1. Population geographical attributes

Users information, such as avatar, alias, ID, gender and geographical location, which we know in the background of WeChat, belongs to the population  geographical attributes and is the most basic information. When enterprises use these information to make decisions, they always feel inadequate. For example, when we logged in the WeChat official accounts platform and found that a large number of users who unfollowed, we naturally wondered: Who are these people and have they bought our products? Although you know who they are, what you want to know more is what you did, which made them lose interest in the business and leave. This requires understanding the user’s second attribute: behavior interest attributes.

2. Behavior interest attributes

As far as we know, a official account of 100,000 users will produce more than 1,000 w user behavior in a year. Most of the behavior can not be seen in the background of WeChat, such as: scanning QR codes, sharing geographical location, sending pictures, unfollowing (yes, your user leaving the account is the last behavior), and so on. This is what we call “user behavior attribute”.

For example, an offline promotional activity, involving 500 participants, 200 people scanning QR code to follow the WeChat official account, only 50 people left contact information, and finally 15 people were traded on the spot. It is worth thinking about: 150 people will not subscribe if they are not interested, but after following without leaving contact information, what did they do in WeChat? If there are opportunities, should enterprises conduct targeted research and conduct effective user behavior data analysis? And what did the 15 people who eventually completed the transaction see and do in WeChat? Know the enemy and know yourself and you can fight a hundred battles with no danger of defeat.

3. Life cycle attributes

The first two attributes, we stand in the user’s perspective to understand their appearance. The attributes of life cycle are to understand users from the business point of view, or to understand users’ purchasing intentions, and to judge their marketing/sales stage. B2C and B2B enterprises have slightly different processes, but essentially the same.

B2C corporate marketers pay more attention to the common characteristics of certain types of customer groups, such as the users participating in marketing activities, and the proportion of men and women who are converted into members. B2B corporate marketers are more concerned about the characteristics of individual sales leads, such as all potential customers who leave contact information online, and what information they have learned from WeChat and websites.

The marketing scenario of WeChat is complex and changeable. Sometimes we need to synthesize the above three user attributes for analysis and judgment. For example: whether the customers who ultimately buy products in different offline stores are converting points online or not, and what common characteristics do frequent converters have in terms of consumption capacity? There are many examples like this, which require the marketing staff to go deep into the various scenarios of WeChat marketing carefully, and make marketing strategies scientifically based on user attributes in specific scenarios.