LINE screens men and women, how to separate users of different genders for customer screening?

When dealing with Japan, Taiwan and some Asian markets,LINE is often used as a channel for customer communication and private domain maintenance. With more and more numbers in their hands, many people will think of LINE screening for men and women, hoping to separate male and female users first, and then arrange different marketing content according to the product.

The idea itself is not complicated, but there is one thing that must be distinguished first: LINE activation status and user gender are not the same data. Simply relying on a mobile phone number or LINE account cannot reliably determine a person’s true gender. A more reasonable approach is that the company has already obtained the gender information actively filled in by users through registration, membership information, event registration, order information, etc., and then combines it with the LINE activation test results.

After doing this,LINE's male and female screening is not about casually guessing the user's identity, but reorganizing existing customer tags and communication channels.

Which businesses have more practical value when divided into male and female groups?

Not all products need to be divided into men and women.

Clothing, beauty, maternal and infant products, accessories, some consumer goods, and hobby products often require basic group classification due to different product lines. For example, if a certain batch of products is mainly for female users, you can prioritize the selection of existing female customer information; for another batch of male products, you can create a separate list of male customers.

But if you are selling enterprise software, industrial equipment, logistics services, etc.For B2B products, gender is usually not as important as position, company, industry and procurement needs.

so doBefore screening LINE for men and women, first check whether this label will affect subsequent marketing.

If not, there is no need to add data processing steps for one more label.

If it is indeed related to the product, continue to point it out.

Gender information is best obtained from the original customer information

For example, the company's own membership system already has fields such as name, mobile phone number, country, gender, and purchased products. At this time, the existing information can be used directly.

During the advertising form, event registration, and website registration process, if the user actively selects gender, it can also be used as part of subsequent customer classification.

The biggest advantage of this type of data is that the source is clear.

After sales, if you see that a customer has been assigned to the female user group, you don't need to guess where this label came from, nor will you infer the true identity based on the avatar, nickname, or name.

If there is no gender information at all in the original database, it is not recommended to rely solely onDetermine gender by LINE avatar, username or mobile phone number. The avatar may not be the person's name, and the nickname may not have anything to do with the real identity. The probability of being misidentified is very high.

soLINE's screening of men and women is best based on existing customer information, rather than inferring from the appearance of social accounts.

Organize the numbers first, and thenLINE activation screening

Suppose there is now50,000 pieces of customer information, including mobile phone number and gender fields.

It is not recommended to split the watch according to men and women right from the beginning.

It will be smoother if you process the number first.

Unify the number formats of different countries, check whether the country area code is complete, and then remove duplicate mobile phone numbers. Because the same customer may have participated in the event and registered on the official website, it has appeared twice in the database.

After removing duplicates, do the same for the remaining independent numbers.LINE activation test.

In this way, you can first know which male users have already subscribedLINE, which female users have opened LINE, and then continue to create different lists.

The final data will be more practical than directly classifying men and women at the beginning.

for example:

Japanese female users +LINE has been activated

Taiwanese male users +LINE has been activated

Female Historical Buying Customers +LINE has been activated

Male event registration users +LINE has been activated

When sales see these labels, they basically know which category the customer belongs to.

Digital planet is fit for responsibilityLINE this level of filtering

If the enterprise already has customer numbers submitted by users or accumulated through normal business, the compiled data can be put into Digital Planet for processing.LINE related filtering.

Digital Planet here is mainly responsible for number deduplication,LINE activation status detection and basic data classification. The company's original CRM, membership system or form data is responsible for providing gender labels.

After the two parts of data are combined, a clearer picture can be establishedList of male and female LINE users.

For example, the company's own customer database has already recordedAfter screening 3,000 female users, it was found that 2,200 of them have already opened LINE. Then what really needs to be considered for subsequent LINE communication is these 2,200 pieces of data, rather than letting sales try all 3,000 numbers one by one.

The same goes for male clients.

This method of processing is relatively simple, and Digital Planet will not be written to be able to directly determine the user’s true gender. It is responsible forLINE number screening, male and female information still comes from the original customer information.

After sorting out men and women, we still have to look at where the customers are coming from.

This step is often more important than male and female labels.

Both are womenAmong LINE users, some come from the official website for active inquiry, some come from the advertising form, some are historical transaction customers, and some have only participated in one event.

These types of customers obviously cannot use exactly the same follow-up methods.

Users who inquire on the official website have a clear interest and can continue chatting directly from the product.

Historical customers can start with previously purchased products, usage, or new products.

Ad form users can first confirm which product they are interested in at that time.

If ordinary active users do not show demand for the time being, they can enter low-frequency maintenance first, and there is no need to forcefully promote products as soon as they come up.

Therefore, it is more practicalLINE customer classification is not just two folders for men and women, but continues to combine sources.

For example:

Female +LINE has been opened + official website inquiry

Male＋LINE has been activated + historical customers

Female +LINE has been activated + advertising form

Male＋LINE has been activated + product consultation

Once the list is organized in this way, sales will be much easier.

If the gender is consistent, it cannot be directly regarded as a precise customer.

Let’s say a product is primarily targeted at women.

Screening out 10,000 womenFor LINE users, it seems to be very accurate, but in fact it still needs to be narrowed down.

Some of these people may have never consulted about related products, or they may be ordinary members, and some may not have done business with the company for a long time.

Those who really deserve priority are often those who meet several conditions at the same time.

The gender is in line with the product direction and the number has been activatedLINE, the source of customers is clear, and there have been real behaviors such as inquiry, purchase, registration, and consultation.

If only women +LINE has been opened, which at best shows that the group of people and communication channels are basically matched.

Whether there is demand for purchase depends on behavior.

After men and women are divided into groups, marketing content should not simply follow a template.

Many people have done itAfter LINE screens men and women, it will go to the other extreme: all men will receive one set of content, and all women will receive another set of content.

It doesn't have to be that simple.

Gender can help with the first level of product classification, but the real chat still depends on what the customer is asking for.

For example, if a female user has clearly asked about the price of a certain product, she will answer the product question directly; if a male user is inquiring about another type of product, there is no need to forcefully recommend so-called male products because of gender labels.

Labels are there to help sales determine the direction, not to replace users’ real needs.

soLINE's precision marketing is more suitable to be used based on product interests, customer sources and actual inquiries, rather than just distinguishing between men and women.

The most practical processing sequence for LINE screening for men and women

If the company already has a gender field, the process can be controlled very simply:

First organize customer mobile phone numbers and unify the international number format;

Clean up duplicate data;

Keep the gender tag originally filled in by the user;

Filter by Digital PlanetLINE has opened a number;

BundleLINE status and male and female labels are merged;

Then continue to classify according to country, product interest and customer source;

Finally, it is handed over to sales for follow-up.

After doing this, gender is just a field in the customer profile.LINE is just a communication channel field, and the two will not be confused with each other.

What LINE really needs to solve in screening men and women is not to guess whether the user is male or female from the account number, but to combine the gender information already possessed by the company with the LINE activation status to make the customer list easier to use.Men and women can help divide products,LINE status can help classify channels. In the end, whether it is worth contacting first depends on whether the customer has real needs.

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