Data-driven decision making in marketing

I was talking with one of our clients the other day. She told me they had a significant drop in sales during the last couple of months. We checked the number of visitors but found no answer there. Approximately the same amount of visitors each month from the same traffic sources. This should mean potential customers are lost on the website. Among many issues that could cause this problem, we started to analyze the check-out process, namely the shopping cart abandonment rate.

How to analyze shopping cart abandonment?

First we have to create destination-page type goal in Google Analytics, where the destination page is the so-called „thank-you” page, the one that appears to the users as a confirmation of their order. We add a couple of steps to the „Funnel” option, the ones every user has to go through to place an order (Shopping cart, Start checkout, Order confirmation). This way we can see the abandonment rate of the shopping cart. If this is too high, we have to analyze each step in the funnel, to see why users abandon the checkout process.

If we want to analyze user actions on a page, we have to implement Google Analytics event tracking. There can be many types of events on a website: PDF file download, sending an email or click on a button on a certain page, etc.

In our case we analyzed the clicks on the „Start checkout” and „Order confirmation” buttons.

To create Events in Google Analytics, we used this easy tool from RavenTools:

You have to pay attention to consistency while tracking events on a website, to be able to compare them easily. Ex. If at the first step the event category is „Checkout”, it should be the same category name for all steps afterward. Be careful, because the names are case-sensitive.

When you have configured the tracking codes in RavenTools, send them to your front-end specialist to have them implemented on the required pages.

What are some of the conclusions we can draw from the data we measured?

In our example we can see that out of 186 potential customers who clicked the Start checkout button only 100 clicked the Order confirmation button, too. This means 86 customers abandoned the shopping cart on the Checkout page (the page accessed by clicking the Start checkout button). If we segment the traffic on mobile or even further on, for instance on Samsung users, we can study if this loss is bigger or too big on these segments. If shopping cart abandonment on mobile is higher than on desktop, the website might have some usability issues we need to address. If the abandonment is too high on a certain mobile phone model, there could be a bug on the website for a certain mobile configuration or an OS that we need to correct. We found out the website had a bug on the mobile version that needed to be corrected.

Another solution for shopping cart abandonment in general is the installation of an add-on to the ecommerce CMS (or developing one) that automatically sends a reminder email to the customers about the abandoned shopping cart.

You can use Google’s event tracking method for non-ecommerce conversion tracking. If a PDF document download has a conversion value, by tagging the download link we can analyze during campaigns the efficiency of the traffic sources, we can relocate part of the budget from one source to another to get better results from the same budget.

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