Path analysis methods in user behavior analysis are techniques used to understand the sequence of actions users take within a product, website, or application. These methods help identify common user journeys, detect friction points, and optimize user experience. Below are the main path analysis methods with explanations and examples:
Funnel analysis tracks the step-by-step progression of users toward a specific goal (e.g., purchase, sign-up). It visualizes drop-off rates between each step to identify where users abandon the process.
Example:
An e-commerce platform tracks the path: Homepage → Product Page → Cart → Checkout → Purchase. If 1,000 users visit the homepage, 500 view a product, 200 add to cart, 50 proceed to checkout, and only 10 complete the purchase, the funnel reveals high drop-offs at checkout.
Relevant Service: Tencent Cloud Web+ or Application Performance Monitoring (APM) can help track user flows and optimize conversion paths.
Sankey diagrams visualize the flow of users between different pages or actions, with the width of the flows representing the volume of users.
Example:
A SaaS platform uses a Sankey diagram to show how users navigate from Dashboard → Reports → Settings → Logout. The diagram highlights that most users exit after viewing reports, suggesting a need for better engagement post-report.
Relevant Service: Tencent Cloud DataV or Cloud Log Service (CLS) can generate interactive Sankey visualizations.
This method maps user paths as a tree structure, starting from the entry point and branching out based on subsequent actions.
Example:
A mobile app’s tree path might show: Splash Screen → Onboarding → Home → Search → Product Detail. Analyzing this helps identify whether users frequently drop off after onboarding or search.
Relevant Service: Tencent Cloud User Behavior Analytics (UBA) tools can model tree-based paths.
Markov chains model user transitions between states (pages/actions) probabilistically, helping predict the next likely step and identify critical paths.
Example:
If users often move from Login → Profile → Settings with high probability, optimizing the profile page can improve the likelihood of reaching settings.
Relevant Service: Tencent Cloud AI-Powered Analytics can apply Markov models to user flow data.
While not pure path analysis, session replays and heatmaps complement path analysis by showing real user interactions and click patterns.
Example:
A heatmap reveals that users frequently click a non-clickable element, indicating confusing UI design that disrupts the intended path.
Relevant Service: Tencent Cloud Cloud Infinite (CI) or RUM (Real User Monitoring) provides session replay and heatmap tools.
This method groups users (e.g., by signup date or source) and analyzes their paths separately to compare behaviors.
Example:
Comparing paths of organic users vs. paid ad users may show that paid users drop off earlier, indicating a need for targeted onboarding.
Relevant Service: Tencent Cloud CDP (Customer Data Platform) helps segment cohorts for path analysis.
By applying these methods, businesses can refine user journeys, reduce friction, and improve conversion rates. For scalable data processing and visualization, Tencent Cloud offers integrated solutions like EMR (Elastic MapReduce) for big data analysis and Tencent Cloud BI for dashboards.