Play user behavior path analysis, 3 methods are enough

This article will introduce three commonly used analysis methods in user behavior path analysis: conversion funnel, smart path and user path, analyze the similarities and differences of the three methods, and recommend the use of appropriate methods in appropriate analysis scenarios.

During the operation of a product, the product, operation, and marketing teams all hope to have a clear understanding of the user behavior path and find answers to the following questions from the complex user behavior:

1. What happens from the time a user enters the product to the time they leave? What kind of behavior pattern is mainly followed?

2. Are users following the path guided by the product design? At which steps did the loss occur?

3. What is the actual direction after the user leaves the expected path?

4. What are the differences in behavior among users brought by different channels and with different characteristics? Which type of users are more valuable?

Ultimately, the answers to these questions are used to verify operational ideas, guide product iteration and optimization, and achieve the ultimate goal of user growth and conversion. So how can we answer these questions through massive amounts of user behavior data? Common analysis methods include: conversion funnel, smart path, and user path .

The common point among the three is that they are all based on user behavior, with the conversion rate of the upstream and downstream links as the calculation core. The relationship between the three is like an onion, with each layer closer to the core and more focused than the previous one.

The relationship between conversion funnel, smart path, user path and user behavior

The conversion funnel is a pre-set path; the smart path is to discover more funnels after setting the target behavior; the user path is to fully reproduce the user's entire conversion process. In practical applications, the three have their own applicable analysis scenarios, and usually need to be combined with each other to complement each other . The following is an analysis of the three analysis methods one by one.

▌Conversion funnel: improving conversion results through user guidance

The conversion funnel is suitable for analyzing and monitoring key links in product operations , finding weak links, optimizing through user guidance or product iteration, and improving conversion effects.

Whether it is the onboarding of new users, a business process or an operational activity, a funnel can be established for analysis as long as there is process conversion involved. For example:

• For a social APP , you can build a funnel : open the APP – register – log in – add friends, to analyze the process of new users from starting to use to participating in social activities ;
• For e-commerce apps, you can build a funnel : browse the details page – add to cart – submit order – successfully pay for order, to analyze the process from users seeing the product to the final successful payment, and the loss of each link;
• For EDM before a big promotion, you can also build a funnel : send email – email arrives – email is opened – click on the product in the email – purchase the product – pay for the order.

Conversion Funnel

During the analysis process, you can observe whether the overall conversion rate meets industry standards and which steps still have room for optimization in conversion rate? You can use segmentation dimensions to find out the factors that lead to low conversion rates, or you can check other usage paths in the loss link and provide targeted guidance, etc.

Churn rate comparison

▌Smart Path: Exploring the Diversity of Conversion Paths

It’s easier to monitor conversion rates by building a funnel in advance when there is a clear conversion path. However, in many cases, although there is an ultimate conversion goal, there are multiple paths for users to reach that goal. It is impossible to determine which path is the path most taken by users and which conversion path is the shortest. At this time, the help of an intelligent path analysis model is needed.

Smart Path Sankey Diagram

Determine the target behavior you want to observe, which is usually a function that the business needs to guide users to complete or a page that they need to reach. It can be set as the starting event to analyze the subsequent behavior path after the behavior occurs; or it can be set as the ending event to analyze the source path. For example:

In e-commerce apps, adding items to the shopping cart is the first step before the final conversion goal of successful payment. However, many users do not submit the order and pay directly after adding items to the shopping cart. In this case, select the target event as " Add to Cart " and set it as the starting event to analyze the user's behavior path after adding to the shopping cart, whether the user's attention is attracted by other recommendations on the page or goes elsewhere.

In a certain knowledge payment APP, there are multiple entrances, which lead to the column details page through banners, search lists, special column lists, special articles, etc., and then lead to the column subscription. If you want to analyze the conversion path of the user's final subscription, you can select the target event as " Subscribe to Column " and set it as the end event .

In short, smart paths can be used to explore and discover more conversion paths. When focusing on a certain path, it is actually a conversion funnel, which can be saved for daily monitoring. When problems are found, they can be further subdivided in the funnel.

▌User path: step-by-step tracking, path identification and analysis of user types

Different from conversion funnels and smart paths, user paths do not require pre-setting funnels or defining which page events or click events to analyze. Instead, they calculate each first step when users use a website or app, and then calculate the flow and conversion of each step in turn. Through data, the entire process from when the user opens the app to when they leave is truly reproduced, and the user's frequent path patterns are further identified, that is, which path is visited by the most users; at which step, users are most likely to churn; and even present paths that product managers had not anticipated when designing the product, finding the most basic and original data for analyzing user behavior; user behavior characteristics can also be identified through paths, and analysis can be performed to see if the user is goal-oriented and wants to use the app and leave. Or aimless browsing. In short, the analysis of user paths has a very important enlightening effect on the product operation process.

User Path Sankey Diagram

▌Summary : Selection of analysis models based on different scenarios

In short, conversion funnels, smart paths, and user paths are all important analysis models based on user behavior path data. The three have similarities as well as differences. The conversion funnel is a pre-set path; the smart path is to discover more funnels after setting the target behavior; the user path is to fully reproduce the user's entire conversion process . In different analysis scenarios, different methods can be used to find answers to questions. For example, let’s go back to the question mentioned at the beginning of the article:

1. What happens from the time a user enters the product to the time they leave? What kind of behavior pattern is mainly followed?

You can choose a user path model to observe the user's overall behavior path and discover their behavior patterns through their frequent paths.

2. Are users following the path guided by the product design? At which steps did the loss occur?

You can choose the conversion funnel model , set each guide as a step in the funnel, and analyze its conversion and loss.

3. What is the actual direction after the user leaves the expected path?

You can select the conversion funnel model to view the subsequent behavior path of users who have passed the churn stage, or select a preset event as the target event in the smart path to analyze its subsequent behavior path.

4. What are the differences in behavior among users brought by different channels and with different characteristics? Which type of users are more valuable?

You can select a user path model, subdivide the channel dimensions, and view user behavior paths in different dimensions.

This article was compiled and published by @易分析国际 (Qinggua Media) when it is reprinted. Please indicate the author information and source!

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