Cohort Analysis
Group users by when they started and watch how each group behaves over time.
What it adds
A retention grid that buckets users by a qualifying moment and tracks what each bucket does in the periods that follow.
What your agent is told to do
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What your agent is told to do
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Define the qualifying event that puts a user in a cohort, and freeze their membership at that moment. A cohort that re-sorts itself as users change is not a cohort.
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Support both calendar buckets (users who signed up in March) and rolling buckets (day 0, day 7, day 30 relative to each user's own start).
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Render the result as a triangular grid: cohorts down, periods across, with each cell showing both the count and the rate.
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Read from the app's existing event stream. Event capture is owned by Event Tracking — extend that rather than instrumenting a second pipeline.
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Do NOT restate ordered step-conversion logic here; that belongs to Funnel Analytics. This feature is about time, not sequence.
Edge cases it handles
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Edge cases it handles
6- A user who qualifies twice must be handled by a stated rule — first qualification only, or a separate row per qualification. Silently double-counting inflates every cell.
- The most recent cohort has not lived through a full period. Mark partial periods rather than plotting them as a collapse in retention.
- Late-arriving events change historical cells. Decide whether cells are recomputed or frozen, and say which on the page.
- Calendar buckets need a stated time zone. UTC and the viewer's local zone put the same user in different months.
- A cohort with a handful of users produces meaningless percentages. Suppress or flag rates below a minimum cohort size.
- Deleted or merged accounts must not silently shrink historical cohorts — retention would appear to improve.
Definition of done
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Definition of done
8- Cohort membership is fixed at the qualifying moment and does not change retroactively.
- Both calendar and rolling bucketing are available and clearly labelled.
- Users who qualify more than once are handled by a documented rule.
- Partial and incomplete periods are visibly marked, not plotted as data.
- Small cohorts are flagged or suppressed rather than shown as noisy percentages.
- The bucketing time zone is stated on the report.
- The feature matches the existing design system.
- No existing functionality is broken.
Related features
UI Event Naming Schema
UI Event Naming Schema
Give every tracked interaction a name that still means the same thing in a year.
What it does
A documented vocabulary and structure for event names and properties, applied across the app's existing tracking.
How it works
- 1 Audit the events the app already sends and list them. The duplicates, the near-synonyms, and the ones nobody can explain are the reason the schema is needed, and they are also the migration list.
- 2 Fix a structure of object, action, and context: what was acted on, what happened to it, and where. Fix a closed set of actions — viewed, clicked, opened, submitted, selected, failed — and require every new event to reuse one of them.
- 3 Keep variable detail in properties, never in the name. A record identifier, a plan name, or a workspace slug baked into an event name produces thousands of unaggregatable one-off events.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/ui-event-naming-schema
Data Table Cell Primitives
Data Table Cell Primitives
Render every kind of table cell the same way, wherever the table happens to be.
What it does
A shared set of cell renderers for numbers, dates, people, statuses, links, and row actions, used by every table in the app.
How it works
- 1 Catalogue the cell types the app's tables already render and reduce them to a small set: number and currency, date and relative time, person or avatar, status or badge, link or identifier, and an actions cell.
- 2 Separate each cell's underlying value from its presentation, so sorting, filtering, grouping, and export operate on the raw value while the user sees the formatted one.
- 3 Align and format numerically consistent cells the same way everywhere — figures right-aligned with tabular figures and a fixed precision per column, dates in the user's locale and time zone, currency with its code where more than one is possible.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/data-table-cell-primitives
Segment Event Forwarding
Segment Event Forwarding
Send one clean stream of product events to Segment and let it fan out downstream.
What it does
A documented event schema and a single forwarding path emitting track, identify, group, and page calls with consistent identity.
How it works
- 1 Write the event schema before writing any code: the exact set of event names, the properties each carries with their types, and the traits attached to a user and to an account. Every downstream tool inherits this schema, so a name chosen carelessly is expensive to change later.
- 2 Establish one identity model and apply it everywhere. Use a stable internal user identifier that never changes, associate the anonymous identifier from the first visit with it at signup, and attach the account or workspace so downstream tools can roll events up by customer.
- 3 Route every event through one internal emitter rather than calling the provider from feature code. That emitter validates the event against the schema, drops or flags anything unrecognised, and is the single place where identity and default properties are attached.
Copy the prompt
No account needed
Add this feature to my app:
https://addthisfeature.com/x/segment-event-forwarding
How it works
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1
Copy the link
Grab the Markdown instruction URL for this feature.
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Give it to your AI
Paste it into Claude Code, Cursor, v0, Lovable — whatever you build with.
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It inspects, then implements
Your agent reads your existing app first, then adds the feature to fit it.
Works with your stack
These instructions are written to adapt. They tell the agent to detect your framework, match your existing design system, and reuse what you already have — rather than assuming a particular stack.
Need it tighter than that? Customize the feature and tell it exactly what you're running.