Analysis & Cases | A comprehensive understanding of the five dimensions of user portraits in the financial industry

1. Why does the financial industry need to create user portraits ?

Fintech has greatly changed the traditional marketing methods of the financial industry, getting rid of the pain points of previous single channels, scattershot marketing, and reliance on outlets and telephones for dissemination. Driven by big data, companies can say goodbye to scatter-net marketing and achieve low-cost, high-efficiency, precise and automated marketing. The financial consumption habits of the post-80s and post-90s consumers, who are the main consumers of financial enterprises, are also constantly changing. They do not like to passively accept financial products and services. With the help of big data, marketing scenarios can be integrated into users' lives frequently in ways that users like, creating a warm scenario marketing model, reaching users in a way that "caters to their preferences" and winning their hearts.

However, financial enterprises face a huge user base. How can they create user portraits that are suitable for the enterprises to analyze? We can start with the business scenarios of the enterprise.

2. What is the purpose of financial user profiling?

User profiling is to find the target users of potential products based on understanding user needs and consumption capacity, and to use the profiling information to develop products for users.

User portraits made from a business perspective are of great value to enterprises, so there are two purposes for making user portraits. One is to find target users based on business scenarios. Another one is to refer to the information of user portraits to design products or carry out marketing activities for users.

3. How are the dimensions of user portrait portrayal related to financial product business?

All things are difficult at the beginning. Due to the abundance of data, financial companies have difficulty in dealing with data of many dimensions when creating user portraits. Most companies always think that the more dimensions of user portrait data, the better, and the richer the portrait data, the better, making user portrait a huge and complex project. However, after spending a lot of effort on portrait creation, we found that only user portraits were left, which were far from the business and could not directly support business operations . In fact, the data dimensions involved in user portraits need to be highly integrated with the business of the product itself. In general, planning can be done from three aspects:

1. Population attributes and credit

Including information such as users' assets, work, income, education, etc., demographic information serves the purpose of reaching users, such as phone number, email address, address, office address, etc. This information can help financial companies connect with users and market their products and services to them.

2. Strong relevant information

For example, work and education have a greater impact on income and credit, which are strong related information. However, it is difficult to analyze the impact of information such as height and zodiac sign on consumption capacity from a probabilistic perspective, so it is not suitable to be included in user portrait analysis. Because this information has little impact on users' spending power and has little commercial value.

3. Qualitative Data

The purpose of profiling is to screen out target users. Quantitative information is not conducive to screening users, so it is very important to convert quantitative into qualitative. For example, avoid using quantitative methods such as 30 years old and annual income of 1 million yuan. Instead, you should use age groups (25-30 years old) and income ranges (500,000-1 million yuan), which will help to quickly locate the target user group.

4. After we have the user portrait, how should we reach the users?

From a practical point of view, financial enterprises need to be portrayed in combination with their business. We can divide user portrait information into five categories. They are demographic attributes, credit attributes, consumption types, interests and hobbies, and social attributes. The above basically cover the strong relevant information required for business needs, and combined with external scenario data will generate huge commercial value. Next, let’s take a look at how the five major categories of information in user portraits operate in actual user reach scenarios.

1. Population attributes

The main function is to reach users. Gender, age, phone number, email address, address, current geographic location, etc. are all demographic attribute information.

(Using geo-location, holiday marketing — insurance, WeChat payment)

2. Credit attributes

For example, occupation, income, assets and liabilities, credit score, etc. are all credit information. Used to describe the user's asset growth potential and income and expenditure situation. It can help companies understand users’ asset status and credit, and help locate target users.

(Using risk assessment-income attribute matching financial products-JD Finance)

3. Classification of consumption habits

Used to find high-frequency consumption and high-value users. It helps companies recommend services based on user consumption characteristics and accurately identify consumption characteristics. The conversion rate of this type of people is very high, and the N-time reinvestment rate is also correspondingly very high. For example, children's education, business travel, overseas travel, catering users, automobiles, mother and baby, financial management people, etc. If a company has consumption records of users, it can classify them into groups with certain consumption characteristics and then reach them through targeted marketing activities.

(Using consumption habit attributes - target financial management - GF Fund)

4. Hobbies

This type of information helps companies understand user interests and consumption tendencies, and is also conducive to targeted marketing campaigns. It should be noted that interests and hobbies may overlap with consumption characteristics, the difference lies in the different data sources. Consumption habits come from existing consumption records, but the items and services purchased are not necessarily for oneself, while hobbies and interests represent one’s true interests. For example, outdoor sports, movies, electronic technology, fitness, luxury goods, cooking, etc.

(Using life hobbies - electronic product consumption - lazy investment)

5. Social Information

Users’ behaviors and comments on social media often represent their inner thoughts and hobbies, and are characterized by high real-time availability, high conversion rates, and easy addiction to repurchase. For example, a user asks where are the fun and delicious places in Guangzhou? Where can I get the most discounts on travel hotel reservations? Which home purchase offers more discounts? Where is the best place for risk control in financial investment? These social information represent the multiple needs of users. If companies can understand them in a timely manner, it will help promote their products. However, it should be noted that these social information are dynamic and constantly changing. Remember to update the label classification regularly to achieve accurate promotion.

(Use life consumption scenarios - spend in person - Huabei)

Conclusion

Users’ current needs do not equal their permanent needs. We should use a growth-oriented mindset to reach users based on their behavior and growth stage.

Because change is the only eternal law. We should avoid using portraits to stereotype users, which would cause marketing content to not match users’ actual needs.

Source: Digital Business Cloud MA (Marketing Automation)