Objective: Analyze the performance of your List page
Features used: Page Comparator, Journey Analysis, Zoning
Time: 20 min.
Set up
If you do not have the following mappings, goals, and segments already saved to your Contentsquare platform you will need to create them before getting started.
- Create a high-level mapping to ensure all your product list pages are grouped together.
- If the page templates are different depending on the type of product category, you may need to separate them out. E.g. Shoes, Women's, Men's,...
- Create a goal for Viewing the List page
- Determine what your conversion goals are for your List page and create those goals
- Ex. goals: 'View Product Page' and 'Clicked Quick Buy'
- Landed on the List page and didn’t bounce
- Landed on List page and bounced
You will also need to create two segments for each of your goals:
- one for visitors who achieve the goal, one for those who do not.
- Ex. segments: 'View Product page' and 'Did not view Product page'
Step-by-Step
1. Open Journey analysis, and apply the segment 'View List page' in the Analysis context. When using “All journeys from landing pages” you will be able to see the main way visitors are reaching the List pages and analyze the following metrics:
-
How many visitors are landing on a List page? Do they bounce straight after?
-
Navigation journeys after the List page -Do users tend to view numerous pages (less likely to exit) or just a few? How often do they return to the List pages? Are users navigating to the product pages after viewing a List page? Do they switch between Product and List pages, or do they browse through many Product pages after seeing a List page?
Analyze the retention performance of the List page
If the List pages are a key landing page that have a relatively high bounce rate, consider optimizing retention through the following analysis:
1. Open Page comparator and in a Comparison mode apply the 2 segments: 'Landed on List page and bounced' and 'Landed on the List page and didn’t bounce'. Analyze the following metrics:
- Check the time spent, activity rate, and scroll rate. Can you identify any initial signs of differences between bounce and non-bounce users? Are they spending more or less time on the page? Are they scrolling more and are actively engaging with the content?
2. Open Zoning analysis, and set your Analysis context. Toggle on Comparison mode and compare your two segments: 'Landed on List page and bounced' and 'Landed on the List page and didn’t bounce'. Analyze the following metrics:
- Check the exposure rate and float time. How did these 2 segments scroll? Are bouncers exposed to the most attractive elements on the page that generate a high click rate? Are they spending a lot of time floating over a particular element?
- Check the click rate, hover rate and the engagement rate. What did non-bouncers do? Did they engage more with your content? Are they spending time hovering over the menu or the filters, but ending up not clicking through?
- Look at their click recurrence. Are there non-clickable elements on the page, which are being clicked on multiple times? If so, how does it differ between bouncers and non-bouncers? Could some non-clickable elements be causing frustration for bouncers.
Content performance analysis
If you want to take your analysis further, consider what goal you’d like your visitors to be achieving from the List page - for example, reaching a Product page.
1. Open Page comparator, in a Comparison mode in the Analysis context, apply your 2 segments of users achieving the page goals and those who didn't (e.g., ' Viewed a Product page' and 'Did not view a Product page;). Analyze the following metrics:
- Check the time spent, activity rate, and scroll rate of users who have navigated to a Product page compared to those who did not. Are they spending more or less time on the page? If they are scrolling more and spending more time on the page, they might be looking for specific information such as reassurance, more product details, or reviews.
2. Open Zoning analysis, and set your Analysis context. Toggle on Comparison mode and compare your two segments: 'Viewed a Product page' and 'Did not view a Product page;. Analyze the following metrics:
- Compare their time spent, activity rate, and scroll rate. Which segment is scrolling more and is being more engaged with the page content?
- Check their exposure rate and the engagement rate (for Desktop)/ attractiveness rate (for Mobile) to determine if your two segments are equally exposed to the most attractive elements on the page? Is content in the right order? How exposed are the most engaged elements on the page? What elements are the most attractive? Which filter is the most attractive?
- Look at the click rate and conversion rate per click. How did the 2 segments interact with the page? Are they clicking on the sorting filters? Which filters have the highest purchase conversion rate per click?
- Look at the click recurrence and hesitation time (for Desktop only) to determine if any elements are generation frustration or confusion. Is there a high click recurrence on elements which should only require one click, indicating an error (e.g., product images that do not lead to a Product page or to a 'Quick view' modal)? Are the images or product descriptions generating a high hesitation time?
3. Optional. To understand the highest performing sub-categories, while still in Zoning analysis set your Analysis context to All visitors. Focus on the following page elements:
Listed products
- Check the exposure rate and the engagement rate (for Desktop)/ attractiveness rate (for Mobile) of the listed products. Can users view the list of products? How many rows are being viewed?
Items beside the image
- Look at the click rate and conversion rate per click (goal= 'Add to cart'). Is the info below the image clicked? How is ‘Wishlist’ performing, is seeing a Wishlist contributing to the goal conversion? Is there a CTA for quick ‘Add to cart’? (compare to ‘Add to cart’ performance on the PDP). Is the information below the image being clicked?
- Check the conversion rate per click (goal= E-commerce). How is the 'Wishlist' performing? Does viewing a Wishlist contribute to goal conversion? Is there a CTA for quick 'Add to cart'? (Compare to 'Add to cart' performance on the PDP)
Filters
- Look at the click rate, conversion rate per click (goal= 'Viewed PDP') and exposure rate. Are the filters sufficiently exposed? Which filters are most frequently used? Which filters lead to higher conversion (leading to PDP)?
Information prioritization (page element order):
- Once more, look at the click rate, conversion rate per click (goal='Reach PDP'), and exposure rate/attractiveness rate. Which elements are most interacted with by users? Are they prioritized accordingly? Are there any elements that are not relevant, resulting in a lower conversion rate?
Take action
- If you notice a high scroll rate but low activity, particularly when comparing bouncers vs. non-bouncers, consider making your filters sticky to the page. This will allow users to easily apply and reapply filters as they continue browsing beyond the fold line.
- If you observe a low exposure rate of the first couple of product rows, make sure that at least the first product row is visible above the fold line.
- Based on the performance metrics such as click rate, engagement rate, and conversion rate, reorganize and regroup filters based on their performance and importance to the users. Prioritize filters that are frequently clicked on and lead to higher engagement and conversion rates.
- If you observe a low click/tap rate but a higher conversion rate per click on the filter and sorting features, consider making these buttons stick to the screen to increase their visibility and accessibility. Additionally, clarify the copy related to the filter and sort by CTAs to provide clear instructions to users.
- To address uncertainty around displayed product details indicated by a high hover rate or hesitation time over product images, consider implementing solutions such as including product thumbnail images, changing images upon hover to show different views or variations, and displaying color swatches or styles with availability information.
- If you identify high-performing sub-categories (as indicated in the filter analysis), consider highlighting elements on the Homepage or Landing pages to promote them further.
Go further
Learn how to analyze a Product page this Help center article or take the Product page analysis: Retention and Add to cart CS University course!