Playbook
Use AI to understand how features are used and perform feature impact analysis post-launch.
Sources
Amplitude
Mixpanel
Posthog
Getting started
Understanding feature usage is crucial for optimizing your product and ensuring features meet user needs.
In this playbook, we'll show you how to use Merlin to understand how features get used and perform feature impact analysis post-launch.
Step 1: What you'll need
You'll need access to Lancey's Merlin agent.
Connect to your product analytics and feature flagging platforms within Lancey's integration tab.
Get access to Lancey
Step 2: Setting up filters
Once Merlin is set up, it will automatically collect data from all integrated sources. We'll leverage Lancey's ability to query, segment, and act on the data for the next steps.
Prompt
Find me the usage data for all features launched in the past 3 months.
Merlin will analyze your data set and provide a preview of feature usage.
Step 3: Analyzing data
Now that we have a list of users who activated their accounts, the next step is to analyze this data to identify key behaviours and events that lead to increased product usage.
Prompt
Analyze the feature usage data and identify the most and least used features.
Merlin will provide an analysis of the data, showing patterns and trends that can guide product improvements and future feature development.
Step 4: Targeted actions
With the insights gathered, you can now craft targeted actions to improve feature usage.
Prompt
Create a ticket to enhance the discoverability of underused features.
Merlin will now create the ticket using Jira to:
Simplify navigation to make hidden features more accessible.
Add in-app highlights and notifications for new and underused features using Intercom.
Develop brief in-app tutorials that guide users on how to use the newly discovered features.
Wrapping up
And we're all done here! Get back to building great products. We also have other playbooks you can explore.