How can financial management apps scientifically formulate activation strategies?

In the era of mobile Internet, daily active users are one of the important criteria to reflect the popularity of a product. At the same time, because most APPs adopt a business model of traffic monetization, the higher the daily active data, the stronger the bargaining power.

In the mobile Internet industry, the number of daily active users (DAU for short) is a very important concept, which can determine a company's financing scale and development prospects to a certain extent. This is because daily active users not only directly reflect the degree of users' love and dependence on the product, but also directly affect the profitability of the product.

Currently, most APPs still adopt the business model of traffic monetization. APPs with higher daily active users have higher bargaining power when negotiating with advertisers and investors. Therefore, the vast majority of Internet companies attach great importance to daily active data and will adopt corresponding operational measures to increase daily active users as much as possible.

However, products in different life cycles do not pay exactly the same attention to daily active users. The focus of product operations in the MVP (minimum viable product) period is on how to acquire customers efficiently, while the PMF (product/market fit) stage and relatively mature products will pay more attention to daily active users.

This article takes a financial management app in the PMF stage as an example to share with you how to formulate scientific strategies to quickly increase daily activity.

Background: This financial management APP supports online promotion and sales of financial products. It is currently in a rapid growth stage. The current operating goal is to steadily increase daily active data.

So how to improve daily activity data?

1. Clearly define the definition of daily active users

What is daily activity? Different companies have different definitions of daily active users.

For example, under normal circumstances, APP statistics platforms believe that daily active users refer to the number of users who open the APP every day, which is also the industry's broad definition of daily active users. However, some Internet companies have their own definition of daily active users. Based on their own business attributes, they believe that only users who use a specific function or trigger a specific behavior on that day are considered daily active users. The daily active users referred to in this financial APP are daily active users in a broad sense, that is, the number of users who open the APP every day.

After clearly defining the definition of daily active users, we can analyze the historical data of daily active users in a targeted manner, analyze the problems, and formulate operational strategies that can effectively increase daily active users.

2. Analyze historical daily activity data

We once did data analysis on a financial management app. Through statistical analysis of historical data, we found that the daily active users of the app were composed of two parts: new users who opened the app for the first time that day and old users who had opened and experienced the app before.

However, the number of old users on that day was much smaller than the cumulative sum of new users every day before that day. It is speculated that there may be the following two problems:

• Old users are lost and no longer use the app;
• The old user has not uninstalled the APP, but just did not open and use the APP that day.

Therefore, we recommend that the financial management APP can track and analyze the daily user retention rate through the corresponding data statistics platform.

We observed the number of daily active users, weekly active users, and monthly active users of this financial management APP over a longer period of time. Finally, we found that the number of daily active users of this financial management app fluctuated greatly, but the number of weekly active users fluctuated relatively little. We believe that this is most likely because the financial management app is a low-frequency app and users will not open and use the app every day, so the number of daily active users of the financial management app varies greatly. At the same time, we also found that the retention attenuation curve of the financial management APP tended to flatten out after 2 weeks, which means that the new user retention cycle of the financial management APP is about 2 weeks.

The above is the whole process of financial management APP analyzing the active cycle ratio of daily active users through the data statistics platform. In summary, we draw the following three conclusions:

• The user retention rate of this financial management app is low;
• The opening frequency of this financial management APP is low, which is a low-frequency application;
• The user life cycle of this financial management APP is relatively short.

3. Prescribe the right medicine for the right situation, formulate scientific strategies, and improve daily activity data

Next, we worked with the financial management APP to conduct an in-depth analysis of these three key issues and develop targeted activation strategies.

1. Let’s solve the retention problem first

Generally speaking, there are three main factors that affect APP user retention rate: channel user quality, product design (visual and interactive), and the characteristics of the product itself. There are short-term retention and long-term retention. For each retention cycle, the operators need to overcome different problems.

Next, we start from the entire life cycle of users and obtain a user experience map as follows through data analysis and user interview feedback to explore the specific factors that affect retention.

This user experience map can help operations and product managers analyze the following issues more clearly:

• As a financial management app, what is the user life cycle like?
• What is the user’s main operation process within the product? What do users care about at each key node?
• How should products satisfy users’ needs? (Pain points and needs)

At the same time, combined with the buried data of user behavior paths, we can clearly understand how users use the products, what proportion of users ultimately complete the process of purchasing financial products, and how satisfied users are with the products.

Based on the summary and analysis of the interview results and embedded data, we found the following problems:

Customer acquisition:

• The matching degree between users from certain channels and APP is low. These users open the APP and leave immediately without continuing to use the product. (Conclusions can be drawn by analyzing channel data)
• The registration and login process of the APP is complicated, which leads to user loss; (data analysis can draw conclusions)

Experience:

• Did not understand the product introduction of the financial product and left after hesitation; (path analysis and page heat map can draw conclusions)
• The investment amount of the financial product is too large; (user feedback can be obtained)
• Not very trusting of the platform; (from user feedback)
• Unable to judge whether the financial product is suitable for oneself; (user feedback, combined with path analysis and funnel analysis can draw conclusions)
• The payment process is complicated and consumes the patience of users; (Conclusions can be drawn from user feedback and path analysis)

Usage:

• Cannot find the revenue interface of purchased products; (Page heat map and path analysis can draw conclusions)
• Not knowing that the financial management is due; (path analysis)
• There are thresholds for transferring funds out. (User feedback)

In response to the above problems, the financial management APP can develop targeted and feasible solutions.

Customer acquisition:

• Marketing personnel adjust channel delivery strategies;
• When promoting externally, we seek endorsement from large authoritative organizations, improve safety certification, and emphasize the safety, fairness, legality and compliance of the platform;
• Re-optimizing the registration process, such as adding a one-click login service, can significantly shorten the APP registration process, provide users with a better experience, and reduce user loss during the registration process.

Experience:

• Combine user registration data and third-party data to evaluate the user's financial management experience and risk resistance, and recommend more accurate financial products to users;
• Enrich the variety of financial products;
• Redesign the way product information is presented and set standards for in-product information: clear, accurate, and structured;
• Pre-send coupons and other incentives to new users to lower the threshold for use, allowing new users to complete the purchase process and strengthen their trust in the platform;
• Optimize payment process;

Usage:

• Optimize APP page design and interaction methods;
• Reset the trigger mechanism for in-product and out-of-product message push;
• Lower the withdrawal threshold and process;
• Optimize the user help guidance process and page expression;

The above is only a preliminary plan, and the feasibility and implementation priority of the plan will be discussed in depth later.

2. How to increase product usage frequency

The frequency of product usage is often related to the characteristics of the product itself.

Let’s take two extreme examples: daily communication products attach great importance to daily active users, but travel products often use monthly and quarterly active users as evaluation indicators. Financial products are also tool-based platform products, so in order to increase the frequency of user usage, it is necessary to conduct a user group analysis: What kind of users have a high frequency of use? Find this group of high-frequency users, analyze their characteristics, and then formulate operational strategies to gradually guide low-frequency users into high-frequency users.

We refer to the current business model of the financial management app and make the following assumptions:

• The more financial products users buy on the platform, the more frequently they open the app;
• Users with more remaining budget will open the APP more frequently to select financial products.

In other words, highly active users are related to capital investment and the number of products purchased. Based on this assumption, we can use existing business data for verification (the following data are all simulated data and are for reference only).

The relationship between the number of financial products purchased and the next week retention is as follows:

Weekly activity definition: How many days a week do you open the app?

The relationship between purchase amount and weekly activity is as follows (the division of the amount depends on the division of the purchase amount of existing purchasing users. It is recommended to take the median and mean to observe the distribution of investment amount):

The above data basically verifies that the investment amount is positively correlated with the number of products purchased and the frequency of use. It is recommended to focus on the following three data: the first purchase of a product, the third purchase of a product, and the purchase amount exceeding RMB 10,000.

Several problems arise at this time:

• What is the threshold for first-time purchase?
• Where is the threshold for the third purchase?
• How to increase the amount of independent investment by users?

When we were studying retention issues, we found that the biggest doubts among first-time purchasing users were: platform trust > product fit > product expression. Based on this, our solution is:

• Product publicity, as above;
• There are two ways to do this within the product: launching low-threshold financial products with stable returns; and optimizing product expression.

So what is the threshold for the third purchase and investment amount exceeding 10,000? We found that the distribution of investment funds among user groups is mainly investment budgets, which is inconsistent with the expected returns of purchased products.

Our solution to this is:

• Analyze user tag features
• Provide more diverse products

The above is to attract users to actively open the APP through product design and guidance. Another way is to motivate or encourage users to open the APP through some operational activities.

Enrich product usage scenarios and use high-frequency functions to drive low-frequency functions:

Alipay has a tree-planting game, which uses the energy generated by payments, sign-ins, etc. to feed the seedlings, allowing users to continue to open Alipay even in scenarios where they do not need to use Alipay. This is also one of the reasons why Alipay is willing to continuously expose this game on the homepage to guide users to play it.

Pure financial management apps need to explore the target users’ preference for certain types of functions. This requires almost no innovation; just look at how mainstream financial management products work. For example, adding accounting functions, pushing financial management information, etc.

Promotions:

Use some preferential information to attract users to open the APP actively. This is highly dependent on the construction of product and user contact channels: message push, SMS, in-product advertising space, and personal notification information system.

Design user incentive system:

By building a set of behavioral reward mechanisms, such as point systems and sign-in systems, users are encouraged to use the product frequently.

External arousal:

Place advertisements in other apps to encourage users to open and use this app.

3. How to extend the user life cycle

As we all know, most products have a ceiling and will face the problem of product transformation after operating for a certain period of time.

Here are two examples.

First, it is a tool product. From 2012 to 2014, tool apps were a very popular category of product. However, with the disappearance of the demographic dividend, the advantage of tool-based apps that bring their own traffic no longer exists. Tool products often focus on a single function to meet the needs of users in a specific scenario. In order to extend the user life cycle and retain users, tool APP developers or companies will subsequently develop new products to meet users' new needs.

There is another type of product that has a certain degree of periodicity in itself, such as maternal and child apps. For expectant mothers, they can use mother and baby apps to learn about pregnancy care in advance. Once the baby is born and the woman's identity changes from an expectant mother to a mother, she will expect more mother-and-baby apps on her mobile phone to provide parenting-related content. At the same time, as children continue to grow (from 0 to 1 year old and then to preschool age), women’s functional demands for mother and baby apps will also change. If the mother and baby apps installed on their mobile phones cannot meet their changing needs for parenting knowledge, they may become lost users.

This issue requires operators to look beyond the perspective of their own products. In order to enter the fiercely competitive market, operators will enter the market with a functional point that has unique advantages in their own products, gain seed users, and then continue to expand and build new functions around this core functional point.

However, when each company first develops and promotes its products, it has already established user awareness, and its service target is also that group of core users. Therefore, adding more functions to existing products may not only increase the difficulty of use for existing users, but also make it difficult to attract accurate new users.

Therefore, operations personnel need to carefully delve into the user's actual usage scenarios and think about what a user should do before using this core function and what he should do afterwards? This will help us discover new business opportunities and continuously improve the product function matrix.

In summary, we see that the formulation and implementation of APP activation strategies involves the collaboration of multiple departments, such as marketing promotion, financial product business negotiations, clear operating mechanisms, business collaboration, etc. APP activation is not a small project. Operations personnel need to evaluate the priority of activation tasks based on current business priorities, and ultimately come up with a prioritized list of things to do and complete them step by step. At the same time, it also requires APP product managers, operations personnel, and developers to work together to promote it.

I hope that the activation strategies shared in this article can help APP operators and product personnel to open up new ideas. At the same time, we also recommend that operators should carry out the subsequent promotion work with specific goals and problems, keep relevant data records, and conduct in-depth analysis of the data, so as to solve existing deficiencies and problems with more scientific strategies and achieve long-term and healthy development of the APP!

Author: Personal recommendation

Source: Personal recommendation