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Weekly automated feature adoption report. AI tracks usage of every new feature, surfaces power users, and flags features that aren't catching on.

Use this templateHow automations work
Runs weeklyScheduledDelivered to Slack, Email
Feature adoption report
Active

Trigger

Runs weekly

Instructions

Generate a weekly feature adoption report.

Delivery

Slack · Email

Example output

A realistic sample of what this automation delivers — your version draws on your data.

Feature adoption reportRuns weekly · Sent to Slack, Email
Sample output
Adoption %, top features% of paying customers
Multi-sourceFaster retriesChart hoverDashboards v2SQL export
This weekPrevious week

Features shipped in the past 180 days — 11 in scope

Feature Adoption Trend Power users
Multi-source automations 38% +9 pts WoW 22
Faster chat retries 71% (auto) — n/a
Chart hover insights 24% +4 14
Dashboards v2 19% flat 8
Sleeper: SQL export 4% flat 3

Worth interviewing. Top 5 power users of multi-source automations all upgraded to Growth in the same week they hit 5+ automations. Worth a CSM hello.

Sleeper alert. SQL export hasn’t crossed 5% adoption in 12 weeks — either re-discover or quietly deprecate in Q3.

Generated by Basedash AI from your connected data sourcesProduct
The prompt

Copy, paste, customize.

Drop this into a Basedash automation. AI fills in the numbers from every source you've connected.

Instructions
Generate a weekly feature adoption report.

For each feature shipped in the past 180 days, compute:

- Unique users last 7 days
- % of weekly active users who used it at least once
- Time-to-first-use for users who signed up in the past 30 days
- Trend vs. previous 7 days

Output:

**Headline.** Number of features tracked. Net new adoption this week.

**Top movers.** Five features with biggest gains or drops.

**Power users.** Up to three users who used the most distinct features. Useful for design partner outreach.

**Sleepers.** Features with < 5% adoption that haven't grown in 4 weeks — candidates to redesign, repromote, or retire.

End with one named experiment per sleeper feature.
Data sources

Powered by these sources.

Basedash automations read across every connected source in a single run. These are the ones this template tends to use most.

Frequently asked questions

What is feature adoption?

Feature adoption is the share of users who use a given feature at least once in a defined window. Most teams track it weekly and look at adoption velocity (how fast new users discover it) alongside the absolute number.

What counts as low feature adoption?

Below 5% adoption among weekly active users — and flat for 4+ weeks — usually signals the feature isn't discovered, isn't valuable, or both. Either redesign the entry point, repromote it, or retire it.

Keep going

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