Analyse user behaviour with User IDs

User ID tracking in Matomo links visits, actions, and conversions to a single identifier so you can recognise the same user across sessions, devices, and browsers. User ID tracking requires you to assign a persistent unique identifier when the user logs in. This is implemented using _paq.push(['setUserId', userId]); before trackPageView in the Matomo JavaScript code.

Alternatively, use Matomo Tag Manager, the WordPress plugin, or one of the Matomo SDKs to implement User ID tracking. Once configured and data is collected, you can look at each stage of the journey to see how users progress from their first interaction to conversion, identify patterns, and detect points where engagement drops. The following sections outline how to use Matomo reports to compare and optimise user journeys with User IDs in Matomo.

Understanding User Types

Before analysing the stages of a logged-in user’s journey, it helps to define how you group users in your reports. A User Type is a label that categorises users into meaningful groups such as customer tier, subscription plan or account role. Anonymous visitors with no User ID could be a guest user type.

Use the User ID reports to compare how different user groups convert and interact with the site. You can also drill down into individual User IDs when required. Analysing behaviour by user group helps reveal patterns, friction, and opportunities that would be difficult to spot when viewing users as one large, unsegmented audience.

1. Entry points and first interactions

Logged-in users are first tracked when they subscribe or log in. This is the point when Matomo links activity to a User ID. When a user begins their visit anonymously and then logs in or subscribes during the session, Matomo retroactively attributes the entire session to the User ID.

Use the following reports and features to understand how and where visitors are first identified and highlight referrers and pages that bring more subscribing users.

• Create Custom Dimensions to apply attributes to logged-in users like customer tier, pricing plan, or role to analyse engagement trends across grouped user types.
• Create a Segment to filter by logged-in users (or User Types) and view the Matomo reports.
• Open Behaviour > Entry Pages to identify the landing areas with the most entrances and high bounce rates. These pages either encourage users to continue exploring or they cause early exits.
  
• View the Acquisition > All Channels and Campaigns reports to see what drove the first visit of a session. For configured campaigns, you can analyse how effective they were certain for user types.
• The Visitors > Visitor Log and Visitor Profile reports provide a timeline of all sessions for a given User ID and how they first arrived and what their early interactions looked like. Export the full Visit Log from Matomo and combine it with other internal datasets for in-depth reporting.

2. Content and event interactions

To understand what keeps logged-in users engaged between entry and exit, it helps to examine the viewed pages and content, triggered events, and downloaded files. This can uncover what content signals the most interest or supports conversions across sessions.

With the logged-in user segment selected, use the Behaviour reports to understand how users navigate and engage with your site:

• Pages – provides page analytics that highlight strong and problematic areas where content can be further promoted or refined.
• Events / Downloads – events or downloads frequently triggered can indicate strong engagement and it can show resources with low engagement that can be refined or placed for better visibility.
• Site Search – if many of your logged-in users search for something that’s not obviously accessible, revise your site structure or identify missing content.
• Engagement – provides a high-level, aggregated view of how logged-in users interact during their visits and summarises key metrics. You can monitor how returning visits change over time and respond to shifts in user engagement.
• Users Flow – displays a graphic visualisation of the most common paths taken by users as they navigate through your site. Modify the visual by removing or adding interactions for different stage analysis.
• Transitions – illustrates how users arrive on a specific page and where they go next or if they exit after certain content, or display looped behaviour between specific pages. This report can support design changes to optimise your website’s navigation and content visibility.
  

3. Purchase or conversion points

The conversion stage is when a user completes a defined goal, such as submitting a form, completing a purchase, or signing up. By reviewing these points, you can determine what behaviours occur before a conversion, how many sessions it takes to convert, and whether specific content or interactions contributed to the goal completion. Analyse the following reports for insights into conversions:

• The Visitors > User IDs is a high-level view of logged-in users’ activities showing the total number of visits and actions by each user and the number of visits with goal conversions. Refer to the guide on Analyse User ID Reports.
• Create a Segment to filter by logged-in users and view the Matomo reports.
• Open the Ecommerce > Overview and Sales reports to track purchases with User IDs. You can then take action if sales activity declines or build on the product pages that consistently perform well.
  
• The Goals > Overview report provides a summary of completed goals compared with the previous period for logged-in users. If the conversion rate drops, further analysis with other reports can determine the areas of the site that need improvement.
• Create a Custom Report using User ID and Referrer Name as a dimension with metrics like last days since visit, total conversions per user and specific goals completed or products purchased. It can help find the touchpoints that most often lead to action.

4. Exit pages and return visits

When User IDs are available, exit behaviour and return visits can be analysed at an aggregated level. This helps you understand how identified user groups end their sessions, how often they return, and which parts of the site have low impact or influence long-term engagement.

• Create a Segment for returning visits by users with a User ID (or User Type).
  
• Open the Behaviour > Exit Pages report to see where users often end their sessions. This identifies pages that are natural endpoints as well as pages that cause premature drop-off. By comparing common exit pages with return-visit trends, you can identify exit patterns that correlate with higher user return rates.
• Create a Custom Report that uses User Type as the primary dimension and a secondary dimension such as a page category, action type, or landing page category to compare with entry patterns. Include metrics for meaningful differences between user types, for example: number of sessions, exit rate, return visits, and average actions per session.
• Compare Goal or Ecommerce data to see whether exits commonly occur after successful actions or before important milestones.
• Use Funnels to identify where to strengthen journeys and reduce early drop-offs for ongoing engagement.

5. Putting it all together

Each of the stages above offers insight into how users interact with your site where they come from, what captures their attention, what prompts them to convert, and when they disengage. By using User IDs with User Types, you can trace full user journeys across sessions to improve retention and understand long-term engagement, not just one-off visits.

All standard and custom reports in Matomo can be exported into multiple formats, including CSV, TSV, XML, JSON, and HTML. These exports can be downloaded directly or accessed via API for integration into BI tools, dashboards, or data pipelines. Learn more about exporting Matomo data.