How do you decide what to build before you have enough data?
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While building an early-stage SaaS product, I have found that AI makes it surprisingly easy to turn an idea into a working feature but, deciding whether it is the right feature to build is much harder. At our stage, we rarely have enough usage data to be certain and we usually have to combine a handful of customer conversations, early usage pattern and our own judgment. When the signal is unclear, we try to build the smallest usable version first and learn from it.
For other early-stage founders, what gives you enough confidence to build a feature when the data is still limited? Do you rely more on repeated customer requests, observed behaviour, willingness to pay, or founder judgment?
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My opinion is you don't need data to build, you need it to know what to kill. When the signal's unclear I build the version that's cheapest to throw away, not the one I'm most sure about.
@maxwell_wx Makes sense but I see one problem with this. When everyone is shipping the cheapest version that only solves a small fraction of the user problem, it may not create enough value to generate any meaningful pull. I have seen this with many first time founders who keep moving from one idea to another assuming the idea was not worth pursuing when the first version was simply not useful enough, In this case, how do you distinguish weak demand from an underbuilt product?