Three Approaches to Uncover User Journey

This article was also published on Towards Data Science.

Companies invest in data science only because it serves their critical paths - generating revenue or saving costs. Data science is unique in its ability to automatically uncover viable approaches by analyzing history. This ability supercharges customer acquisition, a key piece in the critical path. Companies can acquire customers much more efficiently by scaling up what has proven to work and cutting back on what doesn't. Specifically, companies care about where their customers come from, when they convert or drop off, and why.

In Connect the dots in data strategy , I discussed how building a data system as the "digital twin" of a user journey helps a company understand the big picture and answer the above essential questions. This article will dive into three practical approaches for building such a digital twin.

Mapping high-level user journey with Sankey diagram

The Sankey diagram is the most popular diagram to illustrate customer journeys. It shows how different groups of users move from one point to another, which user paths are most popular, and where people drop off. Because it's superior in visualization, the Sankey diagram is a critical feature in many data analytics software.

The Sankey diagram is best-suited for high-level business decisions. For example, if the diagram indicates that a specific channel drives the most traffic and has a high conversion rate for a business, it will benefit from doubling down on that channel. On the other hand, if users often drop off after a particular interaction with the website, it's worth investigating what goes wrong with that touchpoint.

However, the Sankey diagram requires careful user journey mapping to work correctly. It's incredibly challenging for companies to try to map user interactions on websites or within apps by setting up a tracking mechanism for each possible touchpoint. It becomes a paradox: companies that need to understand user journey often don't have complete insights into it and, therefore, can't map out all the essential touchpoints on the journey. However, the Sankey diagram will only be accurate when a touchpoint is mapped, and a tracking mechanism is built for it.

Additionally, the Sankey diagram doesn't tell the story behind a user journey - why users take one path over another or drop off. Fortunately, the second and third approaches can complement the Sankey diagram's pitfalls.

User interaction deep dive with session replay

Session replay is a technology to record and playback historical user interactions by session. Since it records every user interaction automatically, it doesn't require user journey mapping beforehand. Therefore, it significantly lowers companies' barriers to getting started with data science.

Session replay records user screen or clickstream data and the time between each click or movement. It provides rich details for product managers, designers, and engineers to interpret user behaviors, such as whether users encounter issues or confusion on a specific screen and what may cause those issues.

Heatmap provides more directions

For some web pages, companies don't need granular tracking on each touchpoint, but insights into page-level user interactions are still beneficial. For example, many companies spend a lot of resources on organic marketing, such as placing creatives and blogs on their websites, and they need to understand if users view or click the content.

Mapping and tracking all the creatives and blogs will take a lot of work, especially considering these often get updates and change positions. It's also unnecessary for companies to employ session replay to understand all user interaction details. In this scenario, a heatmap is a good fit.

A Heatmap shows which sections on webpages get more attention. It helps companies move the crucial content to where the most attention is and potentially redesign websites or apps to put content in front of users.

Choosing the right solution

While each illustration has pros and cons, combining one or more helps companies acquire the necessary details of the user journey.

In the following articles, I will continue diving into data science technologies for customer acquisition. If you want to chat about them, feel free to contact me on Linkedin.

Previous
Previous

A Complete Guide to Data-driven Customer Acquisition

Next
Next

Double Down on the Most Valuable Customers