Understanding User Visits & Content Engagement in Your Vanilla Community

Shauna

Hiya Vanilla Community! 👋

As a community manager, it’s natural to want deeper insight into who is using your community, what they’re reading, and which resources are resonating. Vanilla’s Analytics tools give you several ways to explore visitor trends, article engagement, and content consumption — all without needing custom development.

Below are a few practical ways to pull this information directly from your dashboard, plus options for exporting the data if you’d like to do deeper analysis.

Tracking User Visits (Who is visiting your community and how often?)

You can see which members are visiting your community — and how often — by creating a table chart.

How to build the chart

1. Create a new chart → Table
2. Data Source: Page Views
3. Group By: User Name
4. Function: Count
   → This shows the total number of visits per user (not just unique pages).
5. Add filters:
   • User Name → Exists = true
   • User Name → Not equal to @guest
     (to exclude anonymous guest traffic)

Notes:

This chart typically has a TON of data, so to make it run faster when I'm creating it I tend to set the time frame to around a day or two so that it doesn't slow down the chart creation then I set it to longer timeframes after creation.

Depending on your community’s anonymization settings, users who have chosen to anonymize their data will not appear in these results.
More info: https://success.vanillaforums.com/kb/articles/1483-anonymizing-analytics-data

What Pages or Articles are Users Viewing?

There are two helpful ways to explore this information depending on your goals.

Option 1 — View activity for a single user (least technical)

If you want to understand what a specific member has looked at, simply click "Check Analytics Data" for a single user:

You’ll see a detailed list of pages/articles that the member viewed within your selected timeframe — something like this:

This works well if you only need insights for a handful of users at a time or are scoping out a customer before a call ;)

Option 2 — Build a chart to see article views or user behavior (flexible, more data-heavy)

You can also create charts based on Page Views, then use filters depending on what you want:

Scenario A — See all users who viewed a specific article

1. Data Source: Page Views
2. Group By: User Name
3. Function: Count (note that it defaults to Count Unique, I like to use Count here)
4. Filter: Article Name = (choose an article)

This gives you a list of all users who viewed that article.

Once you save that chart, you can also pull a CSV of the data:

Scenario B — See all articles viewed by a specific user

1. Data Source: Page Views
2. Group By: Article Name
3. Function: Count (again not count Unique)
4. Filter: User Name = (choose a user)

This returns everything they viewed, and how many times.

I also added a filter of article name exists, otherwise it will return an 'other' to account for the users views of community posts, the homepage, etc.

You could do the same thing for community posts:

Note the other at the top, this is everything that doesn't have a post name (like articles, homepage, etc)

MOREEEE DATA! — Exporting Data (CSV or API)

Which way should you pull data?

You've got several options here:

• Creating interactive charts → least technical
  • This is what we've talked about above
• Exporting the chart as CSV and analyzing in Excel → medium technical
  • This is where you would pull a CSV after doing the above
• Pulling the data using the Analytics API → very technical
  • This is much more technical and typically requires a data dev

All methods are supported — pick the one that fits your comfort level and gets you the info that you need.

For customers who want to build dashboards outside Vanilla or run your own analysis:

CSV Export (medium technical)

Every chart can be exported as a CSV.
You can then filter, pivot, or calculate trends such as:

• Day-over-day engagement
• Week-over-week growth
• Month-over-month comparisons

Analytics API (very technical)

If you require more advanced data access, event-level details are also available through the Analytics API:

➡️ https://success.vanillaforums.com/kb/articles/43-analytics-api

This allows developers to fetch raw analytics output for custom reporting.

A note on getting deeper into the 'who' question

Note: Email addresses are not included in analytics data.

If you need to pair usernames with user emails, export your User List separately and join the data offline using a user export.

Final Tips

• Start with short time periods when exploring large datasets
• Exclude guest traffic when analyzing member behavior
• Remember that anonymized users will not appear in analytics
• Choose the level of technical depth that fits your team:
  • Charts → easiest
  • CSV → flexible
  • API → most advanced

If you have questions about building any of these charts, feel free to post in the Success Community — we’re here to help!

Rav Singh

Thanks for sharing this @Shauna

I'm definitely going to use this to create charts for our customer feedback/feature recap posts 🙂