4 ways customer analytics software can help you build better products

Customer analytics software is a platform that collects and analyzes user behavior data to help product teams make data-driven decisions. These tools track how customers interact with your product, revealing patterns that guide feature development and user experience improvements.

You can't build a great product without understanding your users. Customer analytics software bridges that gap by transforming raw user data into actionable insights.

With the right platform, you can:

• Map customer journeys to identify friction points.
• Run cohort analysis to understand user segments.
• Measure feature impact through behavioral tracking.
• Act on insights to improve product outcomes.

Here are four proven ways customer analytics software helps you build better products:

What is customer analytics software?

Customer analytics software turns raw user data into clear insights. It helps you understand how people use your product, what they like, and where they get stuck. Instead of just seeing page views, you can track the specific actions users take—from their first click to their hundredth. This gives you a complete picture of the customer journey, so you can answer the 'why' behind what users do.

What to look for in customer analytics software

The right customer analytics software does more than just show you data. It helps you take action. Look for a platform that lets you:

• Track events: Go beyond page views to see every click, swipe, and interaction.
• Segment users: Group customers by their behavior to find what makes your power users tick.
• Analyze funnels: See exactly where users drop off in key workflows.
• Measure retention: Understand what keeps customers coming back.
• Integrate with your stack: Connect your data across all the tools you use.

A complete platform gives you a single source of truth for your customer data.

1. Behavioral cohort creation

Behavioral cohort creation groups users based on specific actions they take in your product. This segmentation reveals patterns that distinguish high-value customers from casual users.

Customer analytics software enables you to:

• Identify key behaviors that correlate with conversion.
• Compare user segments against your broader user base.
• Find common patterns among your most valuable customers.
• Nudge other users toward these high-value actions.

Meditation app Calm used behavior cohort analysis to triple their user retention. The company realized that the 1% of users who were using their daily reminder feature were highly engaged. But they weren't sure whether setting reminders was a sign of a power user or whether setting reminders turned customers into power users.

Calm used behavior cohort analysis to find a feature that tripled user retention. To investigate, the product team ran an experiment that made the daily reminder feature more obvious to a subset of new users. The result: Calm found that the new users who set daily reminders became highly engaged as well. They made the feature more prominent for all users in order to encourage more people to set the daily reminders.

2. Retention improvement

Retention improvement focuses on keeping users engaged with your product over time. Customer analytics software helps you identify and optimize two key retention components:

Critical event: The most important action users must take to find value in your product.

• Must align with business goals and customer value.
• Can be single or repeated actions.
• Example: A music app might track song purchases, not just account creation.

Usage interval: The timeframe users should complete the critical event.

• Defines when users should act to remain engaged.
• Varies by product type and user behavior patterns.

[Related: 6 Worksheets to Understand, Improve, and Calculate Retention Rate]

Anything you can do to nudge people toward the critical event within your ideal timeframe will help boost your retention rate and reduce churn. But knowing what is causing people to give up before that critical event requires analysis.

Using customer analytics software, you can look at the steps users take leading up to that critical event and see what is keeping them from progressing through the funnel.

ABA English used funnel analysis and behavioral cohorts to understand why users were falling off shortly after subscribing to their language academy. With the goal of users successfully completing a course and renewing their subscription, the ABA English team dug into why their users were abandoning the platform in their first subscription period.

In looking at the data, they found the issue in their onboarding process. Users often signed up for course levels that didn't match their experience, which caused frustration. The ABA English product team revamped the onboarding process to include a Level Test, so users were able to pick the right course for their needs.

ABA English introduced a Level Test into their onboarding process and increased retention.
The ABA English team used funnel analysis to inform a product change, but they didn't stop there. They created a retention chart in Amplitude to validate that the new onboarding flow led to a positive impact. The retention chart proved that by removing hurdles in the onboarding process, ABA English doubled the percentage of users who completed their first study unit—a key indicator for long-term retention.

3. Engagement growth

Engagement growth extends beyond initial onboarding to create lasting user value. Customer analytics software helps you maintain user interest through continuous optimization.

The process involves:

• Identifying key milestones that indicate high user engagement.
• Analyzing behavior patterns of your most active users.
• Tracking action frequency to understand engagement depth.
• Guiding other users toward these high-value behaviors.

This data-driven approach ensures your product stays relevant and valuable as user needs evolve.

Microsoft used multiple rounds of A/B testing to perfect their engagement strategy and quadruple the time spent in their product. After launching a new family of products within Office360, Microsoft found varying levels of engagement with these tools. To encourage high engagement across the board, the company tested feature changes that made it easier to complete tasks that Microsoft knew increased retention, such as scheduling time on their calendar for focused work.

4. New feature development

New feature development uses customer analytics data to identify and validate product improvements before full implementation. This approach reduces development risk and ensures features meet actual user needs.

Customer analytics software supports feature development by:

• Analyzing user behavior patterns to spot unmet needs.
• Tracking site searches to understand user intent.
• Monitoring customization attempts to identify desired functionality.
• Testing feature concepts with targeted user segments before launch.

This data-driven approach combines quantitative behavior data with qualitative feedback to guide strategic product decisions.

Financial ecosystem Dave used product analytics to identify a new offering. The company knew that their most valuable customers were those who took an advance to avoid overdraft fees. The product team suspected that this group might also be interested in a new checking account offering.

To verify this idea, the team showed these users a preview of the potential new product to gauge interest. Dave found that 50% of the users who were shown the preview were also excited about a new checking product.

The company ran more tests to determine possible features of this checking product, such as increased maximum paycheck advance and no overdraft fees. One feature was preferred 2.5x over the others. With this insight, the Dave team could build the checking product from an informed, data-backed perspective.

Transform your product development with customer analytics

Customer analytics software transforms product development from guesswork into strategic decision making. By understanding exactly how users interact with your product, you can build experiences that drive engagement, retention, and growth.

The four approaches covered—behavioral cohorts, retention improvement, engagement growth, and feature development—work together to create a comprehensive understanding of your users. This data-driven foundation enables you to build products customers value and return to consistently.

Ready to transform your product development process? Try Amplitude for free today and discover how customer analytics can help you build better products.