How to analyze Page Comparator data

Let's discuss Page Comparator metrics as if your site were a physical retail shop: 

• Number of views - number of times people walking on the street saw your window display total.
• Bounce rate - number of people who stopped at your window display but left without coming in.
• Number of visits - number of people who came into your shop.
• Scroll rate - number of items that shoppers looked at.
• Time spent - time shoppers spent looking at an item.
• Activity rate - number of times shoppers checked the price or tried an item on. 

Understanding a page by comparing its metrics

Ask and answer these three key questions (and their sub-questions) to assess and understand what happens in your "shop" using Page Comparator. 

Using page metrics, you can also identify whether it provokes a different behavior when it is viewed as the landing page of a visit, or during a visit: is its Bounce rate higher than its Exit rate? 

These questions give you pointers – hypotheses to uncover positive and/or negative anomalies which you then need to compare with other pages on your site.

Understanding a page by comparing it to others

When you have identified a page in the Journey analysis module and analyzed it in-depth in the Page comparator module, you need to weigh your analysis of the page against all pages on your site: "my page is viewed a lot, but it is, on average, viewed as much as my home page, my list page, and my sales page."

Take your analysis further by supplementing these questions with an understanding of your page relative to others: attractiveness, engagement, and performance.

An anomaly exists when a difference is significant enough relative to its environment!

Understanding a page according to different users and period 

When you have identified one or more positive and/or negative anomalies, you can extend your analysis to different periods and segments.

It's important to understand the source of anomalies, and your users, before beginning an analysis of the elements on the page:

• Are they caused by one or more particular user(s)?
• Are they repeated over time or do they occur sporadically?
• Are the anomalies the same?

Once you have asked (and answered) these questions, you will have identified your pages' strengths and weaknesses. You now have the key data (periods, segments, anomalies and hypotheses) you need to continue your analysis of elements on your page using Zoning Analysis and then Session Replay.