FAILURE TO PIVOT

 

The decision to pivot is so difficult that many companies fail to make it. I wish I could say that every time I was confronted with the need to pivot, I handled it well, but this is far from true. I remember one failure to pivot especially well.

A few years after IMVU’s founding, the company was having tremendous success. The business had grown to over $1 million per month in revenue; we had created more than twenty million avatars for our customers. We managed to raise significant new rounds of financing, and like the global economy, we were riding high. But danger lurked around the corner.

Unknowingly, we had fallen into a classic startup trap. We had been so successful with our early efforts that we were ignoring the principles behind them. As a result, we missed the need to pivot even as it stared us in the face.

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We had built an organization that excelled at the kinds of activities described in earlier chapters: creating minimum viable products to test new ideas and running experiments to tune the engine of growth. Before we had begun to enjoy success, many people had advised against our “low-quality” minimum viable product and experimental approach, urging us to slow down. They wanted us to do things right and focus on quality instead of speed. We ignored that advice, mostly because we wanted to claim the advantages of speed. After our approach was vindicated, the advice we received changed. Now most of the advice we heard was that “you can’t argue with success,” urging us to stay the course. We liked this advice better, but it was equally wrong.

Remember that the rationale for building low-quality MVPs is that developing any features beyond what early adopters require is a form of waste. However, the logic of this takes you only so far. Once you have found success with early adopters, you want to sell to mainstream customers. Mainstream customers have different requirements and are much more demanding.

The kind of pivot we needed is called a customer segment pivot. In this pivot, the company realizes that the product it’s building solves a real problem for real customers but that they are not the customers it originally planned to serve. In other words, the product hypothesis is confirmed only partially. (This chapter described such a pivot in the Votizen story, above.)

A customer segment pivot is an especially tricky pivot to execute because, as we learned the hard way at IMVU, the very actions that made us successful with early adopters were diametrically opposed to the actions we’d have to master to be successful with mainstream customers. We lacked a clear understanding of how our engine of growth operated. We had begun to trust our vanity metrics. We had stopped using learning milestones to hold ourselves accountable. Instead, it was much more convenient to focus on the ever-larger gross metrics that were so exciting: breaking new records in signing up paying customers and active users, monitoring our customer retention rate—you name it. Under the surface, it should have been clear that our efforts at tuning the engine were reaching diminishing returns, the classic sign of the need to pivot.

For example, we spent months trying to improve the product’s activation rate (the rate at which new customers become active consumers of the product), which remained stubbornly low. We did countless experiments: usability improvements, new persuasion techniques, incentive programs, customer quests, and other game-like features. Individually, many of these new features and new marketing tools were successful. We measured them rigorously, using A/B experimentation. But taken in aggregate, over the course of many months, we were seeing negligible changes in the overall drivers of our engine of growth. Even our activation rate, which had been the center of our focus, edged up only a few percentage points.

We ignored the signs because the company was still growing, delivering month after month of “up and to the right” results. But we were quickly exhausting our early adopter market. It was getting harder and harder to find customers we could acquire at the prices we were accustomed to paying. As we drove our marketing team to find more customers, they were forced to reach out more to mainstream customers, but mainstream customers are less forgiving of an early product. The activation and monetization rates of new customers started to go down, driving up the cost of acquiring new customers. Pretty soon, our growth was flatlining and our engine sputtered and stalled.

It took us far too long to make the changes necessary to fix this situation. As with all pivots, we had to get back to basics and start the innovation accounting cycle over. It felt like the company’s second founding. We had gotten really good at optimizing, tuning, and iterating, but in the process we had lost sight of the purpose of those activities: testing a clear hypothesis in the service of the company’s vision. Instead, we were chasing growth, revenue, and profits wherever we could find them.

We needed to reacquaint ourselves with our new mainstream customers. Our interaction designers led the way by developing a clear customer archetype that was based on extensive in-person conversations and observation. Next, we needed to invest heavily in a major product overhaul designed to make the product dramatically easier to use. Because of our overfocus on fine-tuning, we had stopped making large investments like these, preferring to invest in lower-risk and lower-yield testing experiments.

However, investing in quality, design, and larger projects did not require that we abandon our experimental roots. On the contrary, once we realized our mistake and executed the pivot, those skills served us well. We created a sandbox for experimentation like the one described in Chapter 12 and had a cross-functional team work exclusively on this major redesign. As they built, they continuously tested their new design head to head against the old one. Initially, the new design performed worse than the old one, as is usually the case. It lacked the features and functionality of the old design and had many new mistakes as well. But the team relentlessly improved the design until, months later, it performed better. This new design laid the foundation for our future growth.

This foundation has paid off handsomely. By 2009, revenue had more than doubled to over $25 million annually. But we might have enjoyed that success earlier if we had pivoted sooner.5