• Low-usage features are slowing us down, but the DAO won’t agree to remove them. What’s the right Product Ops process?

    Aditi  R

    Aditi R

    @aGoKU4J
    Updated: Nov 14, 2025
    Views: 68

    I’m leading Product Ops in a DAO, and honestly I’m stuck. Our analytics dashboard has 14 modules, but only 4–5 get real traffic. Still, every time I suggest removing or even reviewing the low-usage features, contributors push back saying “someone might use it later.”

    The problem is we don’t have a proper process for this — no data thresholds, no decision criteria, nothing. In my previous Web2 role, we could quietly retire low-usage features based on adoption data, but in a DAO every change becomes a governance issue and people take it personally.

    Meanwhile, keeping these modules alive is draining dev/QA time and slowing our actual roadmap work. I’m not trying to force anything — I just want a fair, transparent way to decide what should stay and what should go.

    For those who've worked in DAOs or Web3 Product Ops: how do you decide when it’s time to deprecate a feature without causing community drama or losing trust? What’s a process that actually works?

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  • ChainPenLilly

    @ChainPenLilly3w

    We ran into this exact problem at Polygon DAO. The only thing that worked was switching to a data-first, rule-based process so people understood we weren’t removing features based on opinions.

    We created a simple Feature Lifecycle Matrix with three signals: • 7-day active wallets • share of total gas usage • number of on-chain interactions If any module fell below 2% of ecosystem activity for 30 days, it automatically moved into a “Review” state.

    At that point, Product Ops posted a clear proposal explaining usage, alternatives, and what the migration path looked like. UI alerts told users the feature was under review, so nothing felt sudden.

    Once you make the process predictable and quantitative, people stop treating deprecation like a personal attack. They see it as part of maturing governance rather than “killing someone’s idea.”

  • AlexDeveloper

    @Alexdeveloper3w

    We solved this in a DeFi project with a public Sunset Dashboard that showed feature usage, maintenance hours, and QA load. One module used 28% of QA time but had less than 5% user activity — seeing that made the community vote for removal themselves.

    We also added a freeze phase: disable the feature for two sprints before proposing deletion. If nobody complained, that was clear validation. When you frame it as “resource allocation” rather than “removal,” contributors become much more reasonable.

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