How to filter age on Telegram? Five judgment logics for refined operations

As a decentralized, highly anonymous instant messaging platform, Telegram does not provide explicit user age information, but age stratification is still a very critical link in refined private domain management and marketing reach. The target customer groups of different industries and products often have clear age group preferences, such as:

lEducation and training are more preferredYoung users aged 18-30

lInvestment finance tends toPeople over 30 years old

lEmotional companionship content adaptationMen and women aged 25-40

Therefore, it is important to use age screening to identify account characteristics, match communication skills, and improve conversion efficiency.A strategy that cannot be avoided in Telegram’s private domain operations.

How does Telegram determine a user's age? Comprehensive modeling in 5 dimensions

AlthoughThe TG platform does not provide an age field, but we can still make age tendency judgments based on behavior, content, social patterns and other dimensions:

1. Nickname semantics and language style

Nicknames often contain the user's self-perception of identity and age label. For example:

lYoung people’s nicknames are more network-based and express their individuality, such as"Little Huya", "Azhe Online", "Salted Fish Girl"

lNicknames for middle-aged people tend to be more stable or professional, such as"Mr. Zhang", "Entrepreneurship Alliance" and "Lao Li's Market View"

By building a semantic model and a nickname sample library, age group tendencies can be initially identified.

2. Channel Participation Types

There are significant differences in the channel attention types of users of different age groups:

l18-25 years old: animation, games, campus, and emotional channels

l26-35 years old: workplace growth, e-commerce shopping guide, gender emotions, lifestyle

lOver 35 years old: Finance, international news, blockchain, financial management, family education

By analyzing the type distribution of accounts joining channels, we can establish"Content interest-age tendency" mapping.

3. Rhythm of message interaction behavior

Young people tend to be more active in online social activities, as shown by:

lHigher response frequency, participation in voting and interaction

lExpress emotions in language and use emoticons more frequently

lThe active period is more at night

Middle-aged and elderly users often forward content and read long pictures and texts, their interactions are more rational, and their speaking style is relatively restrained.

4. Account registration and active time

Many registered earlyThe owners of TG accounts are more likely to be early Internet users or digital asset practitioners, and these users are usually over 30 years old. And more young users have joined in recent years.

Combining registration time, activity frequency, and device fingerprints, an age estimation model in the time dimension can be indirectly established.

5. Language and input method features

There are significant differences in the commonly used language styles and input vocabulary of different age groups:

lYoung people use it moreHot words such as "lie flat", "emo", "social fear" and "internal friction"

lOlder users’ language is more standardized and their expressions are traditional.

Among multilingual user groups, this contextual feature is especially applicable to regions with significant cultural differences such as the Middle East and Southeast Asia.

How to identify batchesWhat is the age profile of Telegram accounts?

Manual analysis is inefficient, and it is recommended to conduct batch determination through a system platform with algorithm support. Its standard process includes:

1.Upload the account information to be analyzed (nickname, username, channel joining record, activity information, etc.)

2.The system performs multi-dimensional identification of account characteristics

3.generateFour categories of labels: “18-25 years old tendency”, “26-35 years old tendency”, “35 years old and above tendency” and “unclear”

4.Output classified lists for community management, private message marketing, advertising layering, etc.

This set of identification processes is suitable for community operators, private chat delivery teams,The AI ​​interactive training system implements pre-user stratification to improve strategy accuracy.

What are the advantages of Digital Planet’s age screening capabilities?

existToday, as Telegram’s operational strategies become increasingly refined, the Digital Planet platform providesAge tendency identification modelHave the following capabilities:

lSupports semantic judgment of multilingual nicknames: Classification of age tendency of nicknames based on global multilingual corpus

lChannel type tag smart matching: Automatically identify channel audience age portraits and infer user group preferences

lBehavioral data modeling has rich dimensions: Establish a behavioral age index based on speech frequency, time period distribution, content and emotion, etc.

lSupport export of output label package: Can be directly exported in groupsList of accounts for different age groups such as 18-25 years old, 26-35 years old, etc.

lLinked with gender, activity and other tags: Supports multi-label cross-filtering to meet composite dimension needs under different promotion strategies.

More and more overseas brand owners and cross-border operators are completing their transactions through Digital PlanetAge identification and crowd stratification of Telegram users enable high-conversion script configuration and low-cost delivery layout.

Raising hopeFor the operation team of TG user reach efficiency,Data stratification based on age trends, not only optimizes the interactive experience, but also significantly improvesROI. Welcome to Digital Planet and start a more accurate Telegram user screening strategy.

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