Use NPS data and AI to prioritise your product road map
Product & Tech Initiative Blog | 10 June 2025
Two years ago at our CEO off-site gathering in Vail, we talked about how Net Promoter Score (NPS) could reveal our value across the chain — not just as a number but as a map to customer love.
At the time, we knew it could be powerful. But now, with AI, it’s like adding rocket fuel to that process.
Over dinner recently with an old friend (a management consultant who is sharp as ever), our conversation turned to product prioritisation. He casually dropped this: He’d used an NPS survey and AI to surface the most important product priorities — before his morning coffee. Something that would normally take a team a week was done on his commute.
That made me pause. Should we as news media be doing this?
Here’s a simple idea worth testing:
Run your NPS survey: But go big. The more data, the better. And remember to do this at different parts of the customer value chain. If you already have this data, congratulations.
Segment your responses: Remove the hardcore detractors for now. Not because they don’t matter, but because they may never be won over. Focus first on those who already love you — or could.
Upload it to ChatGPT (or another AI tool): Ask it to cluster the feedback, summarise themes, and point out the most frequently mentioned wants, fixes, or loves. You’ll be amazed at the speed and clarity.
This is the kind of insight that would normally involve a week of workshops, multiple teams, and a lot of Post-its. Now? It’s doable in under an hour — assuming you have the data.
Please try it, even with a small set of data you already have. At worst, you’ve lost an hour. At best, you’ve saved thousands in consulting fees and unlocked real signals on what your audience values. Either way, it’s a win.
And if you do free up that budget, you might want to redirect it to something even more valuable — like our upcoming Media Tech & AI Week in San Francisco. It’s packed with ideas just like this — from people doing the work, not just talking about it.
Because in the end, product is still all about the customer. Now we just have better tools to listen and analyse.
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