How to use user tags to improve activity conversion rate?

In the field of operations , tags are usually a tool for classifying users, and the degree of tag refinement directly affects the operational results.

Because after labeling users, the operators will have a rough judgment about them: this person is the "Prince of Love Songs" and that person is the "Nightclub Girl". People with good ideas are called "encyclopedias", and those who are good-looking are called "Shenyang Peng Yuyan"...

In an era where refined operations are driven, the most important thing to improve the conversion rate of activities is to understand users and know what they want, and "labeling" is a good way to effectively solve this problem.

What are User Tags?

What are User Tags?

How many steps are there to label users?

• First, extract typical users from the crowd
• Then, break down the typical user’s information
• Finally, use general terms to extract labels from the disassembly information

Generally speaking, the user tags we mentioned are divided into two categories: "static tags" and "dynamic tags".

Static Tags

It usually includes the user's demographic attributes, such as gender, age, region, occupation, income, marital status... Its function is to help operators clarify the user's consumption capacity, consumption frequency and other characteristics.

Dynamic Tags

It usually refers to certain characteristics formed by user change information (some articles also call it "behavioral trajectory information"), including behavioral attributes and purchase attributes.

For example, we log in to Taobao App with our mobile phone, which products did we browse yesterday, which products did we browse today, how many times did we log in to the App in one day, how many items did we collect...

These can all be called user behavior information. The tags extracted from these behavioral information are the users' dynamic tags. Through these dynamic tags, operators can clearly identify which products the user is more interested in, thereby preparing for subsequent product recommendations.

Tag users

In order to make the whole process of establishing user tags orderly and rhythmic, we can divide it into the following two parts:

Collecting data

The basis for accurately labeling users is to have sufficient data support. Any labeling that is not based on data is rogue. In actual operations, we often accumulate data through primary and secondary information. The specific sources can refer to the following four:

1. Research reports and literature
2. Background data
3. Questionnaire survey
4. User Interviews

Analyze and extract keywords

When we have collected enough user data in the above way, we can start to process and analyze them and extract keywords that can describe user characteristics.

For example, if we are about to launch an operation targeting post-90s, we need to have some understanding of the personality traits and behavior preferences of this group. Through searching, we may obtain the following information:

• 199IT "Perspective on the Post-90s Generation: Social Behavior of the New Generation"
• Exclusive big data "Post-90s New Generation Social Network Preference Report"
• 360 Search "Insights into the Mobile Internet Behavior of Post-90s Users"
• China Big Data Industry Observation "2015 Post-90s Lifestyle Research Report"

Next, we may extract the labels of the post-90s generation from these data reports : social generation, Weibo, self-esteem, pressure...

Realizing refined operations is not a dream

When we have painstakingly extracted user tags from thousands of information, it means that we have mastered the basic characteristics and purchasing behavior of the target users to a large extent. By combining user information tags and making appropriate classifications during the operation process, more targeted activities can be carried out in the future.

The effect of tags is usually effectively demonstrated in the two stages of activity delivery and promotion.

Flexibly and accurately deliver campaigns

When it comes to campaign delivery, many people have a misunderstanding that accurate delivery is achieved by adjusting the location of the campaign information to high-traffic locations such as the startup page or banner image with just a few lines of code.

In fact, the precise delivery of the event begins as early as when you select the target users for this event. What can help you select targets effectively and accurately are the user tags we mentioned above.

Triggering user scenario perception

We are now in the era of big data, where information flows frequently. If we want to capture the user's attention, the most important way of operation is scenario-based operation. Activities are the best choice to trigger users' scenario-based perception.

By labeling users and centrally managing their attributes and behavior tags, different activities can be triggered for different users, allowing differentiated and accurate recommendations to enhance user experience and engagement, thereby increasing the probability of activity conversions.

Apps often use user tags to plan some reward activities for newly registered users, such as "Congratulations on completing your registration, you have received a 2,000 yuan privilege principal", "New users will receive a 188 yuan red envelope, click to receive it"...

In addition to the marketing activities mentioned above targeting newly registered users, you can also classify users by user tags and push trigger tests to certain paid users. Of course, we can set the attributes of the tested users (gender, region, etc.) in the background according to our needs to define the scope and get the information we need more accurately.

User tags are a visual form of user portraits. By accumulating a certain amount of data, tags that can describe the user's own attributes are extracted and then managed in a unified and centralized manner. When we make operational strategies, we can plan and push activities in a targeted manner according to the different needs of each time, which feels really great.

Mobile application product promotion service: APP promotion service Qinggua Media advertising

The author of this article is @操作合作伙伴. It is compiled and published by (Qinggua Media). Please indicate the author information and source when reprinting!