Moj Data Screening
How to use Facebook group marketing to expand your businessHaving difficulty finding potential customers in overseas markets? The cloud control system generate
Botim private message data
How does MOMO use number filtering to improve communication efficiency?
How to use Facebook group marketing to expand your businessPrecisely target users based on age, gender, activity level, and online time, improving marketing efficiency.
Botim private message dataBatch exporting screening results supports unified management of accounts across multiple platforms, enabling rapid execution and implementation of promotional tasks.
BOTIM user group classifications? How can I find the right target users?
Batch exporting screening results supports unified management of accounts across multiple platforms, enabling rapid execution and implementation of promotional tasks.
Batch exporting screening results supports unified management of accounts across multiple platforms, enabling rapid execution and implementation of promotional tasks.
BOTIM user group classifications? How can I find the right target users?
BOTIM user group classifications? How can I find the right target users?Is social media marketing ineffective? The cloud control platform filters potential customers by pro
Botim private message data
BOTIM user group classifications? How can I find the right target users?The system supports unified management across multiple platforms and transparent data viewing, allowing users to monitor account status, screening results, and activity data at all times, enabling efficient collaboration and helping teams quickly develop targeted marketing strategies to maximize the value of social media operations. With the cloud-based control system, you can filter target accounts by age, gender, activity level, profile picture, and interaction frequency. This allows you to quickly identify high-value users, increase ad conversion rates and social media engagement, and achieve precise and efficient marketing promotions.
Research shows that among the numbers that have not been screened by the system, an average of 35% of the numbers do not exist or have been shut down, and another 20% of the numbers are valid but not the target customers.