One of the more advanced things you can do with Adobe Analytics is to track click-through rates of elements on your web pages. Adobe Analytics doesn’t do this out of the box, but if you know how to use the tool, there are some creative ways that you can add click-through rate tracking to your implementation. In this post, I will share a few different ways to track click-throughs for both products and non-product items.
Product Click-Through Rates
If you sell physical products, you may have pages that show a bunch of products and want to see how often each product is viewed, clicked and the click-through rate. In my Adobe Analytics book, I show an example of a product listing page like this:
If you worked for this company, you might want to know how often each product is shown and clicked, keeping in mind that this could be dynamic due to tests you are running or personalization tools. Luckily, this is pretty easy to do in Adobe Analytics because the Products variable allows you to capture multiple products concurrently. In this case, you would simply set a “Product Impressions” success event and then list out all of the products visible on the page via the Products variable like this:
s.events=”event20″;
s.products=”;11345,;11367,;12456,;11426,;11626,;15522,;17881,;18651″;
Then, if a visitor clicks on one of the products, on the next page, you would set a “Product Clicks” success event and capture the specific product that was clicked in the Products variable:
s.events=”event21″;
s.products=”;11345″;
Once this is done, you can open the Products report and view impressions and clicks for each product. In addition, you can create a new calculated metric that divides Product Clicks by Product Impressions to see the click-through rate of each product:
This report allows you to see how each product performs and can also be trended over time. Additionally, once the click-through rate calculated metric has been created, you can use that metric by itself to see the overall product click-through rate like this:
Non-Product Click-Through Rates
There may be times that you want to see click-through rates for things that are not products. Some examples might include internal website promotions, news story links on a home page or any other important links on key pages. In these cases, you could use the previously described Products variable approach, I don’t recommend it. Using the Products variable for these non-product items would result in many (hundreds or thousands) of non-product values being passed to the Products variable, which is not ideal. It is best if you keep your Products variable for products so you don’t confuse your users.
When I ask Adobe Analytics power users in my Adobe Analytics “Top Gun” class how they would track click-through rates, the most frequent response I get (after the Products variable) is to use a List Var. For those unfamiliar, a List Var is an eVar that can collect multiple values when they are passed in with a delimiter, similarly to how the Products variable is used. On the surface, it makes sense that you can follow the same approach outlined above using a List Var, but unfortunately, this is not always the case. To illustrate why, I will use an example from a company that faced this problem and used a creative solution to it. Ferguson is a plumbing supplies company that displays its main product categories on the home page. They wanted to see the click-through rate of each, but this got complicated because once a visitor clicked on one of the categories, they were taken to a page that had product sub-categories and they also wanted to see impressions of those! So, on the first page, they wanted impressions and then on the second page they wanted to capture the click of the item from the first page, but at the same time capture impressions for more items on the second page! This illustrates why the List Var is not always good for tracking click-through rates. If they were to try and use a List Var, we could easily track impressions on the first page, but what would we do on the second page? It isn’t possible to tell the same List var to collect the ID of the item clicked on the first page AND the list of items getting impressions on the second page. If you passed all of items at the same time, the success events you set (Clicks and Impressions) would be attributed to both and all of your data would be wrong! You could use multiple List Vars, but then you’d have to use two different reports to see impressions and clicks, which makes things very difficult and time consuming. You could also fire off extra server calls when things are clicked, but that can get really expensive!
Therefore, my rule of thumb is that if you want to see impressions and clicks of products, use the Products variable and if you want to see impressions and clicks for non-product items, only use a List Var if there are no items on the page visitors get to after clicking that require impressions themselves. But what if you do want impressions on the subsequent page like Ferguson did? This is where you have to be a bit more advanced in your use of Adobe Analytics as I will explain next.
Advanced Click-Through Rate Tracking (Experts Only!)
The following gets a bit complex, so if you aren’t an Adobe Analytics expert, be forewarned that your head might spin a bit!
As mentioned above, you have solved 2/3 of your impression and click tracking problems – products and non-products where there are no impressions on the subsequent page. Now you are left with the situation that Ferguson faced when they had impressions on both pages. To solve this, you have to use the Product Merchandising feature of Adobe Analytics. This is because you need to find a way to assign impression events and click events on the same page, which means you need to set your success events in the product string so you can be very deliberate about which items get impressions and which get clicks. However, as I started earlier, you don’t want to pass hundreds of non-product items to the Products variable, but you cannot use Merchandising without setting products (I warned you this was advanced stuff!).
To solve this dilemma, you can set two “fake” products and use the Product Merchandising feature to document which non-product items are getting impressions and clicks. By using the Merchandising slot of the Products string in combination with the success events slot of the Products string, you can line up impressions and clicks with the correct values. To illustrate this, let’s look at an example from Ferguson’s website. If you use the Adobe Debugger on the home page, you will see the following in the Products variable:
While this looks pretty intimidating, if you break it down into its parts, it isn’t that bad. First, you will see that a “fake” product named “int_cmp_imp” is being passed to the Products variable once for each item that gets an impression. This means that instead of hundreds of products being added, only one is added to the Products report. Next, in the success event slot of the Products string, you will see that event40 is being incremented by 1 for each item receiving an impression. Next you will see that the actual item receiving the impression is captured in a product syntax merchandising eVar18. For example, the first one captured is “mrch_hh_kob_builder” (you can put whatever values you want here). Then the same approach is repeated once for every item receiving an impression on the page. By setting event40 and eVar18 together, each eVar18 value will increase by one impression upon page load (note: that the “fake” product will receive impressions as well, but we probably will just disregard that).
While this may seem like overkill for this type of tracking, this approach will begin to pay dividends when the user clicks on one of the items and reaches the next page. On the next page, you need to set impressions for all of the new items shown on that page AND set a click for the item clicked on the previous page. Here is what it might look like:
Notice here that the beginning of this string is exactly the same as the first page with the “fake” product of “int_cmp_imp” being set for each item as well as the impression event40 and the item description in eVar18. The key difference here is highlighted in red in which a new product is set “int_cmp_clk” and a new click event41 is incremented by 1 at the same time as eVar18 is set to the item that was clicked on the previous page. The beauty of using the Products variable and Product Merchandising is that you can set both impressions and clicks in the same in the same Products string, while at the same time only adding two new products to the overall Products report.
When you look at the data in Adobe Analytics, you can now add your impressions event (event40), your clicks event (event41) and add a calculated metric to see the click-through rate:
Final Thoughts
By using a combination of success events, the Products variable and, in some cases, Product Merchandising, it is possible to see how often specific items receive impressions, clicks and the resulting click-through rate. There may be some cases in which you have a large number of items for which you want to see impressions and clicks and in those cases, I suggest checking with Adobe Client Care on any limitations you may run into and, as always, be cognizant of how tagging can impact page load speeds. But if you have specific items for which you have always wanted to see click-through rates, feel free to try out one of the techniques described above.