[Huawei Developers] Jack Wu Shenzhen:
Defining the Session Path Analysis Model​

The session path analysis model provides an intuitive way of displaying how an app is used. With this model, developers can clearly understand the changes in user behavior, frequently visited paths, steps where users churned, and steps with an unexpected churn rate. Such information helps developers enhance the app, user experience, and user conversion.

When to Implement Session Path Analysis

1. Guiding Updates by Showing How Users Actually Use the App​

To maximize the benefits of app optimization and updates, it's important to identify the differences between an app's purpose and its actual usage.

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* Example of a session path analysis report

Let's take Now: Meditation, a leading meditation app in China, as an example of Analytics Kit being used effectively. Now: Meditation provides five types of online courses (pressure relief, emotional management, personal development, sleeping, and focus enhancement) and its revenue is mainly generated from member payments. Initially, the product team thought that pressure relief and emotional management courses would be the most popular, but in reality, the session path analysis shows that sleeping-related courses were the ones drawing most user payments.

In light of this discovery, the product team decided to adjust the display level of the sleeping-related courses so that users would spend less time making a choice. Now: Meditation has reaped the rewards of this change, which has boosted the next-day retention rate of new users by 15%, the number of daily active users by 17%, and the payment conversion rate by 20%.

2. Locating App Flaws by Comparing the Preferred Session Paths of Different Users​

The filter function enables us to compare the path preferences of different audiences. For example, we can check whether new users share the same path during different time segments, and learn which paths are preferred by loyal users. You can segment and further analyze different audiences, and determine the rule of each session path. In this way, session path analysis lets you best optimize your app.

Let's say that we have a lifestyle and social app that allows users to share excerpts of their life using short videos, images, and text, as well as follow people and like others' posts. The operations team found that recently the overall user retention rate dropped significantly, so they were eager to learn about the behavior characteristics of loyal users. Such information could be used to help them design operations campaigns to lead new users and those about to churn to have such characteristics. In this way, the team could improve overall user loyalty for the app.

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* Example of a session path analysis report

The app's operations team utilized the session path analysis function. They selected Active users in the filter and set App launch as the start event, with the goal of analyzing the behavioral path of such users. They found that over 70% of active users launched the app three times per day, and were more likely to browse content and follow other users. With this information, they were able to implement two measures to improve user retention by improving the rates of push notification tapping and of users following each other:

First, by enhancing the push notification sending mechanism, drafting better push notification content according to the A/B testing result, and sending audience-specific push notifications. And second, by displaying a message to prompt the user to follow another user when the user browses the latter's home page for more than 3 seconds. After just one month since these two measures were implemented, the retention rate skyrocketed.

3. Finding the Path with the Highest Payment Conversion Rate​

An app tends to have different banners, icons, and content, designed to guide VIP members toward making payments. But which path best gets users to make payments? What is the difference in churn rate for each step per path? Which path has the best conversion effect? And which paths are worthy of more in-app traffic?

Session path analysis has the answers. First, we select only the events related to app launch and payment completion, and then set payment completion as the end event. Session path analysis will then automatically display the traffic resulting from each path to the payment completion event, helping us compare their payment conversion rates.

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* Example of a session path analysis report

4. Specifying the Start Event, and Exploring a Diverse Range of Paths​

The product management or operations team often pre-design a path for a function or campaign, which they expect users to follow. However, not all users will follow this path, and a certain number of users will churn during each step. This leads to some important questions, such as, what do users do after they churned? What attracted them in the first place?

Let's say for an e-commerce app, many users churned in the steps between order creation and payment completion. The operations team wanted to analyze why users abandoned payment. Was it because users browsed other products? Did they leave to compare prices? Did they set another order because they had provided a wrong address or ordered too little/much? To answer these questions, the team can set order creation as the start event, and checked what users did after this event.

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* Example of a session path analysis report

5. Checking the Path with Unexpected Churn to Determine the Reason​

When using session path analysis, if you find unexpected churn during certain steps, you can save these steps as a funnel with just one click. Then, you can use the funnel analysis function to identify the reasons behind user churn.

For example, if the session path analysis report has revealed that most new users churned from adding a product to favorites to placing an order and making payment, the events of this process can be saved as a funnel. You can then use the funnel analysis function to determine the reasons behind user churn, and analyze the conversion effects of the funnel.

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* Example of a session path analysis report

Funnel analysis provides the filter and comparison analysis functions, which allow you to check data according to such conditions as app version, active users, new users, and download channel. By analyzing such data, you'll be able to locate the root causes leading to user churn, and take measures to optimize your app accordingly.

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* Example of a funnel analysis report

These are about the major scenarios where session path analysis can play its role. To learn more, click here to get the free trial for the demo, or visit our official website to access the development documents for Android, iOS, Web, and Quick App.