A good CRO process starts with thorough preliminary research in which the customer journey (or customer journey) plays the main role. In most Web analytics tools, it is difficult to see the actual paths customers take. In the average navigation reports, you can see the first two or three consecutive pages. But if you want to look beyond that, it quickly becomes difficult. In addition, if you deploy a funnel report, you only see the steps you've predefined yourself and not which steps customers view in between. 

Disco

So these funnels and navigation reports give a good first indication, but if you want to add more detail, you'll have to go to a tool other than the web analytics tool. For this we have the tool Disco tried out. Disco is a process mining tool that provides detailed insight into processes. The tool is often used to map processes that have both online and offline steps. For example, you can use it to easily track the processing of an order through to delivery.
In this case, we used the tool to map an entire online customer journey. 

What do you need.

First, you need access to your raw data. For example, through BigQuery. In advance, you determine what data you need. The minimum requirement is a user-id, a timestamp and the pages and main events users see. For example, we quickly found out that we needed not only all page visits, but also event data such as search used or add to cart. Depending on your research question, add other dimensions. Like your device type or user characteristics like logged in or new visitors. With this raw dataset we did some more manipulations in Python. For example, the timestamp of Bigquery does not match the data format of Disco, so we adjusted that. We also categorized all pages into distinct content types. Consider, for example, removing the search term in a url. This way you ensure the cleanest possible data set. 

Provide a clear hypothesis

Even if you have a very clean data set, there are obviously millions of versions of a route a customer might take on your Web site. When you look at this whole data mush, you quickly get lost in details. So think carefully beforehand about the question you'd like to answer. So not, “What is my customers” online behavior?“ But ”How do customers navigate on desktop when they've done an add to cart?". 

The result

When you make all customer journeys insightful, you still end up with spaghetti: 

In the Disco tool, you can zoom in on the different paths customers take in detail. You can filter, zoom in and view individual cases. In addition, the colors indicate how often this step occurs in a customer journey (the darker the color the more people have this step in their journey). When you look at all the data it's still a big mess, but the further you zoom in the more detail you can see.

This is an example of a deel of a journey:

This level of detail does allow you to gain insights. And the advantage of this type of data set is that you can use the same data to answer multiple research questions. This forms a good basis for your optimization program. 

Meetup on Process Mining

Want to learn how to apply data science within CRO yourself? On May 19, we will organize a meetup on this topic. Want to know more? Then take a look here: Meetup on Process Mining.