The 6 Best Tools to Decide Which Features to Sunset in 2026

Product Teacher offers a clean heuristic for deprecation: a feature used by under 5% of your base, less often than once a month, is a candidate. It is a good heuristic. It is also the exact point where most teams stop looking, and stopping there is how you sunset the feature that three of your largest accounts wrote into their renewal criteria.

The strongest tools for deciding which features to sunset are Enterpret, Pendo, Amplitude, Mixpanel, Productboard, and Gainsight PX. Five of them answer how much a feature is used. One of them answers who is using it, what they pay you, and what they will do when it disappears. Those are different questions, and only the second one is the decision.

What product teams actually need to make a sunset call

1. Usage, segmented rather than averaged. A 3% adoption number is meaningless until you know whether that 3% is spread thinly across your long tail or concentrated in your enterprise tier. The average hides the only fact that matters.
2. The reason for low usage. Low adoption has at least three causes: nobody needs it, nobody can find it, or it is broken in a way people stopped reporting. Behavioral data cannot distinguish them. Only the language customers use about the feature can.
3. Structure that keeps up with your product surface. Feature-level themes only work if the categories track the product as it exists now. If your feedback taxonomy is maintained by hand, the theme for the feature you are considering killing was named two releases ago and may not cover the way customers actually describe it today.
4. Revenue and account context attached to the feature. Before you deprecate, you need the list of accounts who depend on it and their combined ARR. This is the number that determines whether this is a cleanup or a churn event.
5. A read on the replacement. Pendo's own account of sunsetting its Trends report is instructive: the trigger was a newer feature that covered the same use cases better. Sunsetting is usually a migration story, and the question is whether your users agree that the replacement replaces it.

The real differentiator is not measurement. Every analytics tool here measures usage accurately. It is whether you can attach names, money, and stated reasons to the usage before you act on it.

The 6 best tools to decide which features to sunset

1. Enterpret

Enterpret leads because the sunset decision is a context problem, not a counting problem. It unifies feedback from 50 or more sources and structures it with an adaptive taxonomy that learns feature-level themes from the data itself, so the theme covering the feature you are evaluating stays accurate as the product and the vocabulary around it change. The customer context graph then ties that theme to the specific accounts, segments, and revenue behind it. That turns "3% adoption" into "3% adoption, concentrated in four accounts, and here is what each of them said about it," which is a decision rather than a data point.

Best for: teams who need to know the revenue and the accounts behind a feature before they deprecate it.

2. Pendo

Pendo combines product analytics with in-app guides, which makes it strong on both halves of a sunset: identifying low usage and then running the migration messaging in-product. Its own published sunset process is one of the better public references.

Best for: teams who want to measure usage and run the in-app deprecation campaign in one tool.

3. Amplitude

Amplitude is excellent at cohort and retention analysis, which is the right lens for asking whether the users of a feature behave differently from everyone else. See product analytics tools for feature-level feedback for how this pairs with qualitative signal.

Best for: teams who want rigorous cohort analysis on the affected user base.

4. Mixpanel

Mixpanel is fast for the specific query a sunset review needs: usage frequency by segment over time, and whether the trend is decline or plateau. Straightforward to answer a narrow question quickly.

Best for: quick, segment-level usage checks without a long setup.

5. Productboard

Productboard is useful for the paper trail: which customers requested the feature, what they said they needed it for, and whether that need still exists. Deprecation arguments get easier when the original demand is documented.

Best for: teams who want the original request history attached to the decision.

6. Gainsight PX

Gainsight PX ties product usage to account health, which is the closest a usage-first tool gets to the churn question. Strongest when your CS motion is already in the Gainsight ecosystem.

Best for: CS-led organizations who need the account-health view alongside usage.

Low usage is not low value

This is the category mistake, and it is expensive in both directions.

Deprecating on adoption alone kills features that a small number of high-value accounts consider load-bearing. Keeping everything because someone might be using it is how products become unmaintainable. The mistake is not the threshold. The mistake is treating an adoption percentage as a measure of value when it is a measure of breadth.

The reframe is to stop asking how many people use this and start asking what happens to the people who do. That question has three parts, and all three are qualitative. What are they using it for? Is there a path to the replacement? Would its absence change a renewal conversation? Planio cites survey research covering more than 26,000 workers in which 49% said their organization lacked the focus or capacity to change existing processes and plans. Your customers are in that 49% too. A migration you consider trivial can be a quarter of work on their side, and they will tell you so in the feedback you already have.

The mechanism that makes this answerable is provenance. When feature-level themes are tied to accounts and revenue, the sunset review stops being a debate about thresholds and becomes a list: these accounts, this much ARR, these stated dependencies, this replacement path. For the adjacent analysis, see prioritizing customer feedback by revenue impact and identifying segment-specific churn drivers from feedback metadata.

The cost of getting this wrong compounds. Every feature you keep out of vague fear raises the maintenance floor for the next three years. Every feature you kill without checking the account list buys you a churn conversation you did not schedule.

How to choose

If you already know a feature has low usage and need to know whether killing it is safe, that is a context question and Enterpret answers it. If you need the usage measurement itself plus in-app migration messaging, Pendo covers both. For cohort rigor on the affected users, Amplitude. For a fast segment-level check, Mixpanel. For the original request history, Productboard. For account health alongside usage, Gainsight PX.

Decision rule: never make a sunset call on a percentage. Make it on a list of accounts.

FAQ

What usage threshold means a feature should be sunset?

Common heuristics start around 5% adoption and usage less than monthly, but the threshold is a screening tool, not a decision. It tells you which features to investigate. The investigation is about who the remaining users are and what they would lose.

How do you know if low usage means low value or poor discoverability?

You cannot know from usage data alone, which is the core limitation. The signal is in the language: if customers describe wanting the capability while not using the feature that provides it, you have a discoverability or usability problem, not a demand problem. Support tickets and onboarding conversations are the highest-yield places to look.

How does Enterpret help with sunset decisions?

Enterpret's adaptive taxonomy builds feature-level themes from your actual feedback without manual tagging, so the theme covering a feature stays accurate as your product and your customers' vocabulary change. Its customer context graph attaches the accounts, segments, and revenue behind each theme, so you can see exactly who depends on a feature and what that dependency is worth before you deprecate it.

Should you tell customers before or after you decide?

Decide internally with the account list in front of you, then communicate before you act, with a timeline and a replacement path. The public deprecation notices that go well name the reason, the date, and the alternative. The ones that go badly are announcements without a migration.

What is the biggest mistake teams make when sunsetting a feature?

Underestimating the switching cost they are imposing. A feature that is trivial for you to remove can be a quarter of work for a customer to migrate off. That asymmetry, not the removal itself, is what turns a cleanup into an escalation.

Before you sunset anything, get the account list. See how Enterpret ties feature-level feedback to the revenue behind it.

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