How to select the active window in the US data filter? The meaning, applicable scenarios and common misunderstandings of recent activity

When your team is sifting through customer acquisition data for the US market, one key parameter often gives people pause: Activity Window. Should I choose 7 days or 30 days? What does it mean to be active recently? Will choosing the wrong one waste budget and miss out on truly valuable users?

This article will start from the actual scenario of US data screening, dismantle the meaning of “active window”, common marketing adaptation strategies, and misunderstandings that are easy to avoid. Whether you are doing a Telegram community cold launch or WhatsApp private message promotion, choosing the right active window can significantly improve reach efficiency.

---

What is an active window? How to define “recently active” in screen numbers

In screening platforms such as KK-DATA, the “active window” refers to a time interval (such as the last 7 days, 30 days, 60 days), which is used to determine whether the social account (Telegram, WhatsApp, Line, etc.) corresponding to the mobile phone number has been online or detected during this time period. The detection result usually only returns “yes/no” and does not involve the chat content or private details.

Common ranges of active windows (7 days/14 days/30 days/60 days/90 days)

The window options supported by different platforms may be different. KK-DATA provides the following options for mainstream platforms such as Telegram, WhatsApp, and Line (subject to the actual display on the console):

• 7 days: very recently active, suitable for highly time-sensitive promotions.
• 14 days: short-term active, often used for verification groups in the cold start phase.
• 30 days (natural month): Taking into account both quantity and response rate, it is the default choice in most marketing scenarios.
• 60 days: active in the mid-term, suitable for brand warm-up or content marketing.
• 90 days: Long-term active, suitable for hoarding basic data or making secondary contacts.

How activity detection works (users don’t need to know the technical details)

The detection process is completely transparent to users: you only need to submit a list of numbers, and after selecting the platform and detection type, the platform will make a judgment based on the activity characteristics disclosed by the platform (such as the latest online time, frequency of sending and receiving messages, etc.). The result only outputs a “yes/no” conclusion and does not involve any chat content or personal privacy data**.

---

Why is it particularly important to select active windows for US data?

User habits, time zone distribution and marketing rhythm in the US market are significantly different from other regions. If you copy the Asian or European window settings, it is likely to lead to a significant decrease in the utilization of US number data.

US users’ usage habits and time zone effects

• Telegram vs. WhatsApp: In the United States, Telegram is more popular than WhatsApp, especially in the technical community and cryptocurrency field. WhatsApp is more used by Hispanic household users.
• Active Period: 8 pm to 11 pm Eastern Time is the peak period for social apps, while users on the West Coast are used to it later. If your testing time is during the day in the Eastern United States, some numbers may appear as “inactive.”
• Weekend vs. Weekday: Activity is significantly higher from Friday to Sunday, but lower on Monday morning.

Therefore, when filtering, not only the window length must be considered, but also the detection start time (some platforms support scheduled tasks) to ensure that the results truly reflect the online habits of the target group.

The marketing value of “recently active” in US customer acquisition data

• Open rate and click rate: Users who have been active recently (7-30 days) are 3 to 5 times more likely to open a private message or join a group than users who have been inactive for 90 days.
• Reduce the risk of account ban: Sending group messages to numbers that have been inactive for a long time can easily trigger the platform’s anti-spam mechanism, resulting in account restrictions.
• Accurate cold start: If you are a newly established Telegram group, the recommended invitation numbers should be users who are “active in the last 30 days”, and they are more likely to accept the invitation.

---

Three typical scenarios of active windows: near-term, mid-term and long-term

Scenario type	Recommended active window	Suitable for industry	Reason
Recent (7–14 days)	7 days or 14 days	Promotions, limited-time offers, financial loans (users in urgent need of funds)	The user is currently active and the response window is extremely short, suitable for fast-paced conversions.
Mid-term (30 days)	30 days	E-commerce promotion, education and training, SaaS trial	Users still maintain regular usage frequency, sufficient quantity, and balanced ROI.
Long-term (60–90 days)	60 days or 90 days	Brand content accumulation, secondary contact, CRM supplement	Users only log in occasionally, but they are still willing to receive brand information, so they are suitable for continuous cultivation.

Among them, the mid-term active window is most commonly used for U.S. data: it can not only ensure a sufficient sample size (the proportion active within 30 days in the U.S. number database is usually more than 40%), but also maintain a good response rate.

---

Common misunderstandings in active window selection (with pitfall avoidance guide)

Misunderstanding 1: The shorter the active window, the better, ignoring industry matching

Misconception: The 7-day window is the most accurate and the cost should be the lowest.

Actual situation: For industries such as finance and education, the user decision-making cycle is long, and those who are active for 7 days may only account for a small proportion (less than 5%), resulting in no data available. On the contrary, the 30-day window can cover more users with potential needs, and the payment ability is not bad. The per-item billing mode has a short window ≠ low cost, and a large number of numbers that are filtered out will also be charged (because the activity status of all numbers is detected, but only the ones that pass are returned).

Correction idea: First respond to the test based on the industry average (for example, small loan: 7 days; large loan: 30 days), do not apply one size fits all.

Misunderstanding 2: Regardless of national time zone differences, the 7-day window is uniformly used

Misconception: It is also “recently active” and is valid for 7 days worldwide.

Actual problem: The time zone span of American users is large (the difference between the Eastern United States and the Western United States is 3 hours), and the weekend activity pattern is different from that in Asia. For example, 7 a.m. on Monday morning in the Eastern United States is during the commuting period, and social app activity is low; while it is still early morning in the Western United States. If the detection task is performed in the morning of Eastern Time, a large number of active users on the West Coast may be missed.

Correction idea: When setting the detection time, refer to the peak period of the target population (for example, 9 p.m. Eastern United States), or select the “multiple detections and intersection” mode (if available).

Misunderstanding 3: Thinking that the larger the active window, the higher the cost (actually billed on a per-item basis)

Misconception: A large window means more data needs to be detected, so it is expensive.

Clarification: KK-DATA’s billing model is deduction based on the number of tests. Whether you choose 7 days or 90 days, the fee for testing the same number is the same. The window size only affects “whether the pass rate is high or low” and does not affect the unit price. Choosing a longer window may result in more passed numbers, which in turn reduces the unit cost of each passed number.

---

How to set the optimal active window for US number data?

Step 1: Clarify your marketing goals

• Newcomers (invite to join the group/follow the channel): A 14-30 day window is recommended to ensure that users have long-term retention intentions.
• Activation (promoting users to place orders/register): 7-14 days window to accurately reach the current active population.
• Second touch (return visit to old users): 60–90 day window to avoid disturbing too frequently.

Step 2: Test with reference to historical data of similar groups of people

Use KK-DATA’s Small Task Test function: First use 5,000 number samples to test three windows of 7 days, 30 days, and 60 days respectively. Compare:

• Pass rate (active number)
• Follow-up message opening rate (can use third-party analysis)

Recommendation: Don’t just rely on the first test, repeat it 2 to 3 times and take the average to eliminate occasional fluctuations.

Step 3: Combine KK-DATA’s real-time price and task overview functions

When creating a task in the console, an estimated cost (based on detection type and quantity) is displayed. You can adjust the window at any time and observe changes in costs - in fact, only the unit price of the platform (such as the unit price of Telegram active detection) affects the total price, and window modification does not affect the unit price. Use the task overview to confirm the final number of numbers before submitting.

---

In the US data filter, how does the active window match other filter conditions?

A single filter is often not granular enough. Taking American male aged 28-40, active in the last 30 days as an example, the steps to implement on the Telegram platform are:

1. Use the number source from KK-DATA (you can import CSV yourself or use the global number generation function to generate a US number).
2. Set the detection task: Select the Telegram platform and check “Enable detection” + “Activity detection” + “Gender detection”.
3. The active window is set to 30 days.
4. Keep the gender and age fields when exporting results, and filter out males and ages 28–40 in subsequent processing.
5. Export tgid for targeted message push.

The US data screened in this way is of extremely high quality and is especially suitable for B2B leads or mid-to-high-end consumer product promotion.

---

Summary: Choose the right active window to make your US customer acquisition data more accurate

The active window is not a fixed “optimal value”, but a dynamic parameter that is highly related to the industry, marketing rhythm, and time zone. Understand the principles behind it, combined with small-scale testing, and you can get higher response rates at lower costs.

Suggestions for follow-up actions:

• First try KK-DATA’s Free Number Generation Function to generate a batch of US numbers.
• Create a task with 1,000 items to test the 7-day vs 30-day window and compare the results.
• During the official running, set the window you need based on the test results.

---

FAQ

Question: When filtering US data, is it more appropriate to choose 7 days or 30 days for the active window?

Answer: It depends on your marketing intensity and industry. It takes 7 days for quick verification (such as holiday promotions); 30 days for regular customer acquisition (such as B2B leads). It is recommended to do A/B testing, first run 5,000 samples to compare the pass rate and subsequent message opening rate.

Q: Does the active window have an impact on the detection cost?

Answer: No. KK-DATA is charged based on the number of detections, regardless of the window length. Choosing a longer window will not charge more, but may detect more “existing” numbers; choosing a shorter window may miss a large number of recent inactive but valuable historical users.

Question: What is the difference between active window and “open detection”?

Answer: The activation test only determines whether the number is registered with the platform (such as Telegram), and does not reflect the frequency of use. On the basis of activation, the active window further determines whether there is any activity within the specified time period. In the US customer acquisition data, the response rate of users who have only been activated but have not been active for a long time is extremely low.

Question: I want to obtain US number data, but only focus on “users who have logged into Telegram in the past week”. How should I set it up?

Answer: Select “Telegram Activity Detection” in the KK-DATA screening task and set the activity window to “7 days”. At the same time, fields such as gender and age can be superimposed (such as middle-aged women exporting e-commerce), and the tgid can be exported for subsequent accurate push.

Question: Are the active window detection results 100% accurate?

Answer: There is no guarantee of 100%, but the platform is based on multi-dimensional behavioral characteristics and the accuracy is at the industry-available level. It is recommended not to rely solely on a single field, but to make a comprehensive judgment based on gender, avatar, last seen, etc. Please note that the test results are for reference only and are not responsible for accidental errors caused by changes in user behavior.

---

👉Log in to the console to start screening numbers Two-way contact customer service https://t.me/kkdata_robot For more documentation and function descriptions, please visit KK-DATA official website and Online Documentation