How to Build a Power User Analysis in Amplitude
Power users are the small group of customers who get the most value from your product. They use it daily, they adopt new features first, and they are the most likely to expand and refer others. Understanding what makes them different — what they do, how they discovered key features, and what their journey looked like — gives you a playbook for turning regular users into power users.
Amplitude's behavioral analysis tools let you define power users by actual behavior rather than self-reported satisfaction, then work backward to find the patterns that predict power user status. This guide walks through defining your power user criteria, profiling their behavior, and building the analysis that informs product strategy.
Step-by-step guide
Define your power user criteria using behavioral thresholds
Power users are defined by what they do, not who they say they are. Start by analyzing the distribution of a core engagement metric — daily or weekly frequency of a key action. In Amplitude, create an Insights chart showing the distribution of event counts per user for your core action (e.g., files created, searches performed, reports generated). Look for a natural breakpoint where a small group performs significantly more actions than the median user. This breakpoint defines your power user threshold.
- Choose the core action that represents value delivery in your product
- Create a histogram of action frequency per user over the last 30 days
- Identify the threshold (e.g., top 10% by frequency or users performing >5 actions/week)
Create a power user behavioral cohort in Amplitude
Navigate to Cohorts > New Cohort and define it using the criteria you identified. For example, users who performed core action 5 or more times in the last 7 days. Save this cohort with a clear name like Power Users - Weekly Active 5+. This cohort becomes the lens through which you analyze every behavioral question. Amplitude keeps it dynamically updated as users enter and exit the threshold.
Analyze feature adoption patterns of power users
Create an Insights chart showing the top 10 events performed by the Power Users cohort versus all other users. Look for features that power users use significantly more than regular users. If power users use an advanced search feature 8x more often than average users, that feature might be a key driver of power user status. These features are candidates for better discoverability and onboarding.
Map the power user activation journey
Create a Pathfinder analysis in Amplitude starting from the signup event, filtered to users who later became power users. Compare it with the pathfinder for users who never reached power user status. Look for divergence points — actions that power users take early that others do not. Common findings include completing a specific onboarding step, connecting an integration, or creating their first complex artifact within the first 3 days.
- Run Pathfinder for the power user cohort from signup forward
- Run the same analysis for non-power users
- Identify the 2-3 actions where the paths diverge most significantly
Build a power user scorecard dashboard
Create an Amplitude Board with four key charts: power user count over time (is the segment growing?), feature adoption comparison (what do power users do differently?), time to power user status (how long does it take?), and retention comparison (do power users retain better?). This dashboard is your ongoing health metric for engagement depth. Review it monthly to track whether product changes are growing or shrinking the power user segment.
Create experiments targeting power user conversion
Based on the behavioral predictors you identified, design experiments that nudge regular users toward power user behaviors. If connecting an integration predicts power user status, build a more prominent integration setup prompt. Use Amplitude's Experiment feature or Insights to measure whether the intervention increases the percentage of users crossing the power user threshold. This closes the loop from analysis to action.
Common mistakes
Defining power users by revenue instead of behavior
Enterprise customers on expensive plans are not necessarily power users — they might be on auto-renewal without active engagement. Define power users by behavioral frequency and depth. Revenue is an outcome; behavior is the driver you can influence through product changes.
Setting the power user threshold too low
If 40% of your users qualify as power users, the threshold is too low to be meaningful. Power users should be a distinct minority (typically 5-15% of active users) whose behavior is qualitatively different from the majority. A threshold that includes most users washes out the behavioral signals.
Analyzing power users without comparing to non-power users
Knowing that power users use advanced search 20 times a week is interesting but not actionable alone. The insight comes from the comparison: power users use advanced search 20x/week while regular users use it 0.5x/week. Always compare the two groups to identify meaningful behavioral differences.
Tips
Track the power user percentage as a north star metric — the percentage of MAUs who meet your power user criteria. This single number captures engagement depth across the entire product.
Use Amplitude's Compass feature to automatically identify behaviors that correlate with power user status, saving you from testing hypotheses manually.
Segment your power user cohort by persona or use case to find multiple paths to power user status — enterprise power users might look very different from SMB power users.
Set up an Amplitude alert for when the power user percentage drops below a threshold so you catch engagement declines early.
How Vantage helps
Vantage pulls analytics insights into the product planning workflow. When you are defining features to grow your power user segment, Vantage can incorporate your Amplitude power user analysis as context during PRD generation, ensuring requirements are designed to drive the specific behaviors that predict deep engagement.