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In the process of market expansion in Vietnam,Zalo is still one of the most active social platforms among local users. How to accurately filter outof specified gender and ageZalo users, has become a key operating point for many marketing teams, brands and private domain traders.
In the past, we could only rely on manual judgment of avatars, nicknames, and interactive content."Guess" gender and age. In 2025, with the development of AI recognition and platform technology,Zalo gender age filterIt has become batch-based, precise and efficient.
This article will explain to you in detail:Zalo's latest screening technology principles, usage scenarios, efficient operation methods, and how to complete screening with one click through the Digital Planet platform.
Why is gender and age screening the first step to precise reach?
The first step in marketing is not"What content to send", but "to whom".
especially inOn social platforms like Zalo, excessively disturbing content will lead to risks of being blocked, blocked, and banned. And only inA clear picture of the target groupOnly under the premise of communication can it be valuable.
l Female users are more suitable for beauty, maternal and infant, education and other products
lUsers under 30 years old are more inclined to entertainment, e-commerce, and game content
lUsers over 35 years old focus on health, insurance, parenting, and investment
Batch accounts without gender and age tags are like a blind man trying to figure out the elephant, unable to accurately invest every resource.
Current mainstreamComparison of Zalo gender and age screening programs
1. Traditional manual judgment (low efficiency)
The earliest approach is to downloadZalo avatar, view nickname, look through chat history to determine gender and age group:
lCheck whether the avatar is male or female and whether it is young
lCheck if the nickname has a gender hint
lInfer age group based on interaction frequency
But this way:
lIt is difficult to operate if the amount of data is slightly larger
lJudgment is highly subjective and accuracy is low
lCannot be operated in batches and is only suitable for small-scale experiments
Suitable for personal use, not suitable for enterprises or large-scale operations.
2. Third-party plug-in tools (high risk)
Some plug-in scripts or crawlers claim to be able to"Recognize Zalo's gender and age", but mostly in the following ways:
lSimulated loginZalo account, read user information
lBatch crawlZalo public information for analysis
lInstall plug-in to automatically judge tags
The following problems exist:
lLogin requiredZalo account, easily blocked
lRecognition accuracy is not high, excludingAI judgment
lThe data structure is not uniform, difficult to export and use
lLegal compliance risks are high
Most project teams are inSuch tools will no longer be used after 2023.
3. Digital Planet Platform AI tag recognition (recommended)
Currently, the most secure, stable, and batch-operated method is to usedigital planet platformZalo account filtering function.
The core advantages are as follows:
l No login requiredZalo account, based on mobile phone number detection
l One-click identification of gender (male)/Female/Unknown)
l Automatically determine age group (18-25, 25-35, 35-45, 45+)
l filterableCombination conditions such as "active + female + 25-35 years old"
l Support one-time detectionMore than 100,000 pieces of data
l Export results in standard format for easy direct importCRM, SaaS system
Platform useAI conducts cross-modeling analysis on more than ten dimensions such as avatar, nickname, device behavior, etc., and outputs highly accurate user portrait labels, which is currently theclosestZalo official dimension filtering method.
Usage process:3 steps to complete Zalo tag filtering
No.Step 1: Prepare target mobile phone number
You can upload your existing mobile phone number pool, or you can customize designated groups through Digital Planet (such as northern Vietnam+Android users+women over 30 years old)
No.Step 2: Platform detection and marking
The Digital Planet backend system completes mobile phone number detection within a few minutes, including activation status, online activity, gender determination, and age group classification.
No.Step 3: Export data for use
ExportableActive accounts that are "opened + female + 25-45 years old" can be used for private message marketing, group promotion, text messaging, Facebook matching, etc.
Practical case: How to use it well in the e-commerce industryZalo tag filter?
A skin care product brand owner plans toTo expand agent users on Zalo, their goals are very clear:
lWomen aged 25-40
lWas inActive on Zalo
luseAndroid phone (easier to install APP)
They handed over the screening task to the Digital Planet platform, using onlyIn 3 hours, the following data processing was completed:
lRemove unregisteredZalo account
lEliminate zombie accounts with no active behavior
lreserve"Female + active + Android + 25-40 years old" user pool
lfinally obtained42,000 accurate accounts
After importing this data into their group-building system, the conversion rate increased by more than30%, and successfully developed 600+ effective agents.
SuitableWhat are the scenarios for gender and age screening in Zalo?
The following industries and teams are strongly recommended to useZalo gender age tag filtering function:
l Education and training: Find parent groups
l Beauty and skin care: targeting female users
l Maternity and baby products: reaching new mothers
l Health care: Targeting middle-aged users
l Foreign trade agent: screening entrepreneurial women
l Drainage team: improve the quality of private domain
lCRM system: complete data label dimensions
Only by finding the right people can we have the right marketing
Zalo is one of the most mainstream communication tools in Vietnam. Its account data structure is complex and not public. It is difficult to obtain core tags by relying on traditional means. But in 2025, with the development of AI screening and platform technology, we will finally be able to efficiently and safely identify the gender and age of users in batches, laying a solid data foundation for marketing and private domain operations.
Through the [Digital Planet] platform, you only need a list of mobile phone numbers to identify the person behind them with one click."People" to achieve precise delivery and low-cost conversion.
Act now, turn onThe journey of intelligent filtering of Zalo user data. If you need test samples or a quick trial, you can contact customer service directly.
digital planetis a world-leading number screening platform that combinesGlobal mobile phone number segment selection, number generation, deduplication, comparison and other functions. It supports customers worldwideBatch numbers for 236 countriesScreening and testing services, currently supports40+ social and apps like:
The platform has several features includingOpen filtering, active filtering, interactive filtering, gender filtering, avatar filtering, age filtering, online filtering, precise filtering, duration filtering, power-on filtering, empty number filtering, mobile phone device filteringwait.
Platform providesSelf-screening mode, generation screening mode, fine screening mode and customized mode, to meet the needs of different users.
Its advantage lies in integrating major social networking and applications around the world, providing one-stop, real-time and efficient number screening services to help you achieve global digital development.
You can find it on the official channelt.me/xingqiuproGet more information and verify the identity of business personnel through the official website. official businesstelegram:@xq966
(Warm reminder: When searching for the official customer service number on Telegram, be sure to look for the username.xq966), you can also verify it through the official website personnel:https://www.xingqiu.pro/check.html, confirm whether the business contact you is a planet official
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