The Importance of Focus for Startups
Today, Instagram — an app that has hit a milestone of over 1 billion users — is purely associated with photo sharing and social media. What few people know, however, is that Instagram did not start out this way: it was founded back in 2010 as Burbn, by Stanford graduate Kevin Systrom. Burbn’s product enabled people to say where they were going (a lot like Foursquare’s check-in product), make plans with their friends, and get virtual prizes for going out more. As Systrom would describe the product to investors: “It’s a fun way to see what your friends are doing and go join them in real life! You can get inspired about where to go next!”
This application failed to generate the excitement needed to take a product from zero to one. While Kevin Systrom was able to raise some seed venture money for Burbn ($250,000 from Baseline Ventures, $250,000 from a16z, and a $25,000 angel investment from Twitter co-founder Jack Dorsey), these investments were more of a bet on Systrom than a bet on the product fundamentals itself. Though Systrom got his friends (and the friends of his friends) to use the app, it would plateau at 80 users, not showing much promise for growth.
Systrom and his co-founder Mike Krieger knew they had to change something. But instead of searching outside of their current stack to expand to another product line, they instead decided to take a close look at what they already had. On a day which would represent an inflection point for the company, Systrom and Krieger made a list of the top three features of their app, based on customer reception. One was plans, in terms of being able to see where friends went and then join them. Another was the visual component of photos, where users could share pictures of where they went (this was the part of Burbn which customers were engaging with the most). The last was the virtual prizes, which served as a way to incentivize users to log back in. Systrom and Krieger took a hard look at these three, and decided they needed to focus on photos and cut the other two. People didn’t need an app for making plans (there was already tons of competition in the market for check-in apps), nor would meaningless virtual prizes be able to grow into a sustainable business. Photos, on the other hand, were ubiquitous and useful for all. It leveraged the technological wave of the shift to mobile, with more people being able to carry a camera 24/7 in the form of their phone, and thus take more pictures. Instagram’s transformational feature of filters led to more people posting their pictures because of their overall increased satisfaction with them, and the combination of this and the social network component which Instagram created (follows, likes, etc) led to a product which achieved viral growth. 25,000 people were using the product on the first day, which turned into 100,000 within the first week, and 2 million users in a few months. The rest is history.
Instagram’s story isn’t just another example of a company pivoting to adjust to market needs; it’s a brilliant case study in the importance of focus for a startup. As strategy guru and Harvard Business School professor Michael Porter has said, “The essence of strategy is choosing what not to do.” Entrepreneurs often come into their startups with complicated, multifaceted products which they want to take to market. Often, the best thing to do is to be minimalist about it, thinking about what the core essence of the product is and removing anything that adds unnecessary complexity.
This thought process should certainly be guided by data, and is especially useful following a period of experimentation. Experimentation is the key form of discovery for startups: it’s how they iterate, building products and receiving customer feedback to see if they should persevere or pivot. For startups, experiments can often be high-optionality plays, where the experiment doesn’t use high quantity of resources but could net huge returns if it truly resonates with the market. Looking at user retention, churn, growth rates, DAUs/MAUs (for high frequency products) and other pieces of granular product data can be key in informing a company’s decision to continue or put an end to a certain experiment.
But there comes a point where trying and testing new ideas becomes a hinderance to focusing deeply on a core product, where the opportunity cost of experimentation reaches its maximum. Experimentation is for gathering data to find out what works, what doesn’t work, and what really works. Once the company is able to hit on something that really works, either from the data or from a unique insight they come across, any time not spent on that is time that’s not being properly utilized. In Instagram’s case, their decision to focus squarely on photos was a combination of the data they got from Burbn’s usage, their conversations with investors and customers, and their insights on which markets had problems which they could properly position themselves to attack. Once they settled on photo sharing as their core focus, they went full steam ahead on that and only that.
A huge proponent of focus in a business setting is the late Steve Jobs. As Jobs once said, “People think focus means saying yes to the thing you’ve got to focus on. But that’s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully. I’m actually as proud of the things we haven’t done as the things I have done. Innovation is saying ‘no’ to 1,000 things.” Jobs echoed this sentiment during his time at Apple — two examples show this. When Jobs returned to Apple in 1997, the company had dozens of product lines; he cut it to just four: consumer desktop, pro desktop, consumer laptop, and pro laptop. He did this because he knew that his team at Apple had finite time, energy, and resources — investing those resources in a few brilliant products would prove to be better than investing them in multiple good ones. Another example involves an Apple strategy offsite, where the top people at the company worked to reduce their strategy to ten priorities. Jobs stood up and crossed out the bottom seven priorities, claiming that they could only do three.
Even with Apple’s emphasis on focus, they’ve still needed to release multiple products over time. The world changes. A product that’s superb today will grow stale in a few years. In order to stay alive, companies need to continue to innovate and break into new product categories. All the great companies have been multithreaded, either through in-house processes or acquisitions. Microsoft started with the PC, became a player in the operating systems business, and then got into the cloud game fairly recently. Google started in search, built their AdWords business, and then got into the video and phones space through acquisitions of YouTube and Android, respectively. Even Facebook: they started with social networking, made acquisitions in chat and VR (WhatsApp and Oculus), and are now rebranding into a Metaverse company. The lesson? Multithreading is essential and will happen. The danger is in multithreading too early, before the company has hit the global maximum for their core product. If they multithread before this, they can risk future growth in the areas which they are dependent upon.
A prime example of a company multithreading too early is Mixpanel, a product analytics company. Suhail Doshi, the co-founder of Mixpanel, initially got the idea while working as a product intern at Max Levchin’s startup Slide (which is now defunct); he didn’t have the proper metrics to truly gauge the performance of the products he was working on. While many other companies used tools like Google analytics, that service mainly showed how users got to a product, not what they did there. In alignment with the macro trend of big data and more data-driven decision-making, Doshi built Mixpanel to provide product teams with more advanced and granular analytics. Mixpanel was solving a problem which was a real one for startups, and people began to take notice, validated by their acceptance to YCombinator in the summer of 2009. The company soon began to hit many key milestones; as Neil Rahilly, Mixpanel’s VP of Product and Design, described: “When I joined, Mixpanel had really just started to take off, and we had this incredible product-market fit with startups and helping them with understanding their product usage and prioritizing and designing to build a successful product. We actually were [growing really fast] without a big sales team. And so there was a sense of ‘Hey, we can really accelerate growth even further by building a big sales team,’ which we did and which worked — at least initially.”
Mixpanel was living the startup dream: they built something which customers needed, found product-market fit, and were growing rapidly in an organic way. But premature multithreading and expansion to new product lines, with an underlying lack of focus, would the primary factors which nearly brought Mixpanel back to zero. After raising a huge Series B round ($65 million in funding at a post-money valuation of $865 million), the company built a messaging app and an A/B testing service. These key decisions led to time, energy, and resources being devoted to the new product lines, taking away focus from the heart of Mixpanel (their product analytics service) that had gotten them this far. Furthermore, Mixpanel decided to move up market and focus on selling to the enterprise rather than just to startups and small businesses, as those customers provided the opportunity of bigger sales and more top-line revenue. While this is a common play for B2B companies, Mixpanel’s product was perfectly suited for the market segment of startups and small businesses (as proven by their product-market fit and hyper growth), and premature expansion to a new market segment with different needs would lead them astray. By trying to expand to different product lines and serve new market segments, Mixpanel had taken their eye of the ball which was the core essence of their business, and the results were starting to show that: their customer retention rate, WAU’s (weekly active users), and NPS (net promoter score) were all in precipitous decline.
Luckily for Mixpanel, they confronted these brutal facts and acted upon them by making the strategic shift to refocusing on their core product. As Rahilly has said, “In my mind part of the reason why we had to refocus was that it was just evident that we could not get to the level of quality and depth across the entire surface area that we had with the resources that we had. And so we had to cut scope.” Observations like these led Mixpanel’s decision to cut the two products of messaging and A/B testing, a considerably risky decision given the vast resources invested in these initiatives. But looking at the TAM of the product analytics market showed them that any potential revenue lost from their other product lines would be made up by capturing a bigger size of an already big pie. Their decision to refocus on their core product analytics service paid dividends: since this decision, their gross dollar retention has gone from 50% to 85%, NPS has increased 15 to 85, signups went up by 67%, and WAUs grew 52%.
Sam Altman, the CEO of OpenAI and former president of Y Combinator, has presented the following graph at classes he’s taught at Stanford and YC. His theory is that, when given the two dimensions of number of users and the intensity that users like your product, there is a finite area under the curve when a product first launches. As the graph demonstrates, a product can either start with a high number of users who like the product, or fewer users who love the product. Which path is more effective?
The second option is far more effective. Though it doesn’t acquire as many users at first, it captures a niche market with users who are going to engage heavily with the product, be retained as users, and spread the word. Once a startup achieves product-market fit in a niche market and gains traction, it becomes substantially easier to grow at a rapid rate and expand to various adjacent markets. Engagement is a powerful catalyst for user acquisition, both through UGC (user generated content) SEO loops and the increased probability of viral growth through word of mouth or referrals. Contrast this with the first option: though the initial user acquisition numbers may be high, the customers don’t really like the product, so they don’t engage with it as much. As time goes on, they start to see less and less value from it, so they churn, which thus lowers the LTV (lifetime value) of the average user. Growth wouldn’t be organic so the company would have to spend a lot of capital on customer acquisition, leading to an even lower LTV/CAC ratio and making them further financially inefficient. It would create a snowball effect which would spiral out of control and eventually kill the company, despite the early noise of massive user acquisition. It’s clear which approach drives better outcomes in the long run: a smaller cohort users who have a higher intensity of affinity for the product.
The first approach is only possible if the startup has a deep sense of focus for building for that specific small cohort of users. Extrapolating out, a determinant of a startup’s future success is their capacity and ability to be intensely focused on their objectives at hand in order to build something that users truly love. A key proxy for this is can they reach an intense level of focus on a particular problem and go really deep on it? Do they care enough about the problem they are solving, have the learning capacity to master their market, and have the grit to persevere? As much as its a product game or market game, startups are also a people game.
And oftentimes, from a people standpoint, early stage startups are composed of generalists — people who have a general array of skills and can do whatever is needed to execute on the goals at hand. That’s the paradox of this entire thing; bringing a group of generalists to specialize on a specific problem or building something from a specific cohort of users. But at the same time, maybe it’s a perfect combination, as the coalescence of versatile minds and forms of intellectual capital, all deployed in unison and in a concentrated manner, can drive special solutions.
