Rahul Vora: evaluation

Transcript context

…Okay, I got to follow this thought on algorithmically building a roadmap to increase product market fit. Talk about just how one would do that. Well, I mean, that's really the meat of the engine. So let's see if I can condense it here in a very easy to grok fashion. So... Let's assume for the sake of argument that you can put a number on product market fit. And it turns out you can. Very simply, you're going to ask people, how would you feel if you can no longer use this product? You give them three responses. One of them is very disappointed. The other is somewhat disappointed. And the other is not disappointed. Very disappointed means I'd be like devastated. I love this product or I need this product. And what Sean Ellis found, Sean Ellis, if you don't know him, is the guy who coined the term growth hacker. And he instrumented, benchmarked this initial question. What he found is that the companies that struggled to grow almost always had less than 40% very disappointed, whereas the companies that grew the fastest almost always had more than 40% very disappointed. And this question, this metric, is way more predictive of success than something, for example, like net promoter score. Okay, so far so easy. How do we make this number go up? Well, you want more people to be very disappointed without your product. And the trick here is... Not to act too much on the feedback that the very disappointed people are giving you because they already love your product. Also not to act at all really on the feedback that the not disappointed people are giving you because they're so far from loving your product that they are essentially a lost cause. But to focus on the segment of the somewhat disappointed people, they kind of love your product, but something, and I would wager something small, is holding them back. So you then divide them into two camps, the camp for whom the main benefit of your product resonates and the camp for whom it doesn't. And what do I mean by that? Well, you go back to the people who really love your product and you basically ask them why. What is it about my products that you really love? In the early days of Superhuman, it would have been speed and keyboard shortcuts and the overall design aesthetic as well as the time that we were saving you. You then go back to the somewhat disappointed users. And in the superhuman example, I would simply ask, wait, do you like superhuman because of its speed or for something else? And if it's something else, well, and this is hard to do, but politely disregard those people and their feedback. Because even if you built everything that they asked for, they're still pulling you in a different direction. And the thing that they like the most from your product isn't actually what the people who en masse love it the most for is. So you have then articulated the sub-segment of the sub-segment that it makes sense to pay attention to. And there's another question in the engine to figure out what they don't like about the product. Now you have a list of things people love. You have a list of things people don't love. y attention to. And there's another question in the engine to figure out what they don't like about the product. Now you have a list of things people love. You have a list of things people don't love. And you can work down that list to make the product market fit score go up. And basically at the start of every planning cycle, I advise spending half your time doubling down on what people really love and half your time systematically overcoming the objections of the somewhat disappointed users, but specifically those for whom the main benefit resonates.…

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