Feature Tracking

Map events to product features and measure adoption — auto-discovered and built for scale.

A feature maps one or more events to a meaningful part of your product, so you can measure adoption — how many of your active users actually use it.

Feature	Adoption (% of active users)
Quote builder	72%
Invoicing	48%
Deals pipeline	35%
Reports	19%

_{Sample adoption across a rolling window.}

Auto-discovered

Like the events catalog, features surface from the data — define a feature once and the dashboard fills it in from incoming events. A feature is a set of event specs:

{
  "name": "Quote builder",
  "events": [
    { "source": "event", "code": "time_on_screen", "filters": { "section": "quotes" } },
    { "source": "event", "code": "quote_created" }
  ]
}

How adoption is computed

Adoption %

Distinct visitors who hit any of the feature’s events ÷ active workspace visitors, in a rolling window.

Filters

Filters match event properties (e.g. section: "quotes") via JSONB containment, so one time_on_screen event can power many features.

Adoption is computed from pre-aggregated rollups (materialized views refreshed on a schedule), not by scanning raw events on each request — so the feature list loads in milliseconds no matter how many events you have.

Next steps

Event Tracking

The events that power features.

Experiments

Test changes to a feature and measure the lift.