If you’ve reached product-market fit, it means you’ve got the innovation piece nailed. You’ve figured out how to take an idea and package it into a product and deliver it to market. Now comes the challenging part, taking early traction and expanding it into broad market penetration.
My name is Ariel Tseitlin and I’m a partner with Scale Venture Partners. I studied computer science at UC-Berkeley and then later went on to get my MBA at the University of Pennsylvania at the Wharton School of Business. I started my career as a software engineer, writing tools and UI for the EDA industry. Before coming to scale, I was at Netflix where I was in charge of the streaming operations group in building the streaming experience for all of the users. If you’ve reached product market fit, it means you’ve got the innovation piece nailed. You’ve figured out how to take an idea, package it into a product, and deliver it to market. Taking that early traction, and expanding it into broad market penetration while maintaining product market fit is the challenge of scaling. One reason why it’s challenging is because the early customers that got you early product market fit may be very different from later customers that expand and grow your business. Another reason why it’s difficult is because complexity and required communication flow will increase greatly as you scale the product. And these are the things that we’re going to talk about how to address as you’re scaling the product.
So the biggest difference between product design at the early stage when you’re just coming to product market fit and when you’re scaling it is that at the early stage you’re just really path finding. You’re trying to understand what the users’ needs are and what’s the simplest, minimum viable product that you can build in order to meet those needs. Once you’ve met that, then the challenge of scaling the product is then thinking about how do you maintain your existing user base and keep them happy while you attract a whole new set of users. Once you have an established user base, and you know the lifetime value for the existing product that you’re selling them, then you need to start thinking about what other product enhancements or what other adjacent products you can sell into that existing user base in order to increase the value that you’re delivering to them, and in order to increase the likelihood of retaining them over time. The product that made you your first million dollars is very unlikely to be the same product that’s going to generate $100 million for you. In order to continue growing, you’ll have to do that which got you here in the first place. Iterate and innovate. The best way to foster this type of innovation is to create a framework of experimentation. Think about different product ideas, different product initiatives, different product features as experiments that you specify early on with an expected hypothesis and outcome. Investing in automation and tooling can be one of the critical investments to make during this phase in order to foster innovation. It will allow you to create a competitive advantage that will keep your innovation engine strong and humming as you scale and as you grow your organization. The challenge is that you need to balance institutionalizing and systematizing processes that scale the product that you have while allowing you to innovate and grow into the product that you want to be in the future. A great example of this in the real world is Amazon. That started out as an online bookseller, became wildly successful as the world’s largest e-commerce store, and then recently moved into the public cloud by providing compute infrastructure for the world’s computing needs. They’ve innovated from one product line to another while maintaining their core focus and growing their business.
A growing organization is like a large complex system with many interact feedback loops that are often unseen and unknown. Like any complex system, if the feedback loops aren’t visible and understood, emergent, unexpected behavior can occur that can be very difficult to diagnose. Take the time to understand the feedback loops in your organization and create mechanisms in order to share information with the rest of your organization on how those feedback loops impact every part of the organization and the product. Over-optimizing for information flow and transparency can be one of the keys to doing this successfully.
Here’s an example of what I mean. As your product grows, the features will expand and your product naturally becomes more and more complex. The result of that is that you often have to staff up your training organization and your support organization in order to help your customers understand that added complexity. One of the things that is often missed though is that because of that complexity, the product becomes more difficult to use, and that inhabits account expansion. So it’s often a surprise when later on we find that account expansion doesn’t match earlier periods and that can often be traced to slowly increasing complexity in a product. So these kinds of feedback loops are very important to understand and diagnose. Deeply instrumenting your product can be one of the most important investments you can make in order to understand these hidden feedback loops. Creating very deep analytics that help you understand how your product is used at every different point in the customer journey can really help illuminate where these hidden connections lie, and help you understand where these signals are coming from.
Make sure your decisions are data-driven. Having a small set of one, two, or maybe three key performance indicators helps provide focus around product decision making and eliminate the curse of the HPPO, the high paid person’s opinion. For example, at Netflix, we had two primary KPIs—subscribers and viewing hours. And the way we picked those KPIs is thinking about what were the most important things to the business? Firstly, it was revenues and subscribers were the primary drivers of revenues. And we picked viewing hours because viewing hours were the most correlated to retention which indicated whether users were going to stick with the service or not. And we were able to make most product decisions based on their impact on these two KPIs.
Security is another really important topic when we think about scaling the product. Software companies are keeping security top of mind in the way that they build and scale their products. But as the physical world becomes more and more connected, non-software companies must think about security in equally important measure. I’ll give you a recent example. Hackers were able to break into a Jeep so that at highway speeds they would be able to take control of the car while it was moving. Obviously, this created a huge problem for Chrysler. It was a PR nightmare, and they had to issue a recall to 1.4 million vehicles. Owners had to either have a USB stick mailed to them that they had to then insert into their vehicles in order for them to fix their vehicles on their own, or the users had to take those vehicles into a Jeep repair shop in order to get them repaired. This was a huge expense for Chrysler, and an incredible inconvenience for the users. Now contrast that with a similar incident that happened just a few weeks later to Tesla. Hackers were also able to break into the vehicle and take control of it. However, Tesla issued an over-the-air update to its cars, and the cars updated themselves overnight without the users having to do anything or take any actions. Very, very different result between these two companies. Having a focus on security early and be the difference between having a response like Chrysler and having a response like Tesla.
As you go broader into the market, expect your investment into R&D to increase as you address more and more sophisticated users, and more demanding use cases in the broader market.