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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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In the competitive SaaS landscape, building innovative features isn't enough—ensuring customers actually use them is what drives retention, growth, and ROI. Feature usage rate has emerged as a key performance indicator that helps product teams understand which investments are paying off and which features might need reconsideration. This metric provides critical insight into how customers interact with your product and can dramatically influence your product roadmap decisions.
What is Feature Usage Rate?
Feature usage rate measures the percentage of your user base that engages with a specific feature within your product during a defined time period. This straightforward but powerful metric helps product teams understand which elements of their software are providing value to customers.
The core formula is:
Feature Usage Rate = (Number of Users Who Used the Feature / Total Number of Users) × 100%
For example, if you have 10,000 users and 3,500 of them used your reporting dashboard in the last month, your feature usage rate for that feature would be 35%.
Why Feature Usage Rate Matters for SaaS Executives
1. Resource Allocation Validation
According to a study by Pendo, approximately 80% of features in the average software product are rarely or never used. This represents significant wasted development resources. By tracking feature usage rates, you can validate whether your engineering investments align with actual customer behavior, helping to optimize future development budgets.
2. Revenue Impact Assessment
High-value features that drive subscription upgrades or prevent churn deserve special attention. McKinsey research indicates that companies that effectively link product usage to revenue growth outperform their peers by 20-30% in revenue. Feature usage rates help you identify which capabilities directly influence your bottom line.
3. Customer Success Insights
Low usage rates for key features often indicate onboarding gaps or user experience issues. According to Gainsight, customer success teams that focus on improving adoption of core features see a 10-15% improvement in overall retention rates.
4. Product Roadmap Prioritization
Understanding which features resonate with users provides essential data for product roadmap decisions. Rather than building based on assumptions, feature usage data allows for evidence-based prioritization.
5. Competitive Differentiation
Features that see high adoption may represent your product's unique value proposition. According to OpenView Partners' Product Benchmarks report, features with usage rates above 60% often represent a product's most defendable competitive advantages.
How to Effectively Measure Feature Usage Rate
Define Clear Measurement Parameters
Before implementing tracking, establish:
- Time period: Are you measuring daily, weekly, or monthly usage?
- User segment definition: Are you looking at all users or specific cohorts?
- Feature interaction thresholds: What constitutes "usage"? A single click or deeper engagement?
Implement Proper Instrumentation
To accurately measure feature usage, you'll need:
- Event tracking: Implement analytics that capture when users interact with specific features
- User identification: Ensure proper user ID tracking to link actions to specific accounts
- Segmentation capabilities: The ability to filter by user types, plan levels, or other relevant factors
Product analytics platforms like Amplitude, Mixpanel, or Pendo can automate much of this process.
Establish Benchmarks and Goals
Feature usage benchmarking creates context for your measurements:
- Internal benchmarks: Compare features against each other
- Historical trends: Track usage changes over time
- Industry standards: When available, compare your rates to industry averages
According to ProductLed's 2023 Benchmark Report, successful B2B SaaS products typically see core feature adoption rates of 70%+ among monthly active users.
Categorize Features by Expected Usage Patterns
Not all features should be measured the same way:
- Core features: Essential functionality that should see high, regular usage (e.g., communication tools in Slack)
- Situational features: Tools used only in specific contexts (e.g., export functionality)
- Power user features: Advanced capabilities expected to be used by a smaller segment
Correlate With Other Metrics
Feature usage rates become more meaningful when coupled with other data points:
- Retention rates: Do users of specific features retain better?
- Expansion revenue: Do users of certain features upgrade more frequently?
- NPS scores: Do users of particular features report higher satisfaction?
Turning Feature Usage Data Into Strategic Action
Low Usage Features
When a feature shows persistently low usage:
- Assess visibility: Is the feature discoverable? A UserTesting study found that 60% of low-usage features suffer primarily from poor discoverability.
- Evaluate onboarding: Are users being properly introduced to the feature?
- Consider UX improvements: Is the feature intuitive to use?
- Gather qualitative feedback: Directly ask users why they aren't using the feature
- Make tough decisions: If usage remains low despite interventions, consider deprecating the feature
High Usage Features
For features with strong adoption:
- Invest in enhancements: Build on success with additional capabilities
- Highlight in marketing: Showcase these features in acquisition efforts
- Learn transferable insights: Identify what makes these features successful
- Consider premium tiers: Evaluate if these high-value features could drive upsells
Conclusion
Feature usage rate is far more than a vanity metric—it's a window into how your customers derive value from your product. By systematically tracking and analyzing these rates, SaaS executives can make more informed decisions about development resources, marketing messaging, and strategic direction.
In an environment where engineering resources are precious and customer expectations are constantly evolving, feature usage data provides the empirical foundation needed for product-led growth. Organizations that establish robust feature tracking systems gain a significant competitive advantage through more efficient development cycles and stronger customer engagement.
For SaaS executives looking to improve product performance, implementing comprehensive feature usage tracking should be considered a non-negotiable practice in today's data-driven landscape.