User Analytics Examples - Inspiration & Best Practices

User analytics give you deep insight into how people use your product or website. By tracking and analysing user behaviour, you can identify bottlenecks in the user experience, improve conversions, and make data-driven decisions about product development. Modern analytics tools go beyond simple pageviews: they offer funnel analysis, cohort analysis, heatmaps, and predictive models. In these examples, we show how organisations deploy user analytics to improve their product and revenue.

Product usage analytics for a SaaS platform

A SaaS company implemented comprehensive product usage analytics to understand which features are most used and where users drop off. Through event tracking on every interaction, feature adoption rates, time-to-value, and session duration per user segment are measured. The product team uses this data to determine roadmap priorities and identifies underused features to consider for removal or redesign.

• Event-based tracking of every user interaction in the product
• Feature adoption rates and time-to-value per user segment
• Automatic identification of underused features
• Data-driven roadmap prioritisation based on usage data

Conversion funnel analysis for an e-commerce platform

An e-commerce platform built an advanced funnel analysis tool that visualises the complete customer journey from landing page to purchase. Per step, the dropoff percentage is calculated and the reasons for abandonment are analysed. A/B tests on funnel steps are automatically evaluated for statistical significance. Thanks to these analyses, the overall conversion rate has increased by 34% in six months.

• Visual funnel visualisation from landing to purchase with dropoff rates
• Funnel segmentation by traffic source, device, and user cohort
• Integrated A/B testing with automatic significance calculation
• Attribution modelling for multi-touch customer journeys

Cohort analysis for a subscription service

A subscription service implemented cohort analysis to understand retention patterns. Users are grouped by their registration date and their activity is tracked over time. The system automatically identifies which onboarding actions correlate with higher retention at 30, 60, and 90 days. These insights led to a redesign of the onboarding flow that improved 90-day retention by 22%.

• Cohort grouping by registration date, acquisition channel, and plan
• Retention curves with automatic trend detection and comparison
• Correlation analysis between onboarding actions and long-term retention
• Churn prediction based on usage patterns and engagement signals

Customer health scoring for a B2B SaaS platform

A B2B SaaS platform built a customer health scoring system that automatically assesses how healthy each client relationship is. The health score combines product usage, support ticket frequency, NPS scores, and contract information into a single indicator. Accounts with a declining health score are automatically flagged so the customer success team proactively reaches out before the client considers cancelling.

• Composite health score from product usage, support, and NPS data
• Automatic flagging for declining health scores
• Proactive customer success interventions based on data
• Integration with CRM for complete customer context

Key takeaways

• Event-based analytics provide more detailed insight than traditional pageview tracking.
• Funnel analysis identifies exactly where users drop off and provides concrete improvement opportunities.
• Cohort analysis reveals retention patterns that remain hidden in aggregated statistics.
• Customer health scoring enables teams to proactively prevent churn instead of reacting after the fact.
• Privacy by design is essential: analytics must comply with GDPR requirements with consent management.

How MG Software can help

MG Software builds custom analytics solutions that give you deep insight into your user behaviour. From event tracking infrastructure to custom dashboards with funnel analysis, cohort analysis, and health scoring — we develop the analytics you need to make data-driven decisions and continuously improve your product.