WhatsApp age detection, can you first screen users by age?

DoWhen WhatsApp acquires customers overseas, age stratification becomes a very real issue as the number of customers increases. For products such as clothing, beauty, games, education, home furnishings, software, and consumer electronics, content focus, product recommendations, and communication methods are often different for users in their 20s and users in their 40s. So many people will search for WhatsApp age detection, hoping that after getting a batch of numbers, they can first separate users of different age groups and then arrange follow-up marketing.

But here we need to clarify the concept first:WhatsApp activation status and user age are not the same type of data. A WhatsApp number alone cannot reliably determine a user's true age. Age information usually comes from registration forms, membership information, event registrations, order information, or information filled in by users. WhatsApp number detection is more suitable to confirm whether the number has been activated for WhatsApp, and then combine this result with the existing age tag.

Understand it this way,WhatsApp age filtering is much simpler.

First have the age information, and then see who has opened itWhatsApp

Suppose you have a batch of overseas customer information, which already includes mobile phone numbers, countries and age groups.

for example:

18-24 years old

25-34 years old

35-44 years old

Over 45 years old

What really needs to be dealt with at this time are two issues.

One is which numbers have been activatedWhatsApp, the other is how many people in different age groups can continue to communicate through WhatsApp.

If the two types of information are combined, a clearer customer list can be formed. for exampleUsers aged 25-34 who have activated WhatsApp, users aged 35-44 who have activated WhatsApp, and further segmented based on country and product interests.

This is better than simply taking a list of numbers and doing it directly.WhatsApp marketing is more convenient.

Because when the salesperson sees the list, he not only knows that this number can be contacted, but also knows what age group the user probably belongs to.

WhatsApp itself cannot easily check the real age

This is especially important.

Many people seeWhatsApp age detection may mistakenly believe that just entering the mobile phone number can directly check the age of the account owner. This is not the case.

WhatsApp activation detection mainly solves problems such as whether the account is activated and whether the number can be entered into the corresponding platform for screening. Age is user data and requires a clear data source.

For example, if a company operates its own website, users must fill in their birth year when registering; the event registration form requires age selection; and the membership system has saved age tags. At this point this information can continue to be used for customer classification.

If there is no age at all in the original data, and no user has actively provided relevant information, we cannot randomly give each person the information for the sake of marketing convenience.WhatsApp number guess age.

Therefore, age screening is best based on existing customer information, rather than confusing account detection and age judgment.

Why some businesses need to group by age

Age itself is not a universal label, but it is indeed very practical in some businesses.

When making consumer products for young people,18-24 year olds and 25-34 year olds may deserve more focus; when it comes to household products, people over 30 years old may have more related needs; when it comes to vocational education, software services, financial tools and other products, the focus of different age groups may also change.

The key is not which age group is better, but who the product is mainly suitable for.

If you sell services related to college students, then young users are naturally more important.

If you sell clothing or household products, older people may be more suitable for the usage scenario.

if doneIn B2B customer development, age may not be as important as position, company and industry.

At this time, there is no need to screen for age screening.

The closer the customer label is to the product, the higher the actual use value.

Digital Planet can be screened firstWhatsApp activation status

The company has obtained a batch of customer numbers through normal channels such as registration, orders, forms, activities, etc., and the original data already has age information, so it can continue to sort it out.WhatsApp status.

Digital Planet can be used in this step.

First unify the number format, process duplicate data, and then filter through Digital PlanetWhatsApp has been activated as a user. After filtering, merge the WhatsApp status with the existing age group field to get a clearer customer grouping.

For example:

USAWhatsApp users aged 25-34

FranceWhatsApp users aged 35-44

ThailandWhatsApp users aged 18-24 have been activated

JapanWhatsApp customers above 30 years old

Customer sources can be added to these groups later.

For example, the same25-34 years old, it can be divided into different types such as advertising forms, official website price inquiries, historical orders, and member registration.

In this way, Digital Planet is responsible for numbers andWhatsApp enables filtering, and the company's original customer data is responsible for the age tag. Combining the two fields is much more practical than looking at one field alone.

Being of the same age does not mean that you are a precise customer.

Suppose a product is mainly aimed atFor users aged 25-35, screening out a batch of WhatsApp numbers that have been opened for this age group does not mean that these people will buy it.

Age just meets a condition.

You also need to continue to look at where the customer comes from, what products they have paid attention to, whether they have taken the initiative to inquire, and whether they have closed transactions before.

For example, both users are30 years old, all open WhatsApp.

User A took the initiative to leave his contact information through the product inquiry page and also asked about the price.

User B just signed up for a normal event and did not have any product requirements.

Sales time is limited,User A should obviously take priority.

soThe precise users of WhatsApp cannot be determined by age alone.

Age is suitable for the first level of grouping, and real behavior is more suitable for determining the follow-up sequence.

There is no need to divide the age groups too finely.

When actually doing data compilation, it will be difficult to use if the age is too detailed.

IfThe 18-year-old, 19-year-old, 20-year-old, and 21-year-old are all separated into separate lists. It is difficult for sales to design different content for each age, and it is unnecessary.

A simpler way is to divide several intervals according to business needs.

For example18-24 years old, 25-34 years old, 35-44 years old, 45 years old and above.

If the product range is very narrow, you can also adjust it yourself.

The point is not to use a certain age classification uniformly, but to make the grouping convenient for subsequent marketing.

If the salesperson doesn’t know how to use a customer label after reading it, it means that the label is meaningless.

The same age group should also be divided again according to needs

After WhatsApp age screening is done, you can continue to look at product interests.

for exampleAmong users aged 25-34, some are paying attention to product A, some are consulting about product B, and some are just registered members.

If they are all put into one table, even though the age labels are the same, the actual communication content will still be very confusing.

A more practical division can become:

25-34 years old +A product consultation +WhatsApp has been activated

25-34 years old + Purchase history + WhatsApp activated

35-44 years old + B product inquiry + WhatsApp has been activated

At this point, sales basically don’t have to guess anymore.

When you see the customer tag, you will know what kind of group the other party belongs to, what they have paid attention to before, and what platform they can currently communicate with.

WhatsApp age screening finally has to go back to chat content

After the data is divided, the communication content must also be adjusted accordingly.

Young users may be more accepting of short, direct, and visual content; older people may pay more attention to product details, after-sales, price, and use value. However, these can only be used as a reference for content adjustment, and cannot fit all users into a fixed personality according to their age.

When actually chatting, it still depends on what questions the customer asks.

If the user asks about the price as soon as they come up, answer the price-related content; if they ask about the function, solve the functional problem first; if the purchase quantity has been explained, do not continue to send basic introductions.

Age tags mainly help with early grouping and should not replace real communication.

How to really understand WhatsApp age detection

If you only have a batch of phone numbers in hand, the first step should be to compare the number status andThe WhatsApp activation status is clearly organized.

If the customer database already has age information, then add the age field toWhatsApp detection results combined.

If there is no source of age, don’t package simple number detection as true age identification.

A more reasonable process is simple:

Already have customer information → Remove duplicate numbers → WhatsApp activation detection → Merge age tags → Continue classifying by country and product → Arrange sales follow-up.

Digital Planet is responsible for number sorting andWhatsApp users are screened, and age information comes from the company’s existing customer information. Only when the two parts are combined can a truly usable group of people be formed.

Age tells you which category the customer probably belongs to.The WhatsApp status tells you whether you can continue communicating through this channel. Only by understanding the two separately and putting them into the same customer table can the filtering results be truly useful.

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