A complete analysis of user retention strategies!

After the user is activated, we need to find a way to retain the user , and then convert him. It can be said that retention is the key. Both attracting new users and conversion are based on good retention. Otherwise, if you spend a high cost to acquire a large number of users but fail to retain them, it means that the money is wasted. Since all the users have left, there is naturally no question of conversion, and the conversion rate will not be good in this way.

Therefore, retention is the key. There is a saying in the industry that life depends on attracting new customers and death depends on retention. Born from attracting new customers means that if you want to grow big you must rely on attracting new customers, and die from retention means that if the retention is not good, the product will die.

Okay, without further ado, let’s talk about the topic of user retention. I hope it will be of some inspiration to everyone.

1. What is the prerequisite for user retention?

There are prerequisites for user retention. Not all products are suitable for retention. Only products with established PMF have the basic conditions for retention, which means that the long-term value of this product must be established.

So how do you determine whether a product has long-term value?

We can evaluate based on the retention curve, which is generally based on three dimensions: basic form, industry average, and changing trend.

We usually judge based on the shape of the retention curve first. For a product with established PMF, its retention curve must be close to L-shaped. If it is a fast-declining curve with the tail end close to 0, then the curve is unhealthy, indicating that PMF has not been achieved.

If PMF is not achieved, then what should be done is not retention but PMF first. There is no value or meaning in retaining data at this time.

If there is no problem with the basic shape of the retention curve, then look at the difference with the industry average. This is easy to understand. If user retention is far below the industry average, it is definitely not acceptable. This does not mean that PMF is not established. In fact, as long as an L-shaped retention curve is formed, it means that the PMF of this product has been established to a certain extent. However, if it is far below the industry average, it means that there is a lot of room for improvement. At this time, what should be done is not retention, but to further improve the value and usability of the product, and first pull the mean of the retention curve to near the industry average.

If the difference with the industry average is not big, then look at the changes in the retention curve at different stages, such as the difference between the retention curve 3 months ago and the retention curve this month, whether it has gotten better or worse.

If it gets worse, you need to first consider the reasons for the worsening retention, solve the systemic problems first, improve the retention curve, and then work on retention.

There is another judgment method circulating on the market, which is to judge through the user data indicators recommended by Android: the number of new daily active users exceeds 100, 30% of new users are retained on the next day, reaching 100,000 users, 5% payment conversion rate, and monthly churn rate is less than 2%.

From my point of view, this set of indicators has certain limitations, but it is indeed of reference value.

2. What are the reasons why PMF does not hold?

The three most likely possibilities are: false needs, short-term value but no long-term value, and the solution is not good enough.

The first type of pseudo-demand is quite misleading. For example, the 020 solution - door-to-door car washing and door-to-door hair cutting - was popular a few years ago. It was popular for a while, but soon faded away because from a practical point of view, it did not really facilitate users. Users still needed to lead the door-to-door service person to the parking place and wait there until the car was washed before leaving. The process is not much different from going to a car wash, except that you save a few kilometers in gas money. Moreover, they may also face problems such as how to obtain water and how to discharge sewage, which is even more troublesome.

As things have evolved to the present, many car washes are now opened in office buildings. This way, you can wash your car while you are at work, and it will be ready when you get off work. This is actually more convenient.

In fact, false demands can only be verified through MVP. Of course, when the market is enthusiastic, people can’t think too much. It depends on yourself.

The second type has short-term value but no long-term value. This is also very common. For example, Face Meng was popular for a while, but soon no one used it anymore. It was just for novelty, but it actually has no long-term value.

There is actually no solution to this situation. Long-term value must be added at the end, and long-term value must be used to take over the traffic brought by short-term value. Only in this way can the entire chain be established.

The third type of solution is not good enough. This may be common in the early stages of many products. For example, if there are not enough drivers in the early stages of a taxi APP, the user experience of taking a taxi will be poor, and retention will naturally be poor.

In this case, gradual adjustments and optimizations can be made through internal testing, public testing, and then opening to the entire network. This method is still relatively common, and even now there are still many apps using it. For example, the podcast app Xiaoyuzhou is made using this method.

3. Difficulty Assessment of User Retention

If the product's PMF is established, the next step is to evaluate the difficulty of retaining users.

The difficulty of retaining users is naturally different for different products.

For example, marriage and dating apps are naturally short-cycle products. For example, if a user finds a marriage partner through a marriage and dating app within three months, the user will naturally be lost at this time, and the value basis of the product no longer exists, so the life cycle is short. A short cycle means limited time, and retention will become more difficult.

For example, for an app for checking provident fund, the frequency of users using it is naturally low. The provident fund data is updated once a month, and no user will check it every day. At this time, the difficulty of retaining users increases.

The difficulty of user retention can be evaluated based on the user retention formula: user retention = user perceived value + migration cost > difficulty of use . Conversely, if user perceived value + migration cost < difficulty of use, then users will be lost.

I think this formula is not difficult to understand. Let me talk about the difficulty of use. It not only refers to the difficulty of using the product, but also the issue of whether users can remember to use it. For example, a national-level product like WeChat is easy to use. It is positioned for social networking among acquaintances, and everyone uses it. However, Maimai is much worse. It is positioned for workplace social networking. How many people really use Maimai to chat frequently?

Based on this formula, we generally ask the following questions to roughly determine the difficulty of user retention:

• How strong is user demand: rigid demand vs. non-rigid demand?
• How complex is the product's functionality: single function vs multi-function? Is it scalable?
• What is the natural life cycle of a product: long-lived vs short-lived?
• How often is the product naturally used: high frequency vs low frequency?
• Are there a large number of broadly substitutable items: few vs many?
• The cost of users switching to other products: Is the switching cost high vs low?

Let's take two examples:

Example 1: Food delivery app

How strong is user demand: rigid demand vs. non-rigid demand?

At least it is an absolute necessity for urban white-collar workers.

How complex is the product's functionality: single function vs multi-function? Is it scalable?

The functions are complex and the service content is rich.

What is the natural life cycle of a product: long-lived vs short-lived?

Long-lived type, I feel like they are basically lifelong loyal users.

How often is the product naturally used: high frequency vs low frequency?

High frequency, at least once a day, and many are 2-3 times.

Are there a large number of broadly substitutable items: few vs many?

There are few. The main ones on the market are Ele.me and Meituan.

The cost of users switching to other products: Is the switching cost high vs low?

This is not high, you can use any one.

It’s easy to retain items in this category.

Example 2: Financial loan app

How strong is user demand: rigid demand vs. non-rigid demand?

It is a necessity for people who are short of money.

How complex is the product's functionality: single function vs multi-function? Is it scalable?

The function is very simple, which is to borrow money.

What is the natural life cycle of a product: long-lived vs short-lived?

It should be considered a short-lived product. Although users may occasionally log in to check their orders or make repayments after borrowing money, they are unlikely to take other actions.

How often is the product naturally used: high frequency vs low frequency?

It’s very low frequency. After borrowing the money, I check it once a month at most.

Are there a large number of broadly substitutable items: few vs many?

There are many loan apps on the market.

The cost of users switching to other products: Is the switching cost high vs low?

Not high, any one will do.

In this case, there is no need to do any retention work, just focus on activation and conversion, and then recall old users.

In general, if retention is too difficult, then consider other directions, such as expanding scenarios or enhancing conversions.

4. Core Path to User Retention

There is an implicit path for user retention, from when a user is acquired, to when the user starts using the product, to when the user forms usage habits, to when the user finally leaves the product. Generally speaking, all products follow this logic.

Every link in the middle can be used for retention. For example, for traffic and customer acquisition, we can improve user retention through precise customer acquisition. For new user activation, we can raise the churn curve by increasing the activation rate, and we generally use the HOOK model to strengthen the repeated use and encourage users to develop usage habits. To extend the life cycle, we generally strengthen incentives + expand scenarios/services + recall old users.

In general, there are three major directions: improving activation rate + raising retention rate + strengthening recall. Next, we will discuss the strategies for each of these links in detail.

5. Traffic and customer acquisition

As we mentioned earlier, this link mainly improves user retention through precise customer acquisition. Generally, data is analyzed based on customer acquisition channels + user grouping. If conditions permit, it can also be analyzed based on functions.

How to divide by customer acquisition channel? Let’s take an example.

For example, for an audio app, suppose its channel retention curve is as follows:

We can probably draw the following conclusions:

a. The number of users entering through the [pre-installation] channel is small and the retention rate is low. Consider suspending the delivery.

b. The long-term retention of users from these two channels [search engine advertising and public accounts] is much better than that from other channels. If ROI allows, we will further increase the investment.

At the same time, we also need to analyze the users and copywriting faced by these two channels, and see [which strategies can be borrowed from other channels].

Finally, we noticed that the user retention rate of the [official account] is high, but the number of users entering is currently small, so we can focus on developing it.

c. [Information flow advertising and WeChat advertising] channels have the most users, but the retention rate is not ideal. It is necessary to specifically analyze whether the incoming traffic is not accurate enough. You can refer to the strategy of search engine advertising.

d. The activation rate of big V promotion is the lowest. We can further understand whether the big V we cooperate with does not match the product tone, or his fans do not match the target user portrait. Adjust the target group of influencers to be more precise.

What should we do to segment users? Let’s take an example to illustrate this.

Assume that the users of this audio app are divided into the following user groups according to their usage purposes:

Through the above user purpose retention curve and product function retention analysis, we can find that:

The retention curves for leisure and entertainment, learning and recharging, current affairs news, children listening to stories, and audio recording are all flat, indicating that users who use the product for these five purposes have felt the value of the product. Based on these five purposes, the user activation rate can be increased, and the corresponding functions can be expanded to increase user usage frequency and engagement.

Leisure and entertainment purpose function : The user proportion is the highest, indicating that most users use the audio as entertainment, but the retention rate in week 0 is lower than the average. The audio content fails to meet user needs and has low appeal. It is recommended to add user tags, make content recommendations based on user personalized needs, and improve user activity.

Purpose and function of learning and recharging : The user retention rate is high and the number of users is large. In addition to providing learning audio content, it is recommended to deepen the user participation of this group and increase the frequency and stickiness of users, such as building learning circles and check-in communities.

Purpose of recording audio : The user retention rate is very high, but the number of users is low and the demand is niche. The APP is used more as a tool. It is recommended to add operation guidance, optimize audio recording operations and other functions to give users more convenience and surprises. When launching campaigns to attract new customers, you can target this type of podcast group with relevant campaign materials to attract new customers.

Functions for current affairs news and children listening to stories: user retention rate is good and user demand is acceptable. However, the loss rate is faster in the middle and late stages, perhaps because the content is not fresh enough or not accurate enough. It is recommended to increase the update frequency of such content and provide more high-quality content.

6. Guide users to use the product multiple times and encourage them to develop a habit of using it

As mentioned above, we generally use the HOOK model to provide intensive guidance to users in this stage until users form stable usage habits.

The Hook addiction model was proposed by Nir Eyal and Ryan Hoover, the authors of "Addicted". It mainly focuses on how to make users "addicted" to the product, that is, the four major product logics that allow users to develop usage habits. It includes four elements: trigger, action, reward, and investment.

The specific contents are as follows:

1. Trigger: How to guide users to take action. Divided into internal trigger and external trigger. Internal triggers are dominated by user emotions, habits, and usage scenarios, while external triggers are prompts, emails, authoritative recommendations, etc.
2. Action: drives user behavior. The important thing is to meet the user's psychological expectations.
3. Reward: Provide a variety of potential rewards to keep users interested. There are three categories: social rewards, prey rewards, and self-rewards.
4. Investment: The amount of money users put into a product. If users invest time and energy in a product or service, then they are invisibly raising the threshold for user churn.

Key issues of the HOOK model:

What do users really need? What pain points can you solve for your users? (Intrinsic drive)

How do you attract users to use your service? (External drive)

What is the simplest action a user can take when expecting a reward? How can we simplify the product to make this operation easier? (action)

Are users satisfied with the rewards they receive, or do they want more? (Variable rewards)

What “little investments” have been made in your product? Do these inputs help load the next trigger and store value so that the product value is increased during use? (Input)

Let’s take WeChat Reading and Amap as examples to analyze the HOOK models of these two apps:

Generally speaking, we design various retention actions around triggers, actions, rewards, and investments.

When designing your own company's products, you can also design various retention strategies according to this model.

7. Extend the life cycle

The HOOK model is designed to help users form usage habits, so the next step is to extend the life cycle. Generally speaking, we will extend the user's life cycle in three dimensions: increasing usage frequency + increasing single depth + increasing usage scenarios + using an incentive system.

There are generally two ways to increase the frequency of use: one is to set reminders and triggers with higher frequencies, such as sending push notifications every day, and the other is to optimize the path of core functions. A good path can optimize the user experience and thus increase the frequency of use.

To enhance the single depth is to extend the time of each use of the product. For example, for video apps, you can push more and more accurate content to users, allowing users to spend more time on the app.

Adding usage scenarios actually means adding functions or services. For example, WeChat originally only had text and image content such as official accounts, but now has video accounts. Similarly, Douyin originally only had short videos, but now has live broadcasts. Based on the original functions and services, new services with similar logic are added to form new scenarios. This can also extend the user life cycle.

It is also common to use an incentive system, such as a points system, a membership system, and a user growth system. Most platforms have at least one, and the giants may have all of them. Taobao and JD.com, for example, consist of three parts. The Taobao gold coin system is a points system. Users can earn coins through various tasks. The coins can be used for lotteries or to offset cash. The 88 membership system is a membership system. 88 members can enjoy various joint membership services of other Taobao products, as well as discounts on some products, exclusive member benefits for some products, etc.

The retention and contribution of users who have purchased membership are definitely greater than those of ordinary users. Taobao Value is a user growth system. Users can continuously obtain Taobao Value through purchases + evaluations, and Taobao Value can enjoy different rights and interests, such as receiving coupons, buying 88 memberships at a discounted price, etc.

No matter which service users like, it will undoubtedly enhance user retention and activity.

Of course, the incentive system has costs, so when planning the incentive system specifically, it is necessary to calculate the benefits and costs, and different businesses are suitable for different incentive systems, depending on the business.

8. Prevention and Recall of Lost Users

This can also be considered a way to extend the user life cycle, such as using new discounts, new products or services to recall users.

There are two parts to recalling lost users. One is at the end of the user life cycle, which is to prevent loss. The other is to recall users after they have already lost them, such as sending a text message to recall them 6 months after they have lost them.

Preventing churn is actually better than recalling churn. Generally speaking, you can see from the user retention curve when the platform's users will churn. For example, if retained users churn quickly after 6 months, you can start to implement some churn prevention strategies in the 5th month.

Some products can use this strategy to recall lost users. For example, e-commerce apps can use old user recall strategies.

But this is not allowed for some products, such as dating apps. Users leave after finding a dating partner and their needs are met. This is normal and such users should not be recalled, otherwise it would be illogical.

IX. Final

Finally, let me summarize a few points:

First, the user retention curve should be drawn based on the actual period of users using the app. Some are daily retention, some are monthly retention, and some are annual retention. If you are not sure, look at your peers.

Secondly, based on the previous description, we can also summarize several significant characteristics of user retention:

1. The long-term value of a product is the prerequisite for user retention, which means that PMF must be established first;
2. The retention focus of products of different business types is different and needs to be determined based on the specific situation;
3. The richer the product functions and the more user behavior paths, the more difficult it is to achieve "retention + activation", and of course the greater the space;
4. Once the closed loop of user usage habits is formed, a suitable user incentive system can significantly enhance the efficiency of retention and conversion.

Again, user retention is a very important task, and it is even an important factor in determining the life or death of a product. We must pay attention to it and conduct periodic sorting and optimization.

User retention, like new user activation, is a part of broad growth. In a narrow sense, growth may only refer to conversion, but this is a relatively later link for many products or services. User retention and activity are relatively more advanced. If you want to have better conversion, you must have better retention and activity. This is a correlation, so we must attach importance to user retention.

In general, user retention is a more complex task than new user activation, and involves more work, so product managers should still spend more time on retention, look at the retention data every month, and focus on improving user retention in stages.

Today I will mainly share user retention. I hope my sharing will inspire you.

Author: Product Person Xuanqing

Source: Product Person Xuanqing