From attracting new users to retaining users, the entire user life cycle analysis process

In today's highly competitive market environment, understanding and managing the user life cycle is the key to achieving user growth and retention. This article will deeply analyze the full process management of the user life cycle, from attracting new users to retaining users, and explain in detail the user life cycle characteristics and analysis methods of different business types (such as consumer goods, durable goods, platform products, etc.).

Understanding the user life cycle is an important step in achieving refined management. How should the life cycle be divided? What issues should be focused on at each stage? What are the differences between the life cycles of different businesses?

Today I will write a long article to explain it clearly to everyone.

A diagram of common practices in the user life cycle:

This picture is often seen on the Internet, dividing the user life cycle into 5 stages

1. Introduction period: users are new to our products
2. Growth stage: Users begin to become familiar with our products and use them extensively
3. Mature stage: Users rely on our products and pay a lot
4. Decline: Demand has been largely met, and payments are declining
5. Churn period: New products are launched, changing demand

There are 4 major types of business that may conform to the above pattern

1. Fast-iterating consumer goods (snacks, traffic generation)
2. Fashion products (clothing, shoes and hats)
3. Technology products (mobile phones, tablets)
4. Cultural and entertainment products (games, movies and TV)

These businesses are frequently updated, with new gameplay and new themes every year, and each update involves a process of user growth and decline.

There are three key issues in analyzing this type of business:

1. Reduce the loss of new users and help new users through their growth period
2. Tap into the value of mature users and encourage them to pay more
3. When the user base declines, launch new products to meet demand

Based on these two goals, four key issues are derived:

1. Introduction period: New user retention analysis. From the day the user registers, look at the retention rate and activity rate of T+1/T+2…T+N days.
2. Growth stage: User path analysis. Pay attention to whether new users have access to paid functions and whether they have converted their first order. Analyze the key factors that affect conversion and promote the first conversion.
3. Mature stage: User stratification analysis. Differentiate between high-, medium- and low-consumption users. Find the characteristics of high-value users and encourage customer acquisition to find more such users. Compare the consumption differences between high-value and medium-value users and try to increase the consumption of medium-value users.
4. Decline stage: User retention analysis. Analyze user retention rate and pay attention to the timing of business iteration. Test whether new products/new selling points attract users.

As shown in the figure below

1. User life cycle of platform/tool ​​products

Note! Not all users need to complete all 5 stages, for example

1. Trading platform: e-commerce, O2O, travel APP

2. Content platform: short video, text, novel APP

3. Tool products: AI tools, Office, ERP, etc.

These products are basic tools for personal life/entertainment and corporate office work, and are daily necessities. Therefore, there is no so-called "decline period". The three core problems of these products are:

1. Does the user know that you can meet his needs?

2. Will users be able to use it and adapt to your operation?

3. Does the content/service you provide meet user needs?

Specifically, in terms of user life cycle data, the effect is as follows: after the introduction period, users begin to divert:

• Core users: have a long period of maturity and strong purchasing power
• Light users: in the growth stage, consumption stagnates to a certain stage, and may be awakened by promotions, etc.
• Marginal users: They barely make it through the introduction period, quickly churn away, and are difficult to awaken

When analyzing this type of product, special attention should be paid to: User structure

1. Is the new user retention rate high enough?

2. Whether it attracts enough core users

3. Do core users continue to pay?

2. User Life Cycle of Durable Goods

Big-ticket items: This category often has high product amounts, low consumption frequency, and a long user selection cycle. For example, houses, cars, weddings, overseas travel, home furnishings, decoration, consumer loans, etc. The characteristics of these products are:

1. Single consumption is large and the decision cycle is particularly long (the introduction period is particularly long)

2. Financial resources are limited, budget is limited, choose within a certain range (there is no so-called growth period)

3. Extremely low consumption frequency and repurchase rate (no so-called maturity or decline period)

At this time, the key to data analysis and operation is to seize the long user introduction period, do enough user homework, and promote business. If you miss this window period, there will be no chance again. For example, the consumption cycle and key nodes of a car are shown in the following figure:

When users have real needs, during the window period, the range of brands they investigate will become narrower and narrower, and the probability of a deal will become higher and higher as time goes by. There are three important nodes:

1. Look aimlessly, without any intention of brand/product

2. If you have an interest in a product, start comparing performance/price

3. Start bargaining and ask directly about price/discount/delivery (as shown below)

If we can collect data and determine which stage the user is currently in, we can greatly increase the transaction rate. This requires the joint efforts of sales, operations and data.

The sales department should not just say, "Just take a look," but take the initiative to understand user needs, especially whether users have referred to competing products.

The data department needs to clearly collect data and label it as material for in-depth analysis.

At this point, there are four major data analysis topics:

1. User demand classification: clearly understand the user needs that each type of product targets.
2. Lifecycle calculation: Understand the decision-making time cycle of each type of user.
3. Contact node collection: Use various means to understand at which node the user contacts us.
4. Key action analysis: From the lessons learned from success/failure, summarize the key actions that are useful in promoting success.

3. More types of user lifecycles

If you want to analyze the user characteristics of more businesses, you can use the user's single transaction amount and purchase batch as a matrix to obtain the classification shown in the following figure.

In general:

• For users with high frequency and low amount of consumption each time, the above general approach to user life cycle can be applied.
• For users with low frequency but high amount of purchases each time, the above approach for large items can be applied.

It should be noted that under the same service, there may be two groups of users, for example:

• For the same micro-loan, when ordinary users borrow, they will have low frequency and high amount, while when small and micro business owners borrow, they will have high frequency and high amount of revolving loans.
• For clothing consumption, ordinary users who buy a few pieces during the changing seasons are high-frequency and low-amount consumption, but the bosses who buy a lot of clothes and sell them to secondary sellers in fourth-, fifth- and sixth-tier cities may be high-frequency and high-amount consumption.
• When booking tickets, ordinary users who are getting married and traveling abroad may have low-frequency and high-amount consumption, but business people who travel frequently have high frequency and high-amount consumption.

This is a very important tip: even in the same business, the users with the longest life cycle may not be in the same group as other users. They have special demands. When managing the user life cycle, you cannot force everyone to become this type of user, nor can you design the paths of other users completely according to the growth path of this type of user, which may lead the business into a ditch.