How To Analyze Wechat Follower Personas?

Author:JINGdigital

5 MIN READApr 21, 2020The big data era brings unprecedented opportunities and challenges to marketing and media publishers alike. Targeted content delivery based on big data is the future and, increasingly, the present. Wechat, as one of the core marketing platforms in China, generates an immense amount of data every day. Understanding how to mine that data for useful information is the secret for making your Wechat strategy really fly. As we all know, in the era of big data, whoever gets the users gets the world. To achieve personalization of your marketing at scale, it’s first necessary to collect a large amount of user data and build a complete set of user personas with tag libraries, structured data, and attribute visualization. But what exactly is the value of knowing your Wechat followers? And how do you go about collecting this information? Personas are virtual models of real usersIn the big data era, web browsing, clicks, commenting, ratings are all pieces of the bigger behavioral puzzle. These fragments, when systematically collected, stored, and organized as a data set, tell us a lot – both directly and indirectly – about a user’s personality, habits, attitude, and buying readiness. This data set forms the basis of your marketing plans and can be referenced to reconstruct your consumers’ real needs. These comprehensive, 3-dimensional sets of user data form what we call “personas”. Personas are virtual models of real users and are based on the observed behavior of target customers. Enterprises will identify a group of target customers to uncover demographic attributes, behavioral attributes, social networks, psychographics, habits, and preferences for individual consumers. After continual refinement and updating, the data is abstracted to form a comprehensive virtual picture of a typical customer. This virtual picture is what we call the persona. Tagging users is central to the persona process. Tags are invested with specific meanings that describe the attributes and characteristics of real users. Tags make it convenient for companies to do statistical analysis. For different target audiences in different scenarios, the tags given to users often have different meanings. At the same time, a user’s behavior is highly context-dependent. When the context changes, the probability of the particular behavior changes as well. Therefore user personas should be dynamic. We generally divide up tags into two major types: dynamic and static. Static tags generally don’t change. They may include things like demographics, location, gender, educational level, etc. Dynamic tags, on the other hand, are more likely to change such as web browsing, search, registration, reviewing, rating, shopping cart activity, commenting, etc. In general, we say that personas using only static tags are 2-dimensional, whereas those using static tags and dynamic tags are 3-dimensional. Why do you need to set up WeChat user personas?1. More accurate ad targeting, improved user experienceWechat is China’s biggest social platform with more than 1.1 billion monthly active users and personas based on Wechat are highly representative of the true target market for your products. So do Wechat account operators really understand their own followers? What kind of people are they? What do they really want from you? Personas can help you understand your fans individually. They can also help you personalize your content and your product offerings so that you get the maximum ROI. WeChat account operators can send content to users based on gender, age, location, hobbies, and other tags mapped out in the persona to achieve precision marketing. Only by knowing who your real followers are can you be sure that you are rolling out the right marketing plan. The goal of creating your user personas is quite simple: know them better so you can serve them better. 2.Guide product developmentIdentify your core users for typical scenario analysis based on user personas. Use this analysis to find pain points and use these pain points to guide product development and product positioning. After that, you can roll out detailed process and planning. Only if you know who the product is for, and the functional demand behind it, can you successfully put your users in the driver’s seat. Carrying out user-oriented product research as part of the development process using a data-driven approach results in products with much-improved user experience. The native WeChat backend provides marketers with an important window for understanding users, such as seeing user growth and user attribute changing over time. These have important reference value, but in general, these data need much deeper data mining and analysis. Compared with the native WeChat platform, JINGdigital functions such as tagging, custom QR codes, tracking, and data analysis provide a rich toolkit for brands to establish and optimize user personas: track user behavior and transmit data in real-time to a backend database or mobile dashboards. After collecting a wealth of data, brands can gain a deeper understanding of their fans by creating segments and lead scoring.

The big data era brings unprecedented opportunities and challenges to marketing and media publishers alike. Targeted content delivery based on big data is the future and, increasingly, the present.

Wechat, as one of the core marketing platforms in China, generates an immense amount of data every day. Understanding how to mine that data for useful information is the secret for making your Wechat strategy really fly. As we all know, in the era of big data, whoever gets the users gets the world. To achieve personalization of your marketing at scale, it’s first necessary to collect a large amount of user data and build a complete set of user personas with tag libraries, structured data, and attribute visualization. But what exactly is the value of knowing your Wechat followers? And how do you go about collecting this information?

Personas are virtual models of real users

In the big data era, web browsing, clicks, commenting, ratings are all pieces of the bigger behavioral puzzle. These fragments, when systematically collected, stored, and organized as a data set, tell us a lot – both directly and indirectly – about a user’s personality, habits, attitude, and buying readiness. This data set forms the basis of your marketing plans and can be referenced to reconstruct your consumers’ real needs. These comprehensive, 3-dimensional sets of user data form what we call “personas”.

Personas are virtual models of real users and are based on the observed behavior of target customers. Enterprises will identify a group of target customers to uncover demographic attributes, behavioral attributes, social networks, psychographics, habits, and preferences for individual consumers. After continual refinement and updating, the data is abstracted to form a comprehensive virtual picture of a typical customer. This virtual picture is what we call the persona.

Tagging users is central to the persona process. Tags are invested with specific meanings that describe the attributes and characteristics of real users. Tags make it convenient for companies to do statistical analysis. For different target audiences in different scenarios, the tags given to users often have different meanings. At the same time, a user’s behavior is highly context-dependent. When the context changes, the probability of the particular behavior changes as well. Therefore user personas should be dynamic. We generally divide up tags into two major types: dynamic and static. Static tags generally don’t change. They may include things like demographics, location, gender, educational level, etc. Dynamic tags, on the other hand, are more likely to change such as web browsing, search, registration, reviewing, rating, shopping cart activity, commenting, etc. In general, we say that personas using only static tags are 2-dimensional, whereas those using static tags and dynamic tags are 3-dimensional.

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Why do you need to set up WeChat user personas?

1. More accurate ad targeting, improved user experience

Wechat is China’s biggest social platform with more than 1.1 billion monthly active users and personas based on Wechat are highly representative of the true target market for your products. So do Wechat account operators really understand their own followers? What kind of people are they? What do they really want from you? Personas can help you understand your fans individually. They can also help you personalize your content and your product offerings so that you get the maximum ROI. WeChat account operators can send content to users based on gender, age, location, hobbies, and other tags mapped out in the persona to achieve precision marketing. Only by knowing who your real followers are can you be sure that you are rolling out the right marketing plan. The goal of creating your user personas is quite simple: know them better so you can serve them better.

2.Guide product development

Identify your core users for typical scenario analysis based on user personas. Use this analysis to find pain points and use these pain points to guide product development and product positioning. After that, you can roll out detailed process and planning. Only if you know who the product is for, and the functional demand behind it, can you successfully put your users in the driver’s seat. Carrying out user-oriented product research as part of the development process using a data-driven approach results in products with much-improved user experience.

The native WeChat backend provides marketers with an important window for understanding users, such as seeing user growth and user attribute changing over time. These have important reference value, but in general, these data need much deeper data mining and analysis.

Compared with the native WeChat platform, JINGdigital functions such as tagging, custom QR codes, tracking, and data analysis provide a rich toolkit for brands to establish and optimize user personas: track user behavior and transmit data in real-time to a backend database or mobile dashboards. After collecting a wealth of data, brands can gain a deeper understanding of their fans by creating segments and lead scoring.

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