What really went wrong at Quibi

Back in April, I wrote that Quibi had already lost and was not competitive and last week this “prediction” was confirmed by the announcement that it was closing down. Quibi, which raised nearly $2 billion in investment, was doomed from the start.

While I would love to dedicate a blog post congratulating my predictive capability, the lessons from Quibi are that there are clear drivers to success in the entertainment space. Rather than focus on the Monday morning quarterbacks (including the Quibi executives) who hypothesize why it failed (if they are so all knowing, why let it happen in the first place), let’s understand what drives successful entertainment (particularly games and streaming).

Not being feature driven

The first lesson is that a cool technology is not critical to consumers of entertainment. Quibi raised almost $2 billion by convincing investors that its unique technology would separate it from other streaming services (Netflix, Hulu, Amazon Prime, etc.). It touted the ability to switch in real time between horizontal and vertical viewing as its key differentiator as well as design around short-form videos. The founders believed this technology would satisfy consumers as it would make the content easier to consume while commuting and traveling.

The ability to switch between portrait and landscape mode is the latest example of a unique technology that ultimately consumers did not care about. Foldable phones are another case of something that looks amazing but the bulk of customers see virtually no value. In the entertainment and gaming space, the industry (particularly naïve investors) is littered with other great technology that customers never valued:


  • Blockchain and crypto-currency Blockchain technology has been touted for years as the next big thing for gaming (both social and real money). I still see many people on LinkedIn talking about the missed opportunities in gaming with Crypto, but it is hard to fathom how everyone is missing an opportunity that has been top of mind for years. The people who tout crypto for gaming have never been able to connect the potential with any real problem consumers experience.
  • 3DO There have been many examples of game consoles that had better technology or more features but could not survive. One of the most salient is 3DO, a gaming console named Product of the Year by Time magazine in 1993. Despite being “Product of the Year,” it failed versus “inferior” products from Nintendo and Sega better delivered what customers actually wanted.

Quantity is critical

The second lesson from Quibi’s failure is the importance of having an (over) abundance of content. The biggest driver of revenue in the gaming and entertainment space is quantity of content, despite many people hoping, often wishfully, to find other drivers. When managing and growing games that are already live, the most certain way to increase revenue is to release more content (and the most likely way to see a decline is not to freshen up the content).

When building and growing a successful game, it is critical to create twice as much content as you would expect your most voracious VIP to consume. I have seen repeatedly companies build a six-month content pipeline that they were confident would satisfy all players only to have their top players run through it in a matter of a couple months (or even weeks). Once they run out of content, they churn to other options and are quite difficult to re-engage. Given that these are your most valuable customers, the cost can be enormous.

Companies frequently try to get off of this “content treadmill,” by innovating on features, events or putting in blockers to slow down consumption. While new features and great in-product events can add significantly to the value, they are not a replacement for more content. You still get a huge bump from new content. Conversely, putting in artificial blockers to slow content consumption almost always frustrates players and makes them more likely to churn, so while it does limit them to your available content, it does not negate the opportunity of delivering an abundance of content (you are actually covering up the underlying issue).

This effect is not limited to gaming, having a wealth of content is critical to consumers of entertainment across all media. Netflix has continued its huge growth by offering a surplus of new, original content weekly. Same driver for Amazon Prime’s success. Other companies solve the content treadmill by relying on user-generated content, which is almost endless. User-generated content is what has driven TikTok, YouTube and even social networks like Facebook to great success. Quibi tried to compete for the same users with a fraction of what customers could find elsewhere.

You also need exceptional quality

While quantity is critical, it does not negate the need for tent pole content. Successful entertainment companies build and maintain their position by creating must-have content that is strong enough to drive consumers to switch over to their channel or product. This content needs to be exceptional and draw in customers that previously thought they were satisfied with the options they are already enjoying.

This phenomenon is consistent in entertainment, from broadcast television to over the top media to gaming. The US television network NBC established decades long dominance driven by one or two situation comedies (Cheers, Friends, Frasier). HBO took the step from niche cable network to must-have content with The Sopranos and Sex and the City. Netflix moved from profitable movie rental company to an integral element of people’s lives with shows like House of Cards and Orange is the New Black. In gaming, Epic went from technology provider to gaming dominance with Unreal.

Quibi failed to deliver tent pole content that people felt they had to see. It invested in original content with A-list stars serving as actors and producers, much of which was entertaining but nothing that was unmissable. While engaging shows from the likes of Kevin Hart, Jennifer Lopez and Steven Spielberg may have entertained viewers, they did not have any flagship content that drove or even retained customers.

Need to plan for Complex Environments

I recently wrote about General Stanley McChrystal’s leadership lessons, with one of the keys being you need to plan for complex, rather than complicated environments. Being complex is different from being complicated. Things that are complicated may have many parts, but those parts are joined, one to the next, in straightforward and simple ways. A complicated machine like an internal combustion engine might be confusing to many people but it can be broken down into a series of neat and tidy deterministic relationships. Conversely, things that are complex, such as insurgencies or the streaming entertainment industry, have a diverse range of connected parts that interact regularly. A small disturbance in one place could trigger a series of responses that build into unexpected and severe outcomes in another place.

With Quibi, that disturbance was Coronavirus. In June, Quibi Founder Jeffrey Katzenberg said he attributed “everything that has gone wrong to coronavirus.” The reality is that to be successful in the entertainment space now, you need to build a company that is resilient and can adapt as the environment changes.

The Halo Effect confirmed

A final lesson from Quibi’s failure is that the Halo Effect is alive and well in the entertainment space. Quibi largely secured its financing on the reputation of its two leaders, founder Jeffrey Katzenberg and CEO Meg Whitman. I am a big fan of both. I love the content Katzenberg created as the Chairman of Disney for ten years and co-Founder of DreamWorks. I admire Whitman, who I credit with growing eBay into the company it is today and I hoped would run for the US Presidency several years ago. Success in these efforts, however, only highlights that you need a different skill set to grow a great streaming company.

The Halo Effect is attributing success or failure to an individual or specific action, which is often misleading. Success and failure are driven by multiple factors and there are no shortcuts to achieving great results. In the situation of Quibi, the leadership skills needed to succeed where very different to what was needed at DreamWorks or eBay:

  1. Start-ups are different. Scaling a company from zero to significant market share is very different than growing a large company. At a start-up, you need to find product/market fit and then grow from there. At a company like eBay, you already have the fit and need to focus on driving out the competition, marketing and margin.
  2. Streaming is a different world for entertainment. At a company like DreamWorks, you have a complicated problem to solve. You need to deploy hundreds of millions of dollars to create one piece of ultra-compelling content. In streaming media, you need a flow of compelling content while dealing with a complex environment (see previous point).
  3. Technology has evolved When Whitman led eBay, recommendations and personalization were a unique add-on. Now machine learning is part of the cost of doing business and you need to ensure every customer is getting the right experience for that individual. Companies like Netflix run thousands of tests a week and have terabytes of data on their customers, Whitman and Katzenberg did not have experience leveraging this data to meet customer expectations.

The predictability of the entertainment industry

Rather than chalking up Quibi’s failure to bad luck or the inability to create a hit in a hit-driven industry, it is the perfect example of the fundamentals to succeeding in the entertainment (including gaming) space:

  • Do not expect to rely on great technology or unique features to succeed, your customers need great content
  • Successful entertainment companies provide a glut of content so their customers never get satiated
  • You need to expand beyond great content to truly compelling and unique content that forces customers to go out of their way for your offering
  • Successful companies must be resilient and adaptive so they can adapt to a very complex environment where there are many unpredictable and uncontrollable events
  • The leadership team has to have the right skillset for this effort, not simply a track record of success in other ventures.

Key takeaways

  1. Quibi’s failure was very predictable and these predictors provide a framework of what companies need to do to succeed in the entertainment space.
  2. Quibi relied on a unique technology, the ability to watch content seamlessly in portrait or landscape mode, rather than relying on creating content people wanted. You cannot succeed in entertainment by relying on technology.
  3. Other key lessons are that great entertainment companies need to deliver a overabundance of content, much more than you expect even your heaviest users to consume, and some flagship products that forces people to try your offering.

Adjacent User Theory Shows How to Supercharge Your Game’s Growth

We are all constantly looking at ways to grow our game or app like Facebook or Twitter or Fortnite, so where better to start looking than Instagram. An article by Bengaly Kaba, The Adjacent User Theory, shows the methodology he used at Instagram to reignite its mega-growth. Kaba joined Instragram in 2016 and was instrumental in helping it grow from about 400 million users to over 1 billion.

Kaba credits his success to Adjacent User Theory, where potential users (adjacent users) are aware of the product, maybe tried it, but are not engaged customers. The app’s positioning or too many barriers in the early user experience often drive the lack of traction with these customers. In Kaba’s situation, the 400 million active users of Instagram represented instances where they found product-market fit but also missed over 600 million potential customers who either did not understand Instagram or how it would fit into their lives. According to Kaba, “our insight was that it is critical for growth teams to be continually defining who the adjacent user is, to understand why they are struggling, to build empathy for the adjacent user, and ultimately to solve their problems.”

Solving for the adjacent user

If you have a successful game or product, you almost certainly have a good understanding of your customers (or else you would not be successful). Essentially by definition, you do not have the same understanding of adjacent or future users, or else they would already be customers. Also, your future audience evolves over time, so what adjacent users are not getting now from your game might be different from what keeps your product appealing outside its core in six or twelve months.

To solve for the adjacent users, either your product team or a satellite of your product team needs to focus on these potential customers. Kaba writes, “[w]ithout a team dedicated to understanding, advocating, and building for your next set of users, you end up never expanding your audience. This stalls growth, and the product never reaches the level you aspire it to…. You can think about your product as a series of circles. Each of these circles is defined by the primary user states that someone could be in. For example Power, Core, Casual, Signed Up, Visitor. Each one of these circles have users that are “in orbit” around it. These users have an equal or greater chance they drift off into space rather than crossing the threshold to the next state. There is something preventing them from getting over the hump and transitioning into the next state. These are your adjacent users and the goal is to identify who they are and understand their reasons struggling to adopt. As you solve for them, you push the edge of the circle out to capture more of that audience and grow.”

Slack represents a good example of the power of adjacent users, according to Kaba. Slack has five user states — not signed up, signed up, casual, core free and monetized — and will lose potential customers at the transition between each of these five states. By understanding why people drop off between states before becoming monetized, Slack can make product changes that moves these adjacent users from non-customers to engaged customers.

Why companies are not focusing on adjacent users

While it seems obvious that converting adjacent users is critical for growth, many companies miss this opportunity. Kaba identifies three reasons for this problem

  1. Focusing on power users. It is natural to focus your development efforts on your VIPs, especially in gaming where a very small percent of your players drive most of the revenue. Thus, product development is geared to giving these players more of what they want, rather than bringing more customers into the tent.
  2. Personas. Many companies build personas (a fictional character created to represent a player type that might use a game) to determine who they are solving for. The mistake with this approach is that personas are usually created based on existing players, do not change as customers evolve, not based on relative usage/contribution and are too broad to be actionable.
  3. The home run swing. Product teams often look for the bold beat feature that will have a dramatic impact rather than a series of changes. Kaba writes, “they get bogged down by trying to establish product-market fit for a new set of users and never fulfill the potential of their current product-market fit.”


How to solve for adjacent users

There are several ways to mitigate the above issues and appeal to adjacent users. To overcome the bias of VIPs, product teams need to cross a “cognitive threshold” and understand the experience of non-VIP customers as well as non-customers. This includes your team putting aside their personal biases if they are using the product, they are not building it for themselves but building for adjacent users.

To avoid having your product team focus on the huge wins, Kaba writes that they must “[r]emember…adjacent users are the users who are struggling to adopt your product today. Non-adjacent users could literally be everyone else in the entire world. Sure, non-adjacent users might be a larger market, but the barriers to their adoption are also dramatically higher. Companies that try to go too big too soon and often, skip the next obvious steps and fail to solve their current adoption problems.”

Identifying and defining your adjacent users

Once you understand the value of adjacent users and how to build for them, you need to find them. You need to look at cohort decay, keeping in mind the different circles or user states for your game. You need to look at these variables (ie. registering to purchasing) and identify the decline in each cohort. That declines represents the adjacent users.

You then need to build a theory on who they are and why they are struggling or not converting. You also need to realize you will not have perfect visibility into the answer. Kaba describes the process, “is to lay out multiple hypotheses of who the adjacent users are, choose which one to focus on strategically, force your team to look at the product through their lens, experiment and talk to customers to validate and learn, then update the landscape to make your next choice. I like to think about it as a snowball. You know very little at first, but as the snowball turns you collect more information about the adjacent user, which helps you collect more snow (users).”

It is also important to gain a deep understanding of your current users. If you find that your current users are predominantly, male, 35-50 years old and from the northeast in the US, you can then look at each of these attributes to find adjacent users. For example, maybe you are losing women. Maybe you are not appealing to 50+. Maybe users from the Midwest are not connecting.

Once you have hypothesis on your current users you can create multiple hypothesis of adjacent users. Kaba recommends, “starting with a bottoms-up analysis of your data. You do not need to spend weeks talking to users to get a sense for who your adjacent user is. Look at what is happening on the edges of these states in the data. The data will help you identify places in the product that people are dropping off. This is the starting point to help you develop hypotheses about why different segments of users are dropping off.”

Understand the why

Once you have identified your adjacent users, you need to understand why they are dropping off. To achieve this knowledge, your product team needs to empathize with the adjacent users. This is usually a challenge as they often think like your VIPs and current users and find it difficult to put themselves in the heads of people who do not like their game or product. There are three ways, though, to overcome this problem:

  1. Be the adjacent user. Your product team needs to be experiencing your game in the conditions and settings that the adjacent user is experiencing. Some examples are new user flows, empty states, and product states that require different levels of play.
  2. Watch the adjacent user. This is done by usability testing. It is best to do this in the adjacent users environment, as focus groups and in-office usage creates artificial conditions.
  3. Talk to the adjacent user. Once you have identified adjacent users, ask them why they are trying to use your product, what jobs they are trying to solve, and what other games they play or have tried.

Prioritizing adjacent users

Once you understand your adjacent users and have identified what they need from your game or product, you need to prioritize. You cannot solve all of their issues at once, instead you need to focus on creating the most long-term value for your company. You want to do it in the correct order or sequence so that your efforts build on each other.

First, the adjacent users you should approach are ones different on only one or two attributes. You will only have to make limited changes or additions to your product to appeal to them.

Second, they should align with your strategy. Will the changes you have to make to appeal to this segment help you achieve your long-term strategy and vision for the product. You cannot please everybody always and trying to do so could potentially take away from what is making your game successful.

Third, start with adjacent users already in your funnel, customers you are losing, rather than trying to appeal to a completely new segment.

Not a one time exercise

Once you have identified and made product improvements to appeal to your adjacent users, do not proclaim mission accomplished, as the pool of adjacent users is constantly evolving. Efforts to build for one segment will identify new segments. These efforts will also bring in new adjacent users who you can then convert. Finally, these efforts will create a new or enhanced value proposition, which means that both current and adjacent users will have a new equation in deciding whether to engage. You will then want to adjust based on how they react.

Key takeaways

  • Adjacent users represent a great opportunity for growth. These are potential players (adjacent users) are aware of the product, maybe tried it, but are not engaged customers
  • You solve for these players by looking at different states of your product (i.e. registration, play, purchase) and seeing who drops off at each of these states, then understand why these potential customers are dropping off.
  • You can make your product attractive by putting yourself in the place of the adjacent user, watching them use your game or product and talking to them.

3 Words I Hate

Last year I wrote about one of the most insidious phrases in business (which, ironically, became a talking point in US politics last month), and there are three other words that exasperate me when used by gaming companies. These words — gamification, whales and directional — often drive the wrong actions, ideas or initiatives.



Trying to gamify a game is the height of absurdity, or at a minimum shows you have not done your job well. A game, by definition, is a game, so why would you want to add gamification. If done properly, the product already will entertain customers. A successful product will have a strong core game loop, that will drive your players enjoyment, and thus retention and engagement. The core loop is a chain of actions that the player does over and over again.

Gamification becomes a problem as it is often used as a solution for a poorly designed game. Rather than creating a strong core loop that retains players, companies try to use tricks (gamification) to overcome the shortcomings of the product. Gamification is often a euphemism for adding features that bandage over underlying problems with the product.

This problem also holds for casino and social casino games. Slots, poker, bingo, etc., represent great core game loops that have been entertaining people for hundreds of years. You do not gamify a slot machine, its core game loop is already compelling. Poker is a fantastic game that people will spend a lifetime playing. These are already great games and cannot be gamified.

If you are trying to make necessary actions outside your core game loop (registration, purchases, CS, etc.) better for the customer, you are not actually making them into a game (gamifying) but looking at principles of consumer behavior and behavioral economics to make users more likely to complete the tasks. You are not going to create a registration process that is more fun than Clash of Clans or more entertaining than the most recent Disney movie, and that should not be your target. Instead, focus on making the task effortless, so the player returns to your (entertaining) game.

The argument against gamification is not a criticism of building strong meta-features that enhance the core game loop. Adding a progression system or social features build on the core game loop but you are not gamifying your game, you are putting it in a superior package.


While gamification is misleading and often used as an excuse, the word whales is insulting and creates the wrong approach to your best players. Many companies, particularly in the iGaming and social casino world, use the phrase whales to describe their most valuable players. If you just look at my last sentence, you should see what is wrong with that approach. These companies are using a derogatory and insulting phrase to talk about the customers who in many (if not most) social games drive the majority or revenue. Rather than a condescending phrase, we should treat these players with the respect they have earned. For those who would argue whales is not derogatory, describe your partner that way to them and see how well it goes.

The damage in using the phrase whales is more than semantics, as it creates the wrong approach to your best customers. When you look at a group of customers as big, fat animals (no offense to actual whales, who are beautiful creatures), you are likely to treat them in a condescending or exploitative manner. Having started and built two successful VIP programs, I have seen that on a tactical level, this is a bad strategy because your highly valued customers are then are put into conflict with the company. The VIPs are trying to optimize their experience; you are trying to get as much wallet share as possible. Long term, the VIPs are more likely to go to another game where they feel respected (just as you would leave McDonalds if you get a condescending sales person and go to Panera). If you want VIPs to stay, call them VIPs and treat them that way.


While not as insidious as whales, another dangerous word is directional. This phrase is often used during or after an AB test, when the results are not statistically significant. Even without significance, you accept the winning variant as a preferred solution.

The problem with looking at directional results is that there is a lot of noise, and you are likely basing your decision on luck, not on numbers. Statistical noise is the random irregularity we find in any real life data. They have no pattern. One minute your readings might be too small. The next they might be too large. These errors are usually unavoidable and unpredictable.

Using directional results is no better than making decisions without numbers, and can lead to the same consequences. If the consequences are minor, or you know you will pursue a certain strategy regardless, then the AB test is a waste of resources and you should not have deployed it (which is fine, not everything needs to be tested).

Using directional data, additionally, creates the illusion of a data-driven decision and is subject to confirmation bias, as people use directional data to support decisions they have already made. I have never heard the phrase directional used when the result is not what the product manager or GM was hoping for. In those cases, the results would be considered inconclusive. People use directional to justify a course of action where there is no real data.

Key takeaways

  • Game companies should avoid the phrase gamification, as their product is already a game and should be entertaining.
  • Whales is an insidious phrase as it describes your best customers in a derogatory way, potentially leading to treating them in a way that destroys long-term value.
  • It is misleading to use data that is directional, without statistical significance as relying on this data is like not using data at all.
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