We'll respond shortly.
Once you’ve launched a product, “metrics” can be a powerful tool in measuring engagement and product issues. From the engineering side, devs have a hard time believing if a metric is valid or misleading. From the biz dev/marketing side, it’s hard to understand the technology enough to know what kinds of questions can be asked. I’ve gone up the learning curve on implementing, understanding, and actioning metrics and have noticed that people have a hard time getting started. This post is the first in a series on metrics, and I hope they give you the kick you need to get started.
Today I want to focus on the funnel, a strange analogy for describing websites and conversions. If you bought a funnel that only delivered 10% of the water you poured in, you’d ask for a refund. Yet, that’s how we describe the attrition that occurs as users/customers engage with your product. Funnels are important for two reasons: they force you to think about which interactions are most meaningful, and they help you understand where your assumptions aren’t valid.
At Profitably, we built a financial dashboard for small businesses. Our historical analysis offering was off the mark, so when the time came to tackle forecasting we wanted to build something more engaging, but also build in a way that allowed us to iterate quickly.
We took inspiration from the wizards in TurboTax to collect the information we needed from a business owner to deliver a useful customer forecast. Even though we were worried about the amount of information we [thought we] needed, we were encouraged by Twitter’s dramatic results from the introduction of gradual engagement for sign up (+29% conversion). This flow also enabled us to create a rather linear process from start to finish: no registration step, just enter the name of your company and click Get Started. Someone that successfully completed the wizard would see a detailed forecast for customer growth…end of the funnel.
We had talked with lots of small businesses before building to understand what they had been doing instead, but you can only get so far with conversations and mockups. Beyond these qualitative tactics, behavioral analytics gave us the ability to dive into this funnel and come out with hard numbers. Here’s what the initial KISSmetrics funnel looked like early in the release process:
Man, that is sobering. I had reached out to every person that went through to get a sense of their business and what problems they were hoping we could solve. But, to be honest, there was a lot of work staring us in the face just from looking at that [looooong] graph. Here are my thoughts on each step, and how we reacted:
Those are just the micro/optimization-focused thoughts and actions. After implementing some tactical fixes, we saw the funnel conversion go from 13% to something in the 65% range (5X). I’ll leave how we improved that funnel on a macro scale and took the product to a much better place for a different post. For now, I’ll leave you with something I try to remember when thinking about making a product better:
“Product development is about figuring out the single most important problem that exists right now and doing that and only that” (Jason Freedman).
By forcing yourself to identify the funnels that are most important to your product, you’ll force yourself to explain why people are falling out. You’ll also give yourself a quantitative feedback loop to confirm that new features actually keep people in.