---
title: "Features - conversion points _ KPIs"
slug: "features-conversion-points-kpis"
updated: 2023-01-03T08:00:44Z
published: 2023-01-03T08:00:44Z
canonical: "knowledgebase.copilot.cx/features-conversion-points-kpis"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://knowledgebase.copilot.cx/llms.txt
> Use this file to discover all available pages before exploring further.

# Features: conversion points and KPIs

When analyzing the success of your features, there are two things you need to think about:

1. Feature adoption – the number of users who use a feature properly for the first time
2. Feature usage – the frequency with which a feature is used

To help make sense of adoption and usage across all your features, it's important to use a consistent set of conversion points and key performance indicators (KPIs). You can then study features individually, as a whole, and in comparison with each other.

In this context, feature usage can also mean a specific way of using a feature. After all, if you were looking for patterns in a user's diet, "ate broccoli" would be different to "ate chips". So the type of feature usage you're looking to improve should be evaluated here too.

## Conversion points

##### Feature viewed

The user viewed the feature and is aware of it.

##### Feature used

The user has used the feature.

##### Feature used X times

The user has used the feature X times.

##### Feature used X times in Y duration

The user has used the feature X times in a day, week, month, or other time frame.

##### Comparisons

Track all the conversion points above to see how usage compares for each of your features.

## Key performance indicators (KPIs)

##### Feature usage %

% of active users who used a feature.

##### Total feature usage %

% of active users who use at least X of the main features.

##### Superuser benchmark

% of active users who use more than X features.

##### Feature usage amount

% of active users who used a feature more than X times.

##### Feature usage pattern

% of active users who use the feature more than X times in Y duration.