In Telegram (TG) marketing, many enterprises still limit their understanding of Telegram number screening to the "basic verification" stage—only judging whether a number is registered or empty, while ignoring the core value of account quality (e.g., whether it is a high-risk account, whether it matches target needs) and activity level (e.g., interaction frequency in the past 30 days). However, truly effective Telegram number screening has long been upgraded through multi-dimensional data analysis: via this analysis, enterprises can accurately identify high-value accounts and eliminate low-quality ones. With ITG Global Screening—a Telegram number screening tool—enterprises can further integrate multi-dimensional information such as "account attributes, behavioral data, and demand tags," achieving the leap from "basic verification" to "dual improvement of quality and activity." This transforms the Telegram customer pool from "quantity accumulation" to "coexistence of activity and value." Starting from the limitations of basic verification, this article will explain in detail how ITG Global Screening optimizes Telegram number screening results and improves account quality and activity through multi-dimensional data analysis.
Relying solely on "basic verification" for Telegram number screening fails to meet enterprises’ needs for account quality and activity. Instead, it causes 3 core issues that restrict marketing effectiveness:
- Limitations of Basic Verification: It can only identify "unregistered numbers, empty numbers, and disconnected numbers," but cannot detect high-risk types such as "virtual numbers, reported accounts, and accounts linked to banned devices."
- Quality Risks: High-risk accounts account for over 15%. Sending messages to these accounts easily triggers Telegram’s risk control, leading to restrictions on the enterprise’s own accounts and a significant drop in customer pool quality.
- Data Reference: Enterprises that only conduct basic verification have an average Telegram account ban rate of 35%, while those that integrate multi-dimensional analysis see the rate drop to below 5%.
A cross-border e-commerce enterprise only performed basic verification. Among 100,000 Telegram numbers purchased from third-party channels, 23,000 were high-risk accounts. After sending promotions, 3 main accounts were banned within a month, and the activity of the customer pool plummeted by 40%.
- Misconception in Basic Verification: Activity is simply judged by "whether there is a profile picture or nickname," failing to distinguish between "inactive accounts (with profiles but no activity for half a year)" and "truly active accounts."
- Low Activity: Inactive accounts account for over 30%. The open rate of these accounts is below 5%, and the reply rate is nearly 0—dragging down the overall activity of the customer pool.
- Real Case: A foreign trade enterprise only conducted basic verification, with inactive accounts accounting for 32% of its customer pool. The average open rate of pushed messages was only 8%. After eliminating inactive accounts through multi-dimensional analysis, the open rate increased to 35%, quadrupling activity.
- Blind Spot in Basic Verification: It does not analyze account demand tags, incorporating "high-activity but non-target demand" accounts (e.g., highly active student users) into the enterprise’s service customer pool.
- Wasted Value: High-activity non-target accounts account for over 25%. Although these accounts have a high open rate, they have no connection to product needs, with a conversion probability of less than 1%—wasting marketing resources.
- Comparison Gap: Enterprises that only perform basic verification have an average conversion rate of 2.5% for high-activity accounts; those that integrate demand analysis see the rate rise to 12%, doubling value.
Breaking through the limitations of basic verification, ITG Global Screening optimizes Telegram number screening results and improves account quality and activity through 4-dimensional data analysis: "account quality, behavioral activity, demand matching, and risk prevention."
ITG evaluates the basic quality of accounts through multi-dimensional data, eliminating low-quality accounts to ensure the "authenticity" of the customer pool:
- Account Attribute Analysis:
- Registration Duration: Prioritize accounts registered for over 30 days (new accounts have a retention rate of less than 20%, while these accounts have an authenticity rate of over 90%).
- Profile Completeness: Analyze the completeness of profile pictures, nicknames, signatures, and contact information. Accounts with over 80% completeness have an authentic user rate of 85%—far higher than the 30% of accounts with less than 50% completeness.
- Device Information: Identify "one device, one account" (high probability of being an authentic user) and eliminate "multiple accounts on one device" (low-quality accounts registered in batches).
A maternal and child brand used ITG’s account quality analysis to screen 38,000 high-value accounts matching "registered for over 30 days + 90%+ profile completeness + single-device account" from 80,000 Telegram numbers. The authenticity of its customer pool increased to 92%.
ITG integrates Telegram account behavioral data to accurately judge activity levels and improve the "activity" of the customer pool:
- Core Behavioral Indicators:
- Login Frequency: Mark accounts as "highly active (logged in ≥3 times in 7 days)," "moderately active (logged in 1–2 times in 7 days)," or "low active (no login in 7 days)"—prioritizing retention of highly active accounts.
- Interaction Depth: Analyze "group chat message frequency, channel likes/comments, and link click frequency." Highly interactive accounts (≥5 interactions in 7 days) have a conversion probability 6 times that of low-interaction accounts.
- Content Preference: Identify the type of Telegram content accounts frequently browse (e.g., "product reviews, promotions, industry information"). Highly active accounts that prefer "product-related content" have stronger conversion intentions.
A cross-border 3C enterprise used ITG’s behavioral activity analysis to screen 15,000 highly active accounts matching "logged in ≥3 times in 7 days + ≥5 interactions + 3C content preference." The conversion rate of its pushes increased from 3% to 18%, achieving both high activity and high conversion.
ITG extracts demand tags to achieve "dual matching of activity and demand," preventing high-activity accounts from failing to convert:
- Demand Tag Extraction:
- Industry Demand: Generate industry tags (e.g., "cross-border e-commerce procurement, maternal and child care, outdoor equipment") based on Telegram groups joined and channel topics followed by accounts.
- Consumption Tendency: Mark consumption tags (e.g., "price-sensitive, quality-focused, immediate procurement") based on account interaction content (e.g., "inquiring about prices, comparing products, asking about after-sales service").
- Demand Stage: Judge whether accounts are in the "awareness stage (browsing information)," "consideration stage (comparing products)," or "decision stage (inquiring about discounts)." Highly active accounts in the decision stage have the highest conversion probability.
A home goods brand used ITG’s demand matching analysis to screen 8,000 accounts matching "home renovation needs + decision stage" from high-activity accounts. After pushing exclusive discounts, the conversion rate reached 22%—far higher than the 1% of high-activity non-target accounts.
ITG integrates multi-dimensional risk data to eliminate high-risk accounts and ensure the "security" of the customer pool:
- High-Risk Type Identification:
- Virtual Number Detection: Accurately identify virtual numbers such as Google Voice and TextNow (retention rate <3%)—eliminating them to reduce invalid additions.
- Violation Record Check: Connect to desensitized Telegram platform data to mark accounts with "≥3 reports in 90 days or temporary bans"—avoiding associated risk control.
- Abnormal Device Monitoring: Identify abnormal devices such as "emulator-registered accounts and multiple accounts on the same IP"—these are mostly batch-marketing accounts with extremely low quality.
A SaaS enterprise used ITG’s risk prevention analysis to eliminate 18,000 high-risk accounts from 100,000 numbers. No accounts were restricted during subsequent pushes, and the quality stability of its customer pool increased by 80%.
Enterprises can use ITG Global Screening to conduct Telegram number screening with multi-dimensional data analysis—no complex technology required. In 3 steps, they can shift from "basic verification" to "dual excellence in quality and activity":
Based on enterprise needs, set multi-dimensional screening parameters in ITG, balancing account quality, activity, and demand matching:
- For Cross-Border E-Commerce (Beauty Products):
- Account Quality: Check "registered for over 30 days + profile completeness ≥80% + single-device account."
- Activity: Check "logged in ≥3 times in 7 days + ≥4 interactions."
- Demand Matching: Check "beauty and skincare needs + decision stage."
- Risk Prevention: Check "eliminate virtual numbers, eliminate violation accounts."
- Prepare Numbers: Organize Telegram numbers to be screened into Excel/CSV format (including country codes)—no additional processing required.
- Upload and Launch: Log in to the ITG backend, enter the "Multi-Dimensional Screening" module, upload the number file, confirm screening criteria, and click "Launch Analysis."
- Efficiency Advantage: Analyzing 100,000 numbers takes only 2–3 hours, with automatic background operation. Results will be notified via email upon completion.
A cross-border beauty enterprise uploaded 150,000 Telegram numbers. ITG completed analysis in 2.5 hours and screened 42,000 accounts matching "qualified quality + high activity + demand matching"—100 times more efficient than manual analysis.
Based on ITG’s multi-dimensional analysis report, conduct targeted operations to achieve dual improvement of quality and activity:
- Customer Pool Optimization:
- Stratified Filing: Classify screening results into "high-value high-activity (excellent quality + high activity + demand matching)," "high-value low-activity (excellent quality + low activity + demand matching)," and "low-value high-activity (low quality + high activity + no demand)."
- Dynamic Cleanup: Re-analyze with ITG monthly to eliminate accounts with "declining activity or rising risk levels" and add new high-value high-activity accounts.
- Marketing Strategy Adjustment:
- High-Value High-Activity Accounts: Assign 1-on-1 exclusive customer service and push customized discounts to improve repurchase rates.
- High-Value Low-Activity Accounts: Send "re-engagement content (e.g., new product reviews, exclusive benefits)" to boost activity.
- Low-Value High-Activity Accounts: Temporarily stop pushing marketing content to avoid resource waste.
A foreign trade enterprise adopted this strategy, increasing the proportion of high-value high-activity accounts from 20% to 55%. The overall activity of its customer pool rose by 60%, and marketing ROI tripled.
- Low Account Quality: High-risk accounts accounted for 18%, virtual numbers 12%, and only 60% of accounts were truly valid.
- Poor Activity: Inactive accounts accounted for 35%, with an average push open rate of 9% and a reply rate of 2%.
- Low Conversions: High-activity non-target accounts accounted for 25%, with an overall conversion rate of only 2.8%—wasting significant marketing resources.
- Improved Account Quality: Through multi-dimensional analysis, 25,000 high-risk accounts and 15,000 virtual numbers were eliminated. The proportion of truly valid accounts rose to 95%.
- Doubled Activity: 28,000 high-activity accounts were screened out. The push open rate increased from 9% to 42%, and the reply rate from 2% to 18%.
- Soaring Conversions: The proportion of high-value high-activity accounts reached 58%, and the conversion rate rose from 2.8% to 16%. Monthly sales increased by 4.7 times—achieving a triple win in quality, activity, and conversions.
High-activity accounts still bring no conversions if they do not match demand. Ensure the dual conditions of "high activity + demand matching" to avoid wasting resources on activity alone.
Adjust activity thresholds based on industry characteristics (e.g., B2B enterprises can relax to "logged in ≥3 times in 30 days," while B2C enterprises need to strict to "logged in ≥3 times in 7 days") to ensure screening results align with business needs.
Single-dimensional analysis is prone to distortion (e.g., "high-activity but high-risk" accounts need to be eliminated). Combine "quality + activity + demand + risk" for comprehensive judgment to avoid one-sided screening.
Basic tools can only complete 10%–20% of screening work. Professional tools like ITG Global Screening achieve over 80% multi-dimensional analysis—leading to vastly different improvements in account quality and activity.
Account quality and activity change dynamically (e.g., high-activity accounts may become inactive). Re-conduct multi-dimensional analysis with ITG monthly to ensure long-term stability of customer pool quality and activity.
In the era of refined Telegram marketing operations, Telegram number screening relying solely on basic verification can no longer meet enterprise needs. Multi-dimensional data analysis is the key to improving account quality and activity. By integrating 4-dimensional data—"account quality, behavioral activity, demand matching, and risk prevention"—ITG Global Screening achieves the upgrade from "basic verification" to "value screening," making the Telegram customer pool have both "high activity" and "high conversion."
Remember: The core goal of Telegram number screening is not to "eliminate empty numbers," but to "screen high-value accounts that are ‘high-quality, highly active, and demand-matching’." Choose ITG Global Screening, optimize Telegram number screening results through multi-dimensional data analysis, and transform your customer pool from "low-quality low-activity" to "high-quality high-activity"—achieving sustained growth in Telegram marketing effectiveness!
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