The Journey: #70 Product Ideas to Prioritize and Punt

When I was a CSM, I treated every single feature request like it was the most important thing in the world. A customer would say "it would be really helpful if we could do X" and I was off to the races. Writing it up, submitting it, following up on it, advocating for it in every room I could get into. I thought that was my job. I thought that’s what it meant to be the voice of the customer. Push for what they want. The problem? I didn't know the difference between what customers wanted and what they actually needed. I didn't ask. I didn't dig. I didn't challenge. I just collected and lobbied. It wasn't until I stepped into a leadership role that the picture got a lot more complicated. I remember my first product planning meeting as a VP. In the room: the CPO, the CEO, the CRO and me with a list of 100+ feature requests that my team had surfaced. Then I was asked a question that stopped me cold. "What are the three things you need us to prioritize for the next sprint?" Three. Out of a hundred+ feature requests. I actually Slacked the CEO afterward and told him there was no way I could get it to three. His response was short and the direction was clear: "It's your job to narrow it down and make the right call." That was it. That was the moment. I went back to my team and we started the work. Hours of data analysis. Conversations with every CSM. We built criteria from scratch: What's blocking revenue? What's a retention risk? What's a blocker vs. a nice-to-have? What's the logo impact? How does this align with where the product is actually going? Where does it overlap with what sales is hearing? Slowly, the list got smaller. Not because we ignored customers, but because we finally understood them. And something else happened too. Once we reset expectations with customers, explaining that feature ideas are ideas, not commitments, and that we'd build what was best for the business, the quality of what they submitted went up. The noise went down. The list got sharper because the customers got smarter about what they were asking for. The requests that remained were the ones that mattered. The Takeaway: Being the voice of the customer doesn't mean advocating for everything they ask for. It means being the person who can tell the difference between what they want and what they actually need … and making the call.

The Field Reality

This plays out in CS orgs every single day, and most teams are stuck at the collection stage.

CSMs are great at gathering feedback. They're trained to listen, to document, to relay. What they're rarely trained to do is filter. And that gap costs everyone -- the product team, the customer, and the CS team itself.

When CS shows up to product planning with a sprawling list and no prioritization framework, two things happen. Product stops taking the input seriously, and CS loses credibility as a strategic voice.

The shift happens when CS starts owning the "why" behind the "what." Not just "ten customers asked for this" but "this is blocking $2M in renewal, it affects our three largest logos, and it's not on the roadmap for a reason we need to revisit." That's a different conversation.

The CSMs who earn a seat at the product table aren't the ones who show up loudest. They're the ones who show up prepared with data, context and a clear point of view.

If your team is still treating every feature request like it deserves equal weight, that's the work. Not building a bigger list, but building a better filter.

AI in CS

AI is changing how fast you can get from "100 requests" to "here are the 3 that matter." Here's where it's showing up:

• Synthesizing feedback at scale: AI tools can cluster and theme open-ended feature requests across your entire customer base in minutes, surfacing patterns that would take a team days to find manually

• Revenue and risk tagging: With the right data inputs, AI can flag which requests are tied to at-risk accounts, expansion opportunities, or high-value logos, so you're not doing that mapping by hand

• Sentiment and urgency scoring: Tools are starting to score the intensity behind requests, not just the frequency. This helps helps separate the "that would be nice" from the "we will churn if this doesn't happen"

• Product alignment matching: Some platforms are beginning to cross-reference customer requests against stated product strategy, flagging where there's a gap and where there's natural overlap with what's already planned

• Sales and CS overlap detection: AI can pull from both CS and sales feedback channels to identify where themes are appearing on both sides of the house -- a strong signal that something deserves prioritization

The goal isn't to automate the judgment call, you should still own that. But AI can dramatically shorten the time it takes to get to the conversation that matters.

Closing with Kristi

The best CS leaders I know aren't the ones who fight the hardest for everything. They're the ones who know exactly what to fight for.

That clarity doesn't come from the customer. It comes from the work you do before you ever walk into that room. The data, the criteria, the honest conversations with your team.

Get that right and you stop being a collector … you’ll become a strategist.

See you next week,

Customer Success. Revenue Follows.