Vertical Market Active Filtering Guide: Precision TG Customer Acquisition Strategies for Crypto, Gaming, and E-commerce

In overseas B2B customer acquisition, Telegram has become the core battleground for Crypto/Web3 projects, game publishers, and cross-border e-commerce. However, vertical communities face a common problem: a large number of zombie accounts, bots, and long-term inactive silent users are hidden among community members. When promotion teams perform TG group adding, private message outreach, or airdrop distribution, a huge amount of messages are wasted on these invalid accounts, resulting in low conversion rates and high costs.

Vertical market active filtering is designed precisely to solve this pain point. By detecting account activity (e.g., whether there has been online behavior within 7 days, 15 days, or 30 days), you can accurately lock in high-value users and concentrate marketing resources on truly reachable and responsive targets. This article will focus on three typical scenarios—Crypto, Gaming, and E-commerce—and provide actionable filtering strategies and implementation steps.

Why Do Vertical Markets Need TG Active Filtering?

Before introducing the strategies, let’s look at the typical problems in different vertical markets:

Vertical Market	Main Pain Points	Value of Active Filtering
Crypto/Web3	Airdrop hunters and batch-registered bots mixed in; community activity data is inflated	Eliminate silent accounts, focus on real users and potential investors
Gaming Communities	High player churn, high proportion of abandoned accounts; private messages reach many users who have already left	Filter based on game update cycles to ensure reach to still-active players
E-commerce / Standalone Stores	Phone numbers imported from order data include many users who no longer use TG	Filter invalid contacts, improve conversion rates for promotional notifications and cart abandonment recovery

Active filtering differs from simple TG registration detection (which only verifies whether the number is registered with TG). It needs to confirm whether the user has had recent online behavior, so the data value is higher and the cost is correspondingly higher. For specific pricing, please refer to the official billing page.

Crypto/Web3 Communities: Active Filtering to Lock In High-Value Users

For Crypto project teams, Telegram communities are the core channel for user operations and airdrop distribution. However, communities are filled with batch-registered zombie accounts. Although these numbers are registered, they have been inactive for a long time. Such accounts are often used to farm airdrops or create fake community hype.

Verify Wallet Association and Community Participation

Recommended workflow:

1. Import target numbers: Obtain user TG accounts from community invitation records, airdrop registration forms, or third-party data sources.
2. TG registration detection: First confirm that the numbers are registered on TG, and remove invalid numbers.
3. TG active filtering: Choose “active in the last 7 days” or “active in the last 15 days” to filter out silent accounts that have not been online beyond the window period.
4. Export TGID: Some community platforms (e.g., Tonkeeper, various Telegram bots) support precise airdrop distribution using TGID. Through KK-DATA’s tgid export feature, you can directly obtain the TGID of filtered active users.

Combining activity data with community speaking frequency and interaction rate allows secondary filtering to ensure airdrops are distributed to users who truly participate in discussions and support the project.

Exclude Zombie Accounts and Bots

Most bot scripts do not have sustained real online behavior after registration. Through activity detection, you can identify their distinctive features—long intervals between logins, irregular patterns, no real social interaction. Using 7–15 day active filtering can eliminate most batch-registered invalid accounts, reducing the risk of airdrops being claimed by fake accounts.

Gaming Communities: Precision Group Adding Based on Activity

Gaming communities typically have short lifecycles and high player churn. Three months after a mobile game launches, more than 60% of community members may already be inactive. If you still message the full list of numbers, not only will conversion rates be low, but you may also trigger TG’s anti-spam mechanisms.

Filter Players Active in the Last 7/15 Days

Common strategies used by gaming companies:

• Short activity cycles (e.g., weekend ranking events): Use “7-day active” filter to reach only players who have been online in the past week.
• Persistent games (e.g., SLG): Use “15-day or 30-day active” to avoid over-filtering and missing potential returning users.
• A/B testing: Test different activity windows in batches to find the optimal configuration.

In practice, first create a filtering task in the app console, import player number data, then select “tg active” and specify the day window. After the task is complete, export the CSV and import the valid users into community operation tools for group adding.

Differentiate Player Gender and Interest Groups

On top of activity filtering, you can layer TG gender detection (based on avatar analysis). For example:

• Competitive games (e.g., FPS, MOBA): High proportion of male players; directly filter active male users.
• Otome or dress-up games: Focus on filtering active female users.

By applying dual filtering of gender + activity, targeted promotion efficiency is significantly improved, reducing user aversion caused by irrelevant private messages.

E-commerce / Standalone Store Promotion: TG Customer Acquisition for High-Intent Users

When cross-border e-commerce standalone stores conduct promotional notifications, cart abandonment recovery, or new product launches, they often import order phone numbers into TG for outreach. However, many order numbers may be from months or even a year ago. Users may have already deleted their TG accounts or stopped using TG.

Combine Order Data with Number Filtering

Steps:

1. Export customer phone numbers (with country codes) from the e-commerce backend.
2. Use KK-DATA’s global number generation module to supplement leads obtained from other channels (free generation).
3. First, run TG registration detection on all numbers to remove numbers not registered on TG.
4. For registered numbers, apply “15-day or 30-day active” filtering to lock in users who have been online recently.
5. Export the active numbers and import them into the marketing system for private message delivery.

Through two rounds of filtering, the reach accuracy can be increased from 20% to over 60%.

Multi-Round Filtering to Improve Conversion Rates

It is recommended to optimize customer acquisition costs with staged charges:

• Round 1: TG registration detection (lowest unit price, filters out many invalid numbers).
• Round 2: Active filtering on a subset of registered numbers (higher cost but outputs high-value users).
• Round 3: Based on budget, further filter active numbers by gender, platform (iMessage/RCS), etc.

Each step uses the data deduplication warehouse to avoid double charges for numbers already checked.

Implementation Essentials: Pipeline from Number Generation to Active Filtering

A complete vertical market active filtering workflow is as follows:

1. Number acquisition: Generate target numbers via the global number generation module (supports 240+ countries/regions, custom number range CSV import). Generation is free.
2. First screening: Submit a TG registration detection task to obtain numbers registered on TG.
3. Active filtering: Create a new task, import registered numbers, select the activity detection window (7/15/30 days), and wait for task completion.
4. Deduplication management: Use the data deduplication warehouse to ensure numbers are not charged twice across different tasks for the same batch.
5. Export delivery: Export CSV or TXT from completed tasks. Fields include number, active status, gender, TGID, etc.

Recommendation: Keep the number of numbers per task within 1 million and submit in batches to avoid timeouts. After the task is completed, you can receive results via Telegram notification.

Best Practices and Precautions

• Avoid balance waste: If the same batch of numbers requires multiple screenings (e.g., open first, then active), be sure to use the platform’s “data deduplication warehouse” to prevent double charges for already-checked numbers. Before submitting a new task, it is recommended to first import historical results for deduplication.
• Control single task size: Although up to about 1 million numbers are supported, for small-scale testing in vertical markets, first submit 50,000–100,000 numbers to observe detection speed and accuracy, then gradually expand.
• Watch the billing deduction timing: Filtering tasks are only charged after completion. Estimated costs are shown before submission. Insufficient balance will prevent creating new tasks.
• Utilize online documentation: Detailed steps and common error handling can be found in the user documentation.

Frequently Asked Questions

Q: For Crypto projects doing airdrops, is TG registration detection enough?
A: No. Airdrops usually require users to maintain a certain level of community activity. Registration detection alone cannot distinguish zombie accounts. It is recommended to add TG activity detection (e.g., active in the last 7 days) to exclude long-term inactive accounts, reducing the risk of airdrops being claimed by fake accounts.

Q: In game promotion, how do I choose between 7-day active and 30-day active?
A: It depends on the game’s update rhythm. For short activity cycles (e.g., weekend ranking events), choose 7-day active; for persistent games (e.g., SLG), choose 15–30 day active to avoid over-filtering and missing potential users. You can also test different windows in batches and compare conversion rates.

Q: Can e-commerce standalone stores use the generation module to randomly generate numbers and then directly perform active filtering?
A: Yes. The generation module is free. After generation, it is recommended to first run TG registration detection, then perform active filtering on registered numbers to reduce invalid charges. Note that generated numbers do not contain real users; they need to be combined with other channel data (e.g., existing order phone numbers) to improve outreach value.

Q: How can I export the filtering results for vertical markets? Can I import them into CRM?
A: Multiple formats such as CSV and TXT are supported for export. You can freely import them into CRM, email marketing systems, or upload them again for multiple rounds of filtering. Exported fields include (number, platform, active status, gender, tgid, etc.).

Q: Why is active detection more expensive than registration detection?
A: Active detection requires real-time or near-real-time confirmation of user behavior status, resulting in higher data acquisition costs. For specific unit prices, please refer to the real-time display in the console.

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Start Your Vertical Market Active Filtering Now

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• View operation documentation: https://docs.kkdata.cc/
• For customized solutions or bulk pricing negotiations, contact customer service: @kkdata_cc