Product Ratings/Reviews in Adobe Analytics
Many retailers use product ratings as a way to convince buyers that they should take the next step in conversion, which is usually a cart addition. Showing how often a product has been reviewed and its average product rating helps build product credibility and something consumers have grown used to from popular sites like amazon.com.
Digital analytics tools like Adobe Analytics can be used to determine whether the product ratings on your site/app are having a positive or negative impact on conversion. In this post, I will share some ways you can track product review information to see its impact on your data.
Impact of Having Product Ratings/Reviews
The first thing you should do with product ratings and reviews is to capture the current avg. rating and # of reviews in a product syntax merchandising eVar when visitors view the product detail page. In order to save eVars, I sometimes concatenate these two values with a separator and then use RegEx and the SAINT Classification RuleBuilder to split them out later. In the preceding screenshot, for example, you might pass 4.7|3 to the eVar and then split those values out later via SAINT. Capturing these values at the time of the product detail page view allows you to lock in what the rating and # of reviews was at the time of the product view. Here is what the rating merchandising eVar might look like once split out:
You can also group these items using SAINT to see how ratings between 4.0 – 4.5 perform vs. 4.5 – 5.0, etc… You can also sort this report by your conversion metrics, but if you do so, I would recommend adding a percentile function so you don’t just see rows that have very few product views or orders. The same type of report can be run for # of reviews as well:
Lastly, if you have products that don’t have ratings/reviews at all, the preceding reports will have a “None” row, which will allow you to see the conversion rate when no ratings/reviews exist, which may be useful information to see overall impact of ratings/reviews for your site.
Average Product Rating Calculated Metric
In addition to capturing the average rating and the # of reviews in an eVar, another thing you can do is to capture the same values in numeric success events. As a reminder, a numeric success event is a metric that can be incremented by more than one in each server call. For example, when a visitor views the following product page, the average product rating of 4.67 is being passed to a numeric success event 50. This means that event 50 is being increased for the entire website by 4.67 each time this product is viewed. Since the Products variable is also set, this 4.67 is “bound” (associated) to product H8194. At the same time, we need a denominator to divide this rating by to compute the overall product rating average. In this case, event 51 is set to “1” each time that a rating is present (you cannot use Product Views metric since there may be cases in which no rating is present but there is a product view). Here is what the tagging might look like when it is complete:
Below is what the data looks like once it is collected:
You can see Product Views, the accumulated star ratings, the number of times ratings were available and a calculated metric to compute the average rating for each product. Given that we already have the average product rating in an eVar, this may not seem important, but the cool part of this is that now the product rating can be trended over time. Simply add a chart visualization and then select a specific product to see how its rating changes over time:
The other cool part of this is that you can leverage your product classifications to group these numeric ratings by product category:
Using both eVars and success events to capture product ratings/reviews on your site allows you to capture what your visitors saw for each product while on your product detail pages. Having this information can be helpful to see if ratings/reviews are important to your site and to be aware of the impact for each product and/or product category.
