An Analysis of Common Methods and Operational Procedures for Effective Filtering on Botim
In cross-border communication and overseas marketing scenarios, botim, as a widely used instant messaging tool in the Middle East, directly determines message delivery efficiency and user conversion costs based on number quality. Many teams invest heavily in botim marketing, but suffer from high message failure rates due to neglecting the crucial step of effective bot screening . In fact, the core value of effective bot screening lies in identifying unregistered numbers, inactive accounts, and low-activity users in advance, ensuring that every outreach meets basic communication requirements. Based on long-term practical experience, this article outlines five proven botim screening methods and provides specific processes to help practitioners systematically solve number quality issues.
I. Why is effective filtering in Botim fundamental to reducing the failure rate of sending?
Many companies encounter the following practical problems after investing resources in the Botim channel:
Unregistered Numbers : A significant proportion of the imported numbers were not registered with Botim, making it impossible to send messages.
Accounts banned : Some numbers have been suspended by Botim due to violations. Continuing to send messages will only waste channel resources.
Long-term inactivity : Accounts that have not logged in for more than 90 days have an extremely low open rate, even if they can receive messages.
Formatting errors : Basic issues such as missing international dialing codes and incorrect number of digits caused the API to reject the request directly.
Botim's core filtering logic is simple: before sending, verify that the number has receiving capabilities. This is not an option, but an essential step to reduce resource waste.
II. Pre-verification method based on number registration status
Operating procedures:
Obtain the original number pool : Compile a list of numbers to be filtered, ensuring it includes the correct international dialing code (e.g., +971 represents the UAE).
Calling the registration status detection interface : This involves sending a lightweight verification request (not an actual message) to the Botim server using technical means to determine whether the number has been registered.
Three types of states are marked :
Registered and active: You can proceed to the next screening process.
Unregistered: Removed directly, without wasting any sending resources.
Status unknown: Retained to the secondary review pool
Output the initial approved list : Only registered numbers will be retained for the next stage.
Practical advice : After the initial screening, retain 10%-20% for verification redundancy to avoid misjudgments due to network fluctuations.
III. Activity level assessment based on account avatar and basic information
Operating procedures:
Capture publicly available account information : including whether the profile picture exists, whether the nickname is in the default format, and whether the personal signature contains any content.
Divide into active tiers :
Custom avatar + non-default nickname + signature → High activity
Profile picture but default nickname → Active
No profile picture + default nickname → Low activity (recommended to remove)
Establish screening thresholds : Set minimum standards based on business objectives. For example, mass notifications may accept moderate to high activity levels, while high-end customer conversion requires targeting highly active users.
Batch output of tiered tags : Categorize numbers according to their activity level for subsequent strategy differentiation.
Key takeaway : Users with profile pictures typically have 2-3 times higher account retention and message open rates than users without profile pictures. This is especially evident on the Botim platform.
IV. Timeliness Filtering Based on Historical Online Time Periods
Operating procedures:
Collect recent online timestamps : Obtain the online records of the target number for the past 7-30 days through a compliant interface.
Statistical analysis of active time periods : Aggregating online behavior by hour to identify each user's high-frequency online windows.
Exclude accounts with excessively long offline activity : Numbers that have not shown any online activity for more than 15 days should be excluded.
Generate an active heatmap : Output the optimal reach time for each number in tabular form.
Typical scenario : UAE users are usually online between 8-11 PM, while Saudi users tend to be online in the early morning. Filtering by time period based on historical data can increase the open rate by more than 30%.
V. Batch Review Strategy Based on Number History
Operating procedures:
Establish a small sample test group : Select 5%-10% of the numbers from the initial screening to conduct real message sending tests.
Record return and delivery metrics :
Hard rollback: Number does not exist or is blocked
Soft rollback: A temporary failure that can be retried.
Successfully delivered: The recipient received the item normally.
Reverse correction filtering rules : If the hard rejection rate of a certain batch of numbers is found to exceed 15%, the registration verification logic of that source will be re-examined.
Forming an iterative closed loop : Feeding test results back to the screening rules in the first step to continuously optimize the threshold.
Practical note : Test messages should use neutral content (such as simple symbols or test identifiers) to avoid disturbing users.
Conclusion
The essence of effective botim screening is replacing blind sending with pre-verification. A complete quality control system is formed by four layers of screening: removing invalid numbers through registration status verification, judging activity levels through profile pictures and information, optimizing the outreach rhythm based on online time periods, and recalibrating rules through small-sample testing. In practice, professional tools such as ITG's full-domain screening can be used to standardize the process, thereby consistently controlling the baseline quality of numbers sent each time. Remember: a high-quality botim outreach always begins with effective screening.
ITG Global Screening is a leading global number screening platform that combines global number range selection, number generation, deduplication, and comparison. It offers bulk number screening and detection for 236 countries and supports 20+ social and app platforms such as WhatsApp, Line, Zalo, Facebook, Telegram, Instagram, Signal, Amazon, Microsoft and more. The platform provides activation screening, activity screening, engagement screening, gender/avatar/age/online/precision/duration/power-on/empty-number and device screening, with self-screening, proxy-screening, fine-screening, and custom modes to suit different needs. Its strength is integrating major global social and app platforms for one-stop, real-time, efficient number screening to support your global digital growth. Get more on the official channel t.me/itgink and verify business contacts on the official site. Official business contact: Telegram: @cheeseye (Tip: when searching for official support on Telegram, use the username cheeseye to confirm you are talking to ITG official.)