Complete Guide to A/B Testing Active Windows in Number Screening Systems: How to Filter High-Quality TG Active Users with 7/15/30 Days

Struggling with low reach rates and high account ban risks in TG community promotion? Often, it’s not the numbers themselves but the active window selected in your number screening system that’s wrong. Many operators habitually use a 30-day active window, only to find reply rates far below expectations, wasting budgets on large volumes of “passively online” numbers.

This article will walk you through the core impact of active windows on TG number screening and guide you step-by-step through A/B testing to compare data differences across three active windows: 7 days, 15 days, and 30 days. Ultimately, you’ll find the customer acquisition strategy best suited to your business scenario.

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Why Is the Active Window Critical for TG Number Screening?

Active Window is the time span used by the screening system to determine whether a number is in a “recently online” state. It’s not a toggle but a key parameter that decides how many “real people” you can eventually reach.

Choosing the wrong active window leads to two core problems:

• Too wide (e.g., 30 days): You’ll import a large number of users who only log in occasionally and have very low engagement. These users may have logged in only 1–2 times in 30 days and won’t respond to your private messages or community invitations, resulting in high jumps but low conversions.
• Too narrow (e.g., 7 days): While active quality is extremely high, the quantity may drop sharply. If your business is a content channel that requires a large user base to create momentum, a 7-day window may make you miss many potential followers.

Understanding which marketing scenarios (instant interaction vs. long-term nurturing) correspond to different windows is the first step to optimizing your screening process.

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Comparison of Active Window Features in Mainstream Number Screening Systems

Several mainstream B2B screening tools on the market have different focuses on active window settings. Based on publicly available information, let’s objectively compare platforms like KK-DATA, 007data, and thdata.

Common Settings for Active Windows (7 days, 15 days, 30 days, Custom)

• KK-DATA: In the console, when submitting a TG active detection task, it offers 7-day, 15-day, and 30-day presets. For special requirements (e.g., 21 days), the official statement indicates you need to contact customer service to assess technical feasibility.
• 007data: Also provides 7/15/30-day presets with a similar interface design, suitable for quick start.
• thdata: According to public information, thdata also mainly uses presets; customization requires contacting customer service.

Horizontal Comparison: Features, Pricing, and Data Export Differences

Comparison Dimension	KK-DATA	007data	thdata
Active Window Options	7/15/30 days; custom requires contacting CS	7/15/30 days	Preset windows; custom requires contacting CS
Gender Recognition	Output simultaneously (based on avatar)	Supported	Partially supported
Billing Method	Per record fee, no subscription	Per record fee, no subscription	Per record fee, no subscription
Export Fields	Supports tgid, wsid, active status, gender	Supports tgid, active status	Supports tgid, active status
Data Deduplication Warehouse	Built-in, cross-task deduplication	Supported in some versions	Not publicly disclosed

Note: The above comparison is based on public information. Specific unit prices and feature details are subject to the real-time console of each platform. Do not make purchase decisions solely based on this article; it is recommended to log into each platform for testing.

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Step-by-Step A/B Testing Guide for Number Screening System Active Windows (Using KK-DATA as an Example)

The following is a reproducible A/B testing workflow using the KK-DATA console.

Step 1: Prepare a Unified Number Pool and Deduplicate

The core of A/B testing is controlling variables. You need a standard set of sample numbers, recommended at least 2,000 records.

1. You can purchase a batch of TG numbers from a supplier or generate a batch using KK-DATA’s global number generator.
2. Import these numbers into KK-DATA’s data deduplication warehouse to ensure that the three groups of tasks use exactly the same number list, avoiding wasted balance due to duplicate detection.

Step 2: Create Three Groups of Tasks – 7 days, 15 days, 30 days

Log in to the KK-DATA Application Console, click “New Screening Task”.

• Detection Type: Select “TG Active”.
• Active Window (Days): Set to 7 days, 15 days, and 30 days respectively.
• Keep other settings consistent: Check “Gender Recognition” and “Export tgid”.
• Submit Task: Ensure sufficient account balance. The console will display an estimated fee before submission.

Step 3: Analyze Key Metrics from the Three Output Results

After tasks are completed, download the CSV result files. Focus on the following three metrics:

• Active Number Count: Directly reflects the user base under that window.
• Gender Ratio: If your business requires male/female users, you can filter with gender recognition.
• tgid Export Success Rate: tgid is TG’s UID, a prerequisite for accurate private messaging. Ensure the export field is complete.

Calculate Active Conversion Rate (Active Count ÷ Total Detectable Count × 100%). You will find: The 7-day window has the lowest active volume, but the conversion rate (subsequent reply rate) is usually the highest; the 30-day window has the largest active volume, but the quality is the most uneven.

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Data Interpretation: How to Choose the Best Active Window from A/B Test Results

By comparing the three sets of data, you can make decisions based on your business goals.

Scenarios for 7-Day Active Window

• Precise Invitations to High-Value Communities: e.g., paid courses, VIP communities. Requires immediate user response; 7-day window users have the highest engagement.
• Limited-Time Event Promotion: e.g., flash sales, live streams. You need users to act immediately upon seeing messages.
• Private Consulting Services: e.g., online medical consultations, 1-on-1 coaching. Extremely high requirement for reply timeliness.

If your A/B test shows that 7-day active users have a message open rate 3 times higher than 30-day users, even if the single screening cost is slightly higher, this investment is completely worthwhile.

15-Day vs. 30-Day: Which One Should You Choose?

• 15-Day Window: It’s a “balanced strategy”. It filters out extremely low-activity users (who haven’t been online for more than 15 days) while retaining most users with recent behavior. Suitable for community management, content subscriptions, and routine promotions.
• 30-Day Window: Suitable for content channels or long-term nurturing pools. For example, you need a large base user group to create community atmosphere, or your content is updated weekly, allowing users a longer window to reply.

Conclusion: There is no absolute “best” window. Your business model determines which one you should choose. Small teams are advised to run A/B tests first and let data speak.

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Common Pitfalls and Avoidance Guide for Number Screening System A/B Testing

In practice, these issues most often cause test bias.

• Non-random Number Samples: If group A numbers are brand new and group B numbers are zombie numbers from years ago, the test results are meaningless. Must use the same number pool for all three rounds of screening.
• Not Using Data Deduplication Warehouse: Many people repeatedly submit and import the same numbers in different tasks, resulting in duplicate charges. Use KK-DATA’s deduplication warehouse to automatically identify and skip already detected numbers.
• Ignoring Time Zone Effects: Detection time is UTC. If your target users are concentrated in a certain time zone (e.g., GMT+8), detection results may be biased. It is recommended to complete all tasks within the same natural day.
• Neglecting Gender Screening Bias: If your business requires users of a specific gender, remember to include the gender column when analyzing results to avoid male/female distribution affecting overall activity rate judgment.

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How to Apply Test Conclusions to Your Daily Customer Acquisition Process

Based on the best window selected from testing, establish a standard operating procedure (SOP):

1. Number Preparation: Import from KK-DATA Global Number Generation or suppliers.
2. Data Deduplication: Use the built-in deduplication warehouse to clean duplicate data.
3. Activity Screening: Select the optimal window determined by A/B testing (e.g., 15 days).
4. Additional Screening: Secondary filtering by gender, platform (TG/WhatsApp), etc.
5. Export tgid: Export data including tgid for subsequent sending.
6. Batch Sending: Use professional tools for outreach.

Remember: User behavior changes with platform policies (e.g., TG algorithm adjustments). It is recommended to review A/B testing results every quarter or half-year to confirm whether your selected window is still effective.

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Summary and Action Recommendations

There is no absolute optimal active window for number screening systems; you must find the one that suits your business through A/B testing. Even spending just one hour running three task comparisons can save you a large amount of ineffective budget.

Now, you can open the KK-DATA Application Console to register for free and use the documentation to learn how to set active windows. If you need one-on-one efficiency guidance, contact official customer service via @kkdata_cc.

• View complete product documentation: docs.kkdata.cc
• Learn more screening strategies, visit the blog: kkdata.cc/blog/

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Frequently Asked Questions

Q: Which is better between 007data and KK-DATA for active window detection?
A: Both support active day filtering, but specific window options and unit prices differ. 007data defaults to 7/15/30 days; KK-DATA also covers these three windows and supports custom parameters (some scenarios require contacting customer service). Both charge per record without subscription. It is recommended to choose based on real-time console prices and export formats. KK-DATA simultaneously outputs tgid and gender recognition, which may add extra value.

Q: Is the price the same for setting a 7-day active window vs. a 30-day window?
A: Pricing strategies differ by platform. Typically, screening for 7-day active users may have a slightly higher unit price than 30 days (due to more frequent status checks), but most platforms charge uniformly by detection type. For specific unit prices, please check each platform’s official pricing page in real time. For example, KK-DATA displays an estimated fee before submitting a task in the console.

Q: Why are the number of 7-day active users I screened very low?
A: This is normal. 7-day active users represent numbers that have logged in within the past week, usually accounting for less than 15% of the total. If your number pool is old data from years ago, the 7-day activity rate may be below 5%. It is recommended to have a sample size of at least 5,000 records, otherwise statistical errors will be large. You can also first use a 15-day window to check basic activity.

Q: Can I use different tools for A/B testing?
A: Yes, but ensure the numbers are the same, the detection fields are the same, and pay attention to data deduplication. Different platforms may have different active detection algorithms; for example, some define “active” more broadly (only looking at login records), while others integrate interactive behavior. It is recommended to use the same platform for testing to reduce variables.

Q: Does thdata support custom active windows?
A: According to public information, thdata provides preset windows (7/15/30 days); customization requires contacting customer service. KK-DATA also mainly uses presets. If you need unconventional windows (e.g., 21 days), it is recommended to compare multiple platforms or ask customer service if customization is possible. Currently, the KK-DATA team can technically support some customization requests (needs evaluation).