📊 My experiment with data-driven product development

When it comes to product development and deciding what to work on next, I have never really followed a specific methodology. I just fixed the bugs that seemed the most annoying, and built the features I thought people wanted.

That kinda works, but I'm always wondering: is this really the thing I should be working on? Will this move the needle? How do I know these changes are actually helping my business? What if they are actually hurting it?

Looking at signups and MRR gives me some idea how my business is doing, but they don't really show me where the potential problems lie and opportunities for growth are. So starting today I'm going to try out a more data-driven approach.

I've also decided to share the process with you. As I figured many other makers might struggle with the same questions. So hopefully this will be a useful exercise for both of us. I encourage you to follow along and share your own progress on WIP so we can learn from each other.

Stay tuned for the next post where I'll dive deeper into the metrics I'll be tracking.

I'd love to hear your experience with metric-driven development. Let me know in the comments!

I love the idea!

Shameless plug.. I built ml4all with exactly your thought-process in mind. Although early-stages and many features missing, it's functional. Whatever data you collect, you can quickly stick in in there and see what works. While often that might not be a big surprise, you have now data-validated facts instead of gut-feeling. And sometimes there are surprises.

You ask me to follow along - promised - I will! :)
This is exciting!

Thanks for sharing. Could you elaborate how you see ML helping in this case?

E.g. - If and when you build your CLV model, ML can help you to have an individual CLV per user. I have an article on CLV and plan to write part two where I explain in detail how ML can help here

I read the article, but still not sure what role machine learning would play haha

It took me some time, but I just published an article on exactly this questions - how machine learning is helpful to improve customer retention:…