & Instagram ads because it’s slightly less popular.

Overall, Twitter is a powerful and unique platform for marketing that has changed the industry by making it easier for brands to go viral, connect with customers, and take advantage of real-time opportunities.

As we have seen throughout this article, brands can benefit from the following:

• Showing Humor on Twitter
• Leveraging UGC
• Working with Influencers
• Building Community
• Coming up with custom hashtags

We hope you have enjoyed this article on Twitter Marketing Case studies.

If you would like us to help you with your social media marketing strategy, book a free consultation with us here .

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• Original Article
• Open access
• Published: 08 December 2016

Twitter data analysis as contribution to strategic foresight-The case of the EU Research Project “Foresight and Modelling for European Health Policy and Regulations” (FRESHER)

• André Uhl   ORCID: orcid.org/0000-0002-1498-7112 1 ,
• Nina Kolleck 2 &
• Edgar Schiebel 3  

European Journal of Futures Research volume  5 , Article number:  1 ( 2017 ) Cite this article

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In this article the value of Twitter data analysis for a strategic foresight exercise is discussed. The article offers an overview of Twitter’s basic functionalities, previous Twitter research and related studies on using Twitter in foresight projects to date. Based on this knowledge the case of the EU research project “Foresight and Modelling for European Health Policy and Regulations“(FRESHER) is used to conduct a Twitter data analysis in three steps: an analysis of web-links to get insights into the content spread via Twitter, a social network analysis to define central actors in a Twitter debate, and a hashtag-analysis to find out which topics are discussed and to support the identification of drivers of noncommunicable diseases. The article shows the benefit a Twitter data analysis provides for the FRESHER project and reveals implications for future research in this field.

Introduction

Online social media platforms such as Twitter, Facebook or Youtube cover a big share of the world wide digital communication today. Different software tools allow the gathering of information about users and the collection of data about their communication behavior. Especially the microblog Twitter provides manifold opportunities in data analysis thanks to its functionality and the availability of appropriate software. Despite these opportunities and a wide range of studies about the use of Twitter for different disciplines, the analysis of Twitter data and its contextualization within the scope of Foresight projects is rarely discussed in scientific literature. Therefore the author of this article asks: Can a Twitter data analysis contribute valuable input to a strategic Foresight exercise?

In order to answer this question the case of the EU research project “Foresight and Modelling for European Health Policy and Regulations“is used, Footnote 1 which is part of the EU research and innovation program Horizon 2020. Footnote 2 An international consortium of ten European research institutes conducts this project by applying a cross-disciplinary approach. The objective of FRESHER is to explore alternative futures for the European health sector in order to test the efficiency of different options to tackle the burden of non-communicable diseases (NCDs). The study presented in this article examines whether Twitter data analysis can contribute valuable results to:

the gathering of relevant information around the theme,

the search for contacts and possible participants for workshops or interviews,

the identification of drivers with potential impact on the development of NCDs in the future.

The article is structured as follows: Subsequent to the introduction the main characteristics and functionalities of Twitter are described, an overview of previous Twitter research is provided and possible opportunities emerging with the use of Twitter for strategic Foresight are shown. Then the FRESHER research project is briefly described and possible points of action for a Twitter data analysis within this project are shown. Based on this the methodological approach of the study is explained, followed by the presentation of the findings. Finally, the results are discussed, a conclusion is drawn and possible implications for future work in this research area are revealed.

Development, characteristics and user

What is twitter.

Twitter was created in March 2006 under its original name “Twttr”. Since co-founder Jack Dorsey posted the first message (“just setting up my twttr”) Twitter has developed to the most used and known microblogging platform and one of the most popular online social networking services. At the beginning of 2010 the site had 20 million unique users and 50 million messages per day. By March 2015 these numbers had grown to 302 million unique users and 500 million messages, better known as tweets, were being sent. Footnote 3 Today, the platform can be regarded as a “… communication phenomenon whose reach is still growing and whose consequences are far from understood“[ 30 ].

Like other microblogs Twitter can be described by the following five key characteristics [ 12 ]: (1) a concept of shortness, due to the limitation of 140 characters for each post (hence the name micro blog), (2) a concept of friends (the various accounts a user follows) and followers (the accounts that follow a user), (3) a concept of information presentation, where messages of friends are presented in a list with the most recent at the top, (4) a concept of openness (users can set their profiles to private, but that is rather unusual; almost all posts on Twitter are public), and (5) a concept of web services, meaning that Twitter allows third-party applications to connect with the service using an open application programming interface (API). This open API “provides a mechanism to make use of the functionality of a set of modules without having access to the source code or a specific license“[ 2 ] and is therefore crucial in order to conduct a Twitter data analysis by any means. In view of these characteristics, a microblog, with Twitter being its most prominent representative, can be classed as a service for a complete new way of communication.

How does twitter work?

Besides the basic function of posting a Twitter message (called “tweet”), and the possibility to follow and be followed by other users, Twitter provides several other specific features. Three of these are “replies”, “mentions” and “retweets”. Replying to a user by starting a tweet with an @ sign followed by the user name ( @user ) makes it possible to address a user directly via the public Twitter feed. To mention another user, works in a similar way; it also includes @user but not at the beginning of a tweet. The difference is that a reply is directed to the other user and therefore seen by him or her, while a mention is not directed at the user. You could also say a reply is a message for someone while a mention is a message about someone [ 20 ]. By using the retweet function a user spreads the original message from another user by resending it. While mentioning is a way of referring to another user without necessarily sharing the same opinion, a retweet can be seen as an informal recommendation of a message that another user finds important, interesting or at least entertaining. Therefore the retweet function is a key mechanism for information diffusion and raising content visibility on Twitter [ 36 , 47 ].

Another key function of Twitter is the use of “hashtags”. Putting a “#” (hash) sign in front of a certain word is a simple way of adding context to a message. This can be a name (e.g. #obama ), an event (e.g. #election2016 ), a movement ( #refugeeswelcome ), a conference (e.g. #futuresconference2015 ) or anything else. By adding a hashtag to a Tweet, the referred word receives the informal function of a topic. Thus, hashtags are helpful when sharing news, knowledge or general contributions to a certain topic, and to spread information across networks of interest. Conversely, hashtags make it easy to search and collate information, discussions or central actors regarding a specific theme [ 10 , 37 ]. Also, hashtags can be especially useful when Twitter is used as a communication platform, for example during a conference to share ideas, impressions, comments and additional materials on a “#channel“[ 11 ].

While each tweet can be retweeted, be addressed to other users by replies, or relate to specific context by a hashtag, information spreading on Twitter can also work in other ways: Tweets can additionally contain photos, videos with a maximum length of six seconds or additional web links. The latter is particularly interesting for Foresight practitioners who want to use Twitter as a data source, since they might refer for example to news articles, studies, or reports relevant to the theme under investigation.

Who uses twitter and why?

With the growing popularity of Twitter, not only has the “daily chatter”, as Java et al. [ 28 ] describe it, increased but also the service’s potential as a fast information distribution platform, as a tool for coordination in disaster control/response, or as an instrument for political campaigns [ 30 ]. By the time Twitter reacted to the predominant way people used the platform and changed its initial question in 2010 from “What are you doing?” to “What’s happening?” focusing on ongoing news and events. Other changes Twitter made in reaction to the user behavior are even more remarkable: Both retweets and hashtags were first initiated by users without having a formal function to use it; this was a matter of self-initiative in order to spread information or add context to a message. Twitter later implemented these features formally, which are now two of the services’ most important functions [ 22 ].

A study from Smith and Brenner [ 42 ] gives some hints on what a “typical Twitter user” in the United States might look like. Although the results might be different considering a European sample it seems plausible to assume at least a similar demographic tendency. According to the results of the study most of the Twitter users are younger, with a higher education, more affluent showing a bigger political interest than the average. It is therefore important to note that a Twitter data analysis cannot be seen as a representative sample of a population. Such data can only provide insights in the online communication of the part of the population using this specific online service. This does not necessarily make such data less important or less interesting for social scientists or Foresight practitioners. In fact, focusing on a group that shows a relatively high level of involvement and interest in societal issues [ 29 ] might be fruitful depending on the specific topic of research.

Twitter research

Since Java et al. [ 24 ] published their paper “Why we twitter: understanding microblogging usage and communities“, one of the first studies on Twitter finished in the same year the service was launched, a growing number of studies on Twitter research has been published. According to a bibliometric analysis from Kayser and Bierwisch [ 31 ] examining the different research areas from the year 2006 until 2014 (articles and proceeding papers), the fields “Computer Science” and “Engineering” show the highest activity in Twitter research while other disciplines like “Business and Economics”, “Communication”, “Education”, “Psychology” and “Social Sciences” also show a noteworthy number of contributions. However, the boundaries of the different research areas are not always as clear since some of the studies follow an interdisciplinary approach, while others use case studies from a certain discipline to make a point. Some studies from different disciplines that received attention in the scientific community shall be mentioned in the following.

From the beginning of Twitter research a significant number of studies examined the use of Twitter in a political context. While some try to grasp the role of the microblog in political protest movements [ 30 , 38 ], others try to yield insights into political opinions via semantic structures in Tweets [ 41 ], by sentiment analysis [ 21 ] or through a mixed-method approach of social network analysis and keyword analysis [ 23 ]. However, expectations that Twitter might work as a tool to predict electoral results could not be fulfilled since Twitter users are neither a representative sample of the population [ 40 ] nor do tweets necessarily reflect real life electoral behavior [ 26 ].

Jungherr and Jürgens [ 25 ] also discuss the potential of forecasts based on Twitter data. Instead of aiming to predict events by identifying typical data patterns they suggest to model the “normal state” of a system. Differences between this model and empirical data should then work as an indicator for the occurrence of extraordinary events. Other studies cover geographic aspects of Twitter use [ 14 ], examine the influence of distance, national boundaries or language on Twitter’s social ties [ 45 ], or focus on the use of Twitter as a tool for educational purposes [ 18 , 19 ] and as communication tool at scientific conferences [ 10 , 11 , 13 , 37 ].

Some follow a rather broad approach, analyzing how communication flow on Twitter works in general. Unsurprisingly, such studies were often conducted in the field of “Computer Science”. Castillo et al. for example focus in their studies on the analysis of newsworthy information [ 6 ] and later on information credibility [ 7 ] on Twitter to establish an automatic discovery process of relevant and credible news. Weitzel et al. [ 47 ] have a similar goal utilizing social network analysis to assess reputation from source information in the medical domain. They tested a method to rank trustworthy sources on the basis of a retweet network and concluded, that in the Twitter community trust plays an important role in spreading information. Li et al. [ 29 ] also reveal the efficiency of information diffusion on Twitter and the specific user behavior leading to such information diffusion.

Unlike numerous attempts at using Twitter for forecasting or the “prediction” of the future (e.g. electoral results, product sales or stock markets developments), which have been controversially discussed [ 15 , 30 , 40 ], there have only been few attempts to examine the use of Twitter in the field of Foresight and futures research. In the following the author takes a closer look at some related studies on Twitter and Foresight. Thereafter it is tried to identify opportunities where Twitter may be used as an instrument for strategic and participative Foresight.

Twitter and foresight

The number of studies investigating the use of Twitter for Foresight is still limited and only a handful of papers describe efforts to apply the online platform for different purposes so far. For example Pang [ 34 ] presents an approach he calls “social scanning” whereby he aggregates online content from futurists and Foresight practitioners. This process of gathering and filtering content from Twitter and other social media platforms shall help to identify trends and “weak signals” for possible future developments. One could criticize the approach for drawing exclusively on content from futurists, which might already be shaped by pre-assumptions these persons have about the future.

Amanatidou et al. [ 1 ] implement Twitter into a horizon scanning framework for the European project “Scanning for Emerging Science and Technology Issues” (SESTI). While the authors use the platform mainly for collecting web-links they also emphasize Twitter’s potential for detecting “weak signals” as well as the opportunity to use the microblog as communication instrument during a Foresight process. However, the comprehensive horizon scanning framework was the focal point of the study. Twitter was one information source amongst many and in this regard used as an additional element to complement the framework. Schatzmann et al. [ 39 ] give an overview of methods in a field they define as “Foresight 2.0”. They discuss the aptitude of Twitter and other web 2.0 applications for foresight exercises and outline a possible evaluation process of digital applications by their intended use, knowledge generation and quality of results.

Raford [ 35 ] explores the role online services like Twitter could play in scenario planning. He thus compares five empirical case studies. Like Amanatidou et al. Raford emphasizes both the potential Twitter holds for a horizon scanning process and the opportunities it could offer in communication and in promoting a public dialog. He points out that research communities exploring online data are still largely separated from scenario planning and public engagement, and argues for the potential value of real-time online systems and the interaction with other instruments in a scenario process.

One of the first studies focusing exclusively on the use of Twitter in Foresight comes from Kayser and Bierwisch [ 31 ], asking how the online service can be used as an integral part in technology foresight. The authors examine the potential of Twitter as a tool for monitoring an ongoing debate on the “quantified self” phenomena, but also tests Twitter’s aptitude as a tool for engagement in a foresight exercise. Some of the main assets of Twitter emphasized by the authors are the broad variety of content delivery, the fast access to a large number of people and the possibility to receive real-time feedback on ideas. They suggest working with a mixed methods approach instead of using Twitter as the only data source for a Foresight project.

The study in this article builds on the attempts and insights described in the previous studies. Likewise, the author sees great potential of Twitter as an additional instrument in different phases of strategic Foresight exercises. There are several perspectives in the literature of how many phases of Foresight should be classified and how to differentiate these phases [ 3 , 8 , 22 ]. The author of this article distinguishes four main phases of a strategic Foresight [ 16 ]: (1) Gathering and analysis of information and data, including desk research and horizon scanning, (2) generating knowledge through a participative process, usually in the form of alternative future scenarios, (3) formulating options and handing over of policy recommendations, and (4) implementation, communication and dissemination of results. The previous studies and the way Twitter works as an online communication service speak for Twitter as a useful instrument at all phases: As a tool for data analysis and information scanning at the beginning of a Foresight, as communication tool during the phase of knowledge generation, and at the end for result dissemination. Furthermore it could serve as a tool for continuous monitoring on a topic over the whole Foresight process (see Fig.  1 ).

Phases of Foresight and potential use of Twitter, source: adapted from Giesecke & Uhl, 2015

In this article the author concentrates on the beginning of a Foresight project. In almost every case such a project starts with desk research and the gathering of information in order to capture the status quo of a topic. Other important tasks are the identification of potential stakeholders, the search for participants of workshops or interviews, or the identification of key determinants and drivers affecting the research topic fundamentally. Foresight practitioners are usually confronted with an information gap on the topic under debate. Thus it is necessary to apply varying methods to fill this gap as good as possible. It is assumed that a Twitter data analysis based on a certain hashtag can aid work on this task and broaden the information base at the beginning of a Foresight project. In order to test our assumption the case study of the EU research project “Foresight and Modelling for European Health Policy and Regulation” (FRESHER) is used, which is described in the following chapter.

Foresight and modelling for European Health Policy and Regulations (FRESHER)

Structure, objectives and approach.

Today non-communicable diseases (NCDs) such as heart disease, stroke, cancer, diabetes, depression, and others are the leading cause of mortality in Europe. Footnote 4 Common risk factors of the major NCDs include tobacco, harmful use of alcohol, unhealthy diet, insufficient physical activity, obesity, raised blood pressure, raised blood sugar and raised cholesterol. While the number of people afflicted by NCDs is increasing and the burden is growing, the WHO underlines that a great part of the NCDs threat can be overcome by using existing knowledge, and possible solutions are highly cost-effective.

The research project “Foresight and Modelling for European Health Policy and Regulations” (FRESHER) Footnote 5 draws on this knowledge to support the search for appropriate solutions. A consortium of ten international European research institutes and partners from eight different countries conduct FRESHER. It runs over a time period of three years from the beginning of 2015 until the end of 2017. The project is part of the EU research framework program Horizon 2020 and financed by the European Union Funding for Research & Innovation. According to the FRESHER Funding Frame (unpublished proposal) the overall project objective is to outline alternative futures using emerging health scenarios to test future policies to effectively tackle the burden of NCDs. Intermediary goals of the project are:

To produce quantitative estimates of the future burden (horizon 2030 and 2050) of NCDs in the EU and its impact on health care expenditures and delivery, population well-being, health and socio-economic inequalities.

To base such estimates on Foresight techniques giving credit to the interdependencies of structural long-term trends in gender relations, demographic, technological, economic, environmental, and societal factors (horizon 2050).

To illustrate options for decision-makers in order to contain the burden of NCDs.

To promote an interactive process with key actors in public health and European policies.

Following these goals the FRESHER project shall contribute to a better understanding of causal chains and risk factors of NCDs. This shall provide decision-makers with “timely, accurate information to consolidate the scientific knowledge on the effectiveness of policy interventions.” Footnote 6 The project will also form an active network for effective policy dialogue with major stakeholders of public health policies in Europe and give recommendations on research priorities to reduce the impact of NCDs in Europe.

Horizon scanning and twitter data analysis

Two core elements of the FRESHER Foresight process are the implementation of a horizon scanning process and the development of future health scenarios built on the results of the horizon scanning. Horizon scanning can be described as a practice integrated in the first phase of Foresight exploring trends, drivers, and challenges but also past experiences to identify topics and factors that might influence the theme under investigation in the future [ 32 ]. Delaney gives an overview of existing definitions of horizon scanning, and most of them closely resemble the goal-oriented description above [ 9 ].

Apart from this rather broad explanation of what a horizon scanning should lead to, there is no common understanding in foresight literature of how to process horizon scanning in detail, which methods should be used or which steps to be included in such a process. Some scholars underline the opportunities of automated or semi-automated horizon scanning processes, while using different software-supported and often self-developed infrastructure to process information [ 17 , 33 , 44 ]. Amanatidou et al. [ 1 ] describe their experiences from the European horizon scanning project “Scanning for Emerging Science and Technology Issues” (SESTI) which uses different scanning approaches and scanning tools to improve policy formulation and dialogue. Also, a number of governments operate national horizon scanning centres and have developed their own framework processing information from numerous sources in order to prepare for future challenges. Footnote 7

In the FRESHER project the term horizon scanning is used in a comparatively broad way, meaning a general scanning of different sources like scientific literature, conferences, Foresight projects, online sources etc. without drawing on an existing horizon scanning framework. One key mechanism to identify determinants, trends and drivers in the context of NCDs is a semi-automated bibliometric analysis of scientific literature. Another important element is the discussion of the results with an expert committee and in further expert interviews. These interviews shall also help to explore which policies could address future challenges on NCDs.

The approach sets out from a holistic understanding of the health and well-being sector. Social factors such as family and networks influence health and well-being just as well as economic factors such as the standard of living, environmental factors such as pollution and climate change, and also the safe and secure surrounding in which a person lives. Therefore the horizon scanning looks also at the external factors that lie outside a narrow definition of the health system. The results of the scanning process lay basis for of the scenario building later on.

The aim of this study is to examine whether a particular hashtag on Twitter might serve as a valuable search tool to find relevant information on the topic of NCDs, to identify experts in the field of NCDs, and as an instrument to complement the identification of determinants and drivers for NCDs. Therefore the following three research questions are formulated:

RQ1: Do messages with the hashtag #ncds contain thematically relevant web-links? RQ2: Can central actors of a Twitter network around the hashtag #ncds be regarded as useful contacts for the foresight project? RQ3: Do Tweets with the hashtag #ncds contain other hashtags representing determinants and drivers of non-communicable diseases?

In the following the methodological approach is described, the findings are presented and discussed, and possible indications for more research in the future are shown.

Methodological approach

Every time users interact with online services they leave data traces, documenting their online behavior. While most of these traces are invisible to researchers, Twitter offers access to comprehensive data sets through its open application programming interface [ 25 ]. Beside the actual Twitter message much other information is available, e.g. the number of followers of a user, the number of his or her “friends”, or the profile description. Furthermore a set of metadata is accessible such as geographical data (in case the Twitter user specifies his or her geographical location), the exact time a tweet was sent or the user ID. All in all, Twitter offers a publicly available, comprehensive and in large parts spatially embedded network dataset, which can be of great value for researchers [ 45 ].

Not so long ago the aggregation, analysis and illustration of data from social media platforms such as Twitter demanded significant programming and advanced data management skills [ 20 ]. Today different software applications deliver pre-structured data sets by connecting to the Twitter application programming interface. This enables researchers to concentrate mainly on measurement, analysis and interpretation of data, instead of spending time with coding or mastering an appropriate research tool. For this study the program NodeXL was used. The software runs on Windows operating system and is an add-on for the program Microsoft Excel, where it is virtually integrated as an additional tab while all other Excel functions can still be used for the dataset.

By using the import function for Twitter data NodeXL provides search results as structured network information in different spreadsheets. The “Edges” spreadsheet (relationships between Twitter users are represented as network edges) includes information on messages sent within this network, while the “Vertices” spreadsheet (Twitter users are represented as network vertices) includes information on each user within this network. The search is limited to a maximum amount of 18.000 tweets and also to a time period seven days back from the present. If more data is required a regular search has to be done over a longer time period.

For the study a Twitter network is examined, consisting of all users who include the hashtag #ncds in their Tweets or who are mentioned in such a Tweet from July 5th to September 7th, 2015. Tweets containing the hashtag #ncds are imported every week within this time period. The decision to focus the search on a hashtag instead of a keyword was made because of the specific function of hashtags as described earlier in chapter 2.1. Concentrating on a hashtag makes it easier to capture messages on a specific theme. When a user decides to include a hashtag in his/her tweet he/she adds context to the message and in this regard contributes consciously to a public (Twitter) dialogue on a certain theme. The author’s goal was to aggregate tweets and information about users who deliberately take part at a public dialogue by using a certain hashtag.

Defining the most appropriate hashtag for the search required a pre-analysis of tweets. As Bruns and Stieglitz [ 5 ] point out “hashtag research depends crucially on the existence of a widely adopted hashtag, and on its (early) detection and tracking by researchers”. This is especially true for a thematic field like “non-communicable diseases” where different terms or abbreviations, and therefore alternative hashtags, might be used unlike for example in the case of #smartgrid where the choice of the hashtag term is obvious. To make sure it was searched for the most common hashtag used in the Twitter debate on non-communicable diseases, tweets containing different hashtags ( #ncd , #ncds , #noncommunicable , #noncommunicablediseases ) were imported over a time period of two months. Based on the number of tweets and a spot check of the content #ncds was identified as the most common hashtag in this context; thus it was decided to focus on this search term.

In every Twitter data analysis the question of how to deal with retweets must be answered. There can be different ways how to interpret retweets depending on the research question and the goal of investigation [ 26 , 27 ]. In this study the author wants to examine which web-links are shared the most, which users get the most attention and which hashtags are dominant in the Twitter debate of NCDs. Retweets are interpreted as contributing elements to this debate with the same importance as “original” tweets. Therefore it was decided to give all messages in the network the same attention, no matter if they are “original” tweets or retweets.

The study in three steps

The study is divided into three major steps:

In the first step web-links included in the tweets of the dataset are examined. The total number of web-links is counted and the ten most shared links in the network are checked more precisely regarding the included information. These web-links are then categorized in terms of the character of the included information, for example news, reports, scientific studies, or advertisement/public relation. This allows an assessment whether the shared links can be seen as a valuable contribution to the Foresight exercise or not, and whether these links help to broaden the information base or not. On this basis RQ1 is answered: Do messages with the hashtag #ncds contain thematically relevant web-links? Furthermore the examination of web-links provides a first overview of the topics dominating the debate on NCDs on Twitter within this time period.

In the second step of our study a social network analysis of Twitter users in the dataset is conducted. This builds the basis for answering RQ2: Can central actors of a Twitter network around the hashtag #ncds be regarded as useful contacts for the Foresight project? The Vertices represent all Twitter users within this network. This implies users who include the hashtag #ncds in their tweet as well as users who are mentioned in a Tweet which includes #ncds. Edges represent relationships of Twitter users within this network. The Twitter API provides three types of relationships/messages: (1) „Tweets“, meaning a user has tweeted without mentioning another user, represented by a self-loop. (2) “Replies to”, meaning a user replies to another user by mentioning him or her at the beginning of the tweet. (3) “Mentions”, meaning a user mentions another user within the tweet. “Mentions” also include retweets, as NodeXL classifies retweets as a certain form of mentions.

In this approach such Twitter users are defined as central users, who receive the most attention within the network. The level of attention is measured in two ways: the number of followers a users has in general (indirect attention) and the number of mentions (including retweets) and replies a user has in the network (direct attention) represented by the in-degree, meaning the number of edges going to a vertex in a directed graph [ 46 ]. Based on the network analysis a list of users with the highest number of followers is compiled, and another list of users with the highest in-degree, both represented through a network graph. These Twitter users are then checked for further information through their Twitter profile description and a manual Google search. The results of the network analysis allow to make an assessment about users dominating the discussion on Twitter and also who should be considered for interviews, workshops or as a general contact for the FRESHER project.

In the third and final step of the study the hashtags included in tweets from the network are analyzed. This aims to answer RQ3: Do Tweets with the hashtag #ncds contain other hashtags representing determinants and drivers of non-communicable diseases? In order to answer this question the hashtags are compared to a list of determinants and drivers of NCDs, identified on the basis of the bibliometric analysis of scientific articles that was conducted within the horizon scanning process of the FRESHER project, and based on the feedback of the expert committee. Furthermore it is examined which hashtags are most frequently mentioned. In addition to the examination of the web-links this helps answer the overall question of which topics dominate the Twitter debate on NCDs within the defined time period.

For this study data were imported from the Twitter search network with the search term #ncds every week from July 11 th , 2015 over a time period of eight weeks to September 7 th , 2015. The received dataset contains Twitter data from July 4th, 2015, 04:51 pm, to September 7th, 2015, 09:03 am, with a total number of 3.656 Twitter messages. 5.088 edges represent the total number of relationships in the network: „Tweets“(759 edges), “Replies to” (50 edges), and “Mentions” (4.278 edges). As described previously, “Mentions” include retweets which are by far the most often form of messages/relationships in the dataset (3.502 edges). In the following the term “edges” is used when describing all three types of relationships in the dataset.

Step 1: analysis of web-links

The dataset contains 820 different web-links that are spread via 3.694 edges within the network. Table 1 shows the website headers of the ten web-links with the highest counts. The most shared link leads to the website of the CDC Centers for Disease Control and Prevention (the American health protection agency), more precisely to the web page featuring the current CDC newsletter. The second most shared link leads directly to this newsletter in PDF format, followed by a web-link that leads to a news article on Barbados Today about a new tax on sugary drinks. This tax was introduced in Barbados on August 1 st to reach lower sugar consumption, a political instrument that was discussed in other countries, too. The 4 th link leads to the website of a company offering services to support health professionals and patients with exercises and the management on NCDs. The 5 th web-link leads to a BBC news article also contributing to the discussion on tax on sweet drinks, while the 6 th leads to a report of the British Medical Association on promoting healthy diets among children and young people, released in July 2015. The 7 th leads to a scientific article in PLOS Medicine Journal on the global spread and disparity of NCDs, the 8 th to an article about challenges in the tackling of NCDs on the website of the Clinton Foundation, and the 9 th to an article about financing the fight against NCDs on the website of DEVEX, a media platform for global development. The last of the ten web-links leads to Innovation Countdown 2030, an initiative to identify, evaluate, and showcase technologies and interventions to transform global health by 2030. The initiative is supported by the Norwegian Agency for Development Cooperation, the Bill & Melinda Gates Foundation, and the US Agency for International Development.

Three of these top ten links can be classified as reports of governmental initiatives (1, 2 and 6), three are reports or articles of non-governmental organizations and private initiatives (8, 9, 10), two articles from genuine news websites (3, 5), one article from a scientific journal (7) and another one leads to a commercial website (4). Most of them contain more links to further information such as news around NCDs (5, 6, 9), scientific articles or studies (1, 2, 6, 7, 8) or contacts to professionals in different fields of NCDs (1, 2, 4, 6, 7, 10). In fact, the web-link leading to the report of the initiative Innovation Countdown 2030 provides a collection of information with a close connection to the overall goal of the FRESHER project: the identifications of technologies and interventions that can be seen as possible drivers to shape global health by 2030. In summary, and as an answer to RQ1 , it can be said that the top ten web-links contain up-to-date information on the thematic complex of NCDs and contribute valuable insights to the scanning process of the FRESHER project.

Step 2: identification of central actors

In a second step central actors within the network are identified. As already mentioned the network consists of Twitter users sending messages with the hashtag #ncds or being mentioned in such a message. Table 2 shows the top ten users in the network with highest number of followers. The list is clearly dominated by leading news websites and news agencies such as The New York Times (1), Reuters (3), Forbes (4), Mashable (5) and Washington Post (6). Other user profiles in the list belong to the Prime Minister of India Narendra Modi (2), the President of the United States Barack Obama (9), the United Nations (7), United Nations International Children’s Emergency Fund (8), and the World Economic Forum (10). The list also shows that three of these user profiles are located in the United States, while four of them represent international organizations or media companies with headquarters in the USA. The remaining three belong to Narendra Modi in India, Reuters with headquarter in UK and the World Economic Forum with headquarter in Switzerland.

All followers of a user receive his or her tweets on their Twitter wall. If for example @nytimes tweets (or retweets) a message including the hashtag #ncds nearly 19 million users are potentially reading that message. Therefore the number of followers can be seen as a way to measure the level of attention a user gets on Twitter. However, measuring the level of attention in this way leaves an important question open: Do the followers of this user really read this message or does it get lost in the vast information flow one user is confronted with when following a large number of accounts? Therefore the number of followers of a user must be regarded as a rather indirect or hypothetical level of attention.

Another way to measure the attention users receive on Twitter is to count their in-degree number within the network. The in-degree is defined by all edges in a directed graph going to a vertex (user), which can be tweets (in the form of one self-loop, no matter how many messages a user sends), mentions (mostly in the form of retweets) or replies to another user. Being mentioned in a tweet, being retweeted, or getting a reply requires active involvement of another user. If, for example, a message from @ncdalliance is being retweeted from several other users, it can be assumed that all these users have read this message and regarded it as worth to be spread. Thus, while the number of followers can be seen as a measure of indirect attention , the in-degree number can be seen as a measure for direct attention supported by action.

Table 3 shows the ten users with the highest in-degree number in the network. Top on the list is the account of NCD Alliance, a network of over 2.000 non-governmental organizations, followed by the account of the NCD Asia Pacific Alliance with headquarters in Japan, and the account of the World Health Organization on number 3. The other user accounts belong to NCDFREE, an international network of young professionals against NCDs, the British charity C3 Collaborating for Health, Douglas Webb (who is a health and development expert at United Nations Development Programme), CDC Centers for Disease Control and Prevention (the American health protection agency), Anant Bhan, Professor for bioethics and global health at Yenepoya University in Pune, India, Prevention 1 st (a campaign by the Foundation for Alcohol Research and Education and the Public Health Association of Australia), and the Framework Convention Alliance for Tobacco Control. Regarding the origin of the user profiles the list shows that five of them belong to international organizations, two profiles belong to users in the United States, and one belongs to the UK, India and Australia each.

Figure 2 shows a graph including all vertices in the network. The size of the vertices is proportional to the number of followers; the top ten users with the highest number of followers have name labels. By contrast, Fig.  3 shows the same graph including the network edges. Here the vertices with the highest in-degree number (user from Fig. 5) are presented in dark blue and have name labels. For a better overview all self-loop-edges are excluded. It is clear to see that all of the highlighted vertices in the second graph show a high number of edges.

Network actors highlighted by number of followers. (Graph showing all vertices in the network of #ncds. Size and opacity of the vertices is proportional to the number of followers on Twitter. Top ten users with highest number of followers have name labels.) Source: Author’s data

Network actors highlighted by in-degree number. (Graph showing all vertices and edges in the network of #ncds. Size of the vertices is proportional to the number of followers on Twitter. Top ten users with highest in-degree number have name labels.) Source: Author’s data

Comparing both approaches, highlights that the second approach is more favorable in order to identify important actors in the network. While most of the user accounts with the highest number of followers come from mass media news sites or some of the world’s leading international organizations, user profiles with the highest in-degree number mainly come from non-governmental organizations, governmental agencies or activist groups that specialize in the field of NCDs. With regard to RQ2 it can be stated that it is to a certain extent useful to consider some of the central actors as experts for interviews or as general contacts for the FRESHER project. Since the FRESHER workshops focus on participants from continental Europe, the aptitude of these users as participants for the workshops is rather limited.

Step 3: hashtag analysis

In a third and final step of the study a closer look is taken at the hashtags included in the Twitter messages of the dataset. Besides the key hashtag #ncds the dataset contains 713 other different hashtags. 1.391 edges contain only #ncds while the remaining 3.698 edges also contain one or more other hashtags. Table 4 shows the top ten hashtags in the dataset. Most frequent beside #ncds are #diabetes, #publichealth, #globalhealth, #ffd3, #obesity, #sdgs, #health, #tobacco , and #cancer . While the meaning of most of these terms is obvious, two of the hashtags are abbreviations (number 5 and 7) standing for the Third International Conference on Financing for Development ( #ffd3 ), which was held from 13th until 16th of July in Addis Ababa, Ethiopia, and the Sustainable Development Goals 2030 ( #sdgs ), formulated by the United Nations in 2015 to replace the Millennium Goals from the year 2000.

The word cloud in Fig.  4 displays all hashtags appearing 15 times or more in the tweets of the dataset. The key hashtag #ncds was excluded for a better overview. Color and size vary in proportion to the frequency of the hashtag terms, from bigger and dark blue for the most frequent hashtags to smaller and light blue to the less frequent ones. The highest occurring hashtags from table 4 can be clearly be identified in the word could. Other frequently appearing hashtags are for example #india, #sugar, #prevention, #physicalactivity, or #mentalhealth . Most frequently mentioned types of NCDs in the form hashtags are diabetes, obesity, and cancer. The word cloud illustrates very well the dominating topics in the Twitter debate on NCDs during the observed time period.

Word cloud displaying hashtag terms included at least 15 times in a message with #ncds. (Color and size vary in proportion to the frequency.) Source: Author’s data

Table 5 shows different types/groups of NCDs plus corresponding determinants and drivers that have been identified previously in the FRESHER project on the basis of the bibliometric analysis and expert feedback. All terms showing an exact correspondence to hashtags in the dataset are marked green. All terms containing parts of hashtag terms or having a clear relation to some of the hashtags without showing an exact correspondence (e.g. “access to medication” and #accesstomedicines , “lack of physical activity” and #physicalactivity , or “wellness movement” and #wellbeing ) are marked yellow. Nine NCDs show exact correspondence with hashtags, as well as nine terms defined as determinants and six terms defined as drivers of NCDs. With regard to RQ3 it can be said that tweets with the hashtag #ncds contain other hashtags representing some of the determinants and drivers of NCDs although by no means all of the defined determinants and drivers are included in the list of hashtags.

Discussion and conclusion

The results of the study show the value of a hashtag-based Twitter data analysis for a strategic Foresight exercise at various levels. The most frequently sent web-links in the dataset lead to current and relevant information about topics closely connected to the development of NCDs. This includes actual reports of governmental, non-governmental, and non-profit organizations, recently published scientific articles as well as news and media articles. In this case Twitter can be regarded as a useful tool for gathering current information at the beginning of a Foresight project to complement the scanning process, and also continuously during the ongoing Foresight exercise to support the monitoring process. While concentrating on the most frequently spread web-links is a good starting point to ascertain current debates on Twitter, it can also be of interest to take a closer look at the other web-links in the dataset. Another way to filter relevant web-links could be an automatic search for previous defined keywords within the remaining links.

Furthermore our study displays the aptitude of a social network analysis around the hashtag #ncds to identify organizations and actors who play a central role in the public Twitter debate on NCDs and in the information distribution on Twitter. Getting an overview of these actors is helpful when collecting contacts or searching for potential interview partners and workshop participants for the Foresight exercise. Besides conducting bibliometric analysis or scanning conferences, a social network analysis can help to complement the expert list with qualified contacts not only from the scientific community, but also from civil society. As a further step it could be helpful to analyze the egocentric networks around selected actors to get insights into their network ties, to observe the attention flow going from and to these actors, and to find out which other actors are closely connected.

The examination of the differing hashtags in the dataset gives an overview of the current debate on NCDs on Twitter, precisely about the other topics that have been discussed while using the hashtag #ncds . This includes for example the most frequently discussed types of NCDs on Twitter: diabetes, obesity and cancer. The study also shows that some of the hashtags correspond exactly with some of the determinants and drivers, which are defined at the beginning of the FRESHER project, while some others show an obvious relation to these determinants and drivers. What can we conclude from this observation?

Showing exact correspondence with hashtags in the Twitter data analysis does not prove these factors to be true or more evident than others. It rather reveals that the public debate on Twitter shows in parts similarities to the ongoing debate in the scientific community, observed through the bibliometric analysis and the expert interviews. And it leads to another consideration: Perhaps a closer look should also be taken at the hashtags used in the investigated Twitter network, which do not show correspondence with the defined determinants and drivers. In doing so we leave the beaten track and search for new traces, which is often helpful when working on future scenarios.

Another argument in favor of a Twitter data analysis to complement the scanning process of a Foresight exercise is the relatively short amount of time in which such an analysis can be done. While the analysis demands good preparation to meet the purpose of each specific Foresight (e.g. adjust the focus of the data analysis, defining the appropriate hashtags etc.), the analysis itself can be done within a couple of days, or, depending on the goals of the analysis, even hours, due to its semi-automated nature. This enables Foresight practitioners to get valuable insights into a public debate while keeping the additional input of resources on a small level.

A limitation of the study is the time frame of two months as a basis for data retrieval. All statements and assumptions regarding shared content, network actors, or hashtags only apply to the time from July 5 th to September 7 th . Longer time periods or another time frame might have led to different results. It is therefore obvious that this Twitter data analysis can complement but not substitute the bibliometric analysis of scientific articles, which in contrast examines a debate in a scientific community over a relatively long time period. Also, the limited time frame makes it impossible to make assumptions about topical trends emerging in the public Twitter debate. In order to talk about trends, or at least trending topics, it is essential to capture longitudinal data, making it possible to observe for example the rising frequency of specific hashtags or hashtag combinations over time.

It should also be noted that there are certain limitations associated with hashtag-based approaches, which have already been discussed in the literature. These critics usually emphasize the concern that a concentration on hashtags might exclude a good amount of other Twitter messages on the same topic. Bruns and Burgess [ 4 ] for example hint at the self-selecting mechanism of hashtags and believe that hashtag-based analyses “cover only the tip of a communicative iceberg” while other users respond to hashtagged tweets without including this hashtag in their replies. They also point out that hashtag research crucially depends on the existence of a widely adopted hashtag term. Thus, there is always a remaining uncertainty that tracked data based on a selected hashtag missed out on alternatives contributing to the same discussion [ 5 ], a fact also Jungherr adds for consideration [ 25 ].

Both critics are justified to a certain extent. Concentrating on a specific hashtag to capture a public Twitter debate will probably always exclude some messages contributing to the same topic without using this hashtag. Still, the hashtag-based approach is an easy and effective way to capture at least a good part of the debate – and, what is even more important, to capture that part of the discussion which is consciously contributed by knowing and using a specific hashtag. Especially in the case of identifying central actors in the debate, this part is obviously the most interesting. Regarding the other critical point, the author tried to reduce the risk of potentially selecting the wrong hashtag or ignoring important alternatives by conducting a pre-analysis described in chapter 4.1.

The question, of whether Twitter data is representative of a population, was answered before and can be answered again with a simple “no”. This is the reason that previous attempts such as election prognosis were doomed to fail. Twitter users are likely to be a bit younger, higher educated, more political and societal interested, and more active in terms of communication. As already stated, a demographic shift from the average is not necessarily a problem as representative data is not essential in order to capture a public debate and to identify central actors within this debate. But the question for representative data leads to another one, which has to be discussed: Is Twitter data generally biased by PR professionals, spin-doctors or lobbyists?

In fact, this question is a bit more difficult to answer – and it is probably best answered with “yes” and “no”. Yes, communication on Twitter is shaped by different users sometimes on behalf of political actors, companies, or organizations trying to push forward their messages, products or opinions. Previous studies reported the potential misuse of Twitter for spam and message attacks from political communities or companies by using automated scripts or other tactics [ 28 , 32 ]. Must Twitter data therefore generally be seen as biased? No, the value of Twitter data depends largely on the research question to be answered. In this study it was tried to find out who dominates the debate surrounding NCDs on Twitter (in terms of receiving attention from other users), which subtopics are discussed and what kind of information is spread most frequently. This can be examined regardless of motivations driving the discussion.

Foresight practitioners must always be aware of (open or hidden) agendas potentially connected to information sources at different steps of a Foresight. The personal motivations of interview partners, participants of workshops – or information distributers on Twitter for that matter – should be questioned and taken into account, whether they are politicians, scientists, or representatives from corporations, non-profit organizations or civil society. Nevertheless, one of the main goals of any strategic Foresight is to broaden the perspectives on possible future developments by implementing different views, opinions and information sources into different phases of a Foresight exercise. In this regard Twitter can and must be seen as a valuable contribution to this process.

This does not mean that other methods like surveys, bibliometric analysis or interviews should be disregarded. Twitter data analysis should rather be seen as one component in the interaction of different methods in order to get a wider spectrum and to sharpen the view of the topic under debate. In this regard, the author shares the opinion of Lazer et al. [ 28 ] when they consider that “instead of focusing on a ‘big data revolution’, perhaps it is time we were focused on an ‘all data revolution’, where we recognize that the critical change in the world has been innovative analytics, using data from all traditional and new sources, and providing a deeper, clearer understanding of our world“.

Thus, research in the future might focus on the integration of Twitter data analysis into a systematic and expedient multi-method approach for Foresight exercises. Another goal could be the development of a comprehensive framework for the use of Twitter in foresight in general – not only as a basis for data analysis at the beginning of a Foresight exercise, but also as a tool for communication during the whole Foresight process, a point which could not be further considered in this study. Twitter provides the opportunity to receive real-time feedback on ideas, to involve potentially large number of participants in a scenario process, and to disseminate the results of a Foresight, building for example on a previous network analysis. A comprehensive framework would enable a systematic and interactive use of Twitter in the different phases of strategic Foresight.

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This article has been written with grants from the Austrian Institute of Technology (AIT) in Vienna. The research project „Foresight and Modelling for European Health Policy and Regulations“(FRESHER) is part of the EU research and innovation program Horizon 2020.

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