How to label Zalo users: age, gender, activity, and avatar are the four most practical

Doing VietnamWhen Zalo acquires customers and converts, many teams will start to create user tags, but it is easy to fall into a misunderstanding: the more tags are added, the more difficult it becomes to use. In the end, the system was filled with various fields, but customer service didn’t know who to contact first.

Really practical labels do not lie in having too many tags, but in directly guiding actions. For most projects, the four dimensions of age, gender, activity, and avatar are enough to support a stable set of hierarchical logic.

The point is not"There are many labels", but "the labels can be used".

WhyZalo tags don’t need to be complicated from the start

Many teams want to add all data dimensions right from the start, such as region, equipment, interests, consumption power, etc. But the problem is:

l The more tags, the higher the maintenance cost

l Data updates become more difficult

l It is difficult for customer service or sales to make quick judgments

The result is a lot of labels, but very few actually used.

A more practical approach is to first run through the four most basic and stable tags, and then gradually expand them.

Age tag: determines communication methods and conversion paths

Age is not used to filter out users, but to determine"How to communicate".

existIn the Zalo scene, you can make a simple layering:

l 25-35 years old: more receptive to new products, and the pace of communication can be faster

l 35-45 years old: Pay more attention to actual value and need to clearly explain the product advantages

l Over 45 years old: more emphasis on trust and stability

If the age difference is ignored, it is easy to have a mismatch in speaking skills and affect the response rate.

Gender tag: used to match products with needs

The role of gender tags is to help determine the direction of user needs.

For example:

l For e-commerce projects, there are obvious differences in preferences between genders

l For loan projects, different genders have different decision-making rhythms.

l Local services, different genders have different concerns about service content

However, it should be noted that the gender label is only an auxiliary and is not suitable as a filtering criterion alone, but is used to optimize the reach method.

Active tags: Decide who should be contacted first

Among all tags, activity is the one that most directly affects efficiency.

Can be simply divided into three categories:

Highly active users

l Recent usage behavior

l Prioritize access

l Improve conversion efficiency

Medium active users

l Have a certain frequency of use

l Follow up regularly

Low active users

l Not used for a long time

l Reduce frequency of reach or delay

Without active tags, customer service can easily waste time on unresponsive users.

Avatar tag: Quickly assist in judging account quality

The avatar looks simple but is very useful in actual screening.

Generally speaking:

l Accounts with avatars are more likely to be long-term users.

l There is no avatar account, it needs to be judged in combination with other tags.

Of course, avatars cannot alone determine user quality, but as an auxiliary judgment, they can improve screening efficiency.

Before labeling, you must first do a basic screening

A key point is: the premise of all tags is that the account itself is available.

Tags such as age, gender, and activity are meaningless if the number itself is not available.

In actual operation, you can use Digital Planet to do screen number detection before labeling.Invalid and abnormal data in Zalo numbers are first filtered out, and then age, gender, activity, and avatar tags are added to the valid data. This avoids wasting time on incorrect data. Digital Planet supports free trial screening test.

Four tags, how to combine them more efficiently

Tags are not used alone, but in combination.

A more practical combination is:

l Screen active users first (prioritize)

l Then look at age (determine communication methods)

l Let’s look at gender again (fine-tuning the vocabulary)

l Finally, use the avatar to help judge the quality of the account

This ensures that each step has a clear role, rather than repeated screening.

How to integrate the labeling system into the actual operation process

The value of the tag is only inIt is only reflected when it is "used".

It can be implemented like this:

l Automatically add basic labels after data import

l Automatically assign customers to customer service based on activity

l Different age groups use different speech templates

l Tailor marketing content based on gender and behavior

In this way, the label will directly affect the action, rather than staying at the data layer.

Common misunderstanding: there are many tags, but no one uses them

In actual operations, the most common problem is not the inability to label, but:

l Too many tags to prioritize

l The label is not updated and gradually expires

l Customer service did not adjust strategies based on labels

These will cause the label to lose its meaning.

The core of the labeling system is to make each step more clear

Zalo user tags, if used correctly, can make the entire process clearer:

l Who to contact first

l how to communicate

l Who deserves to be followed up on?

When there are clear answers to these questions, efficiency will naturally increase.

Starting from the four dimensions of age, gender, activity, and avatar, we first run through the basic tags and then gradually expand them. This is easier to implement and more stable than building a complicated system at the beginning.

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