Stop Mass Messaging with No Replies! 3 Steps to Filter Active Zalo Users—Reach Real People.

In the Vietnamese market, Zalo is undoubtedly a national-level app, but many businesses face an awkward dilemma: hundreds or even thousands of messages are sent, yet only a handful receive replies. The root cause is that most of the users you reach are inactive. Zalo's activity filtering is key to solving this problem. By filtering for real users with recent login activity, every outreach will generate a response. Master Zalo's activity filtering to say goodbye to the embarrassment of "mass messages going unanswered" and ensure your marketing resources are truly used effectively.

I. Why is active filtering in Zalo the first step to improving response rates?

Many businesses invest heavily in Zalo marketing, only to suffer dismal response rates due to reaching inactive users. A single inaccurate outreach can lead to the following problems:

• No response : The message was sent to an account that has not logged in for a long time, and the open rate is zero.

• Data distortion : Unable to distinguish between active and dormant users, conversion rate statistics are severely biased.

• Wasted resources : Customer service efforts are being squandered on accounts that don't respond.

Zalo's active filtering process combines eliminating dormant accounts with focusing on recently active users, which forms the basis for improving response rates.

II. Step 1: Filter active users in the past 7 days and identify high-response groups.

Zalo users exhibit significant differences in activity levels, with those who logged in within the past 7 days showing the highest response rate. Skipping this screening process would present businesses with the following challenges:

• Delayed delivery : Users may have changed devices or abandoned their accounts, and the message has gone unanswered.

• Missed Interaction Window : Missing peak user activity periods makes it difficult to get immediate interaction even if messages are sent.

• Low conversion rate : Even if dormant users receive the message, they rarely generate further conversions.

• Wasted resources : Under the pay-as-you-go model, a significant portion of the budget is wasted on invalid accounts.

By using the "Active in the last 7 days" dimension in Zalo's active filtering, you can identify real users who are currently online and ensure timely reach.

III. the second step: Filter active users in the past 30 days to expand the scope of precise reach.

For some marketing scenarios, the number of active users in the past 7 days may be insufficient. In such cases, it is necessary to expand the scope to active users in the past 30 days. Ignoring this dimension will lead to the following problems for businesses:

• Insufficient user pool : Overemphasis on "latest active users" leads to insufficient reach, impacting marketing scale.

• Missing out on potential users : Some users, while not logging in daily, maintain stable weekly activity and also possess response potential.

• Incomplete user profile : Focusing only on recently active users fails to provide a comprehensive understanding of user behavior patterns.

• Insufficient campaign reach : When promotional activities require a certain scale of support, an insufficient user pool directly impacts the effectiveness.

The "active in the last 30 days" dimension in Zalo's active user filtering can both ensure user quality and meet the needs of large-scale reach.

IV. the third step: Combine activity level and account status to filter and eliminate abnormal accounts.

Simply filtering by activity level is insufficient; a combined approach based on account status is necessary. Without account status verification, businesses will face the following challenges:

• Account Abnormalities : Some active user accounts may have been banned or are under restrictions.

• Incomplete information : Accounts without profile pictures or bios, even if active, tend to have low trust levels and low willingness to interact.

• Repeated outreach : The same user is repeatedly entered into the user pool through different channels, resulting in wasted resources.

By using Zalo's active user filtering combination of "active in the last 30 days + normal account status + complete information", a high-quality active user pool can be built.

V. Key to Efficient Implementation: Achieving Batch Automation Through ITG's Global Filtering

When businesses need to acquire a large number of active Zalo users, manual screening is inefficient and makes it difficult to guarantee data quality. Without specialized tools, businesses will face the following challenges:

• Manual operation is cumbersome : it's virtually impossible to filter out the activity status and account status of tens of thousands of numbers one by one.

• Data update lag : User activity status changes dynamically, and static filtering results cannot reflect the latest situation.

• The sources of the numbers are mixed : the quality of numbers obtained from different channels varies, making it difficult to categorize them uniformly.

• Execution efficiency bottleneck : The screening speed cannot keep up with the marketing pace, resulting in missed golden periods for the campaign.

In this step, combining ITG's full-domain filtering can completely solve the efficiency problem:

• Batch import, automated recognition : Supports batch import of Zalo phone number resources, automatically identifies and outputs key fields such as the user's recent active days, account status, and profile picture completeness.

• Quick combined filtering : Helps businesses complete multi-dimensional combined filtering based on "activity in the last 7 days", "activity in the last 30 days", "account normal" and other criteria with a single click.

• Flexible user pool building : Whether it's building a high-response user pool with "active users in the last 7 days and complete profiles" or filtering a large-scale reach audience with "active users in the last 30 days", structured user profiles can be generated as needed.
  
  

In conclusion: Stop sending mass messages and getting no replies! Zalo's activity filtering, from filtering based on activity in the last 7 days, activity in the last 30 days, to a combination of account status, allows you to accurately identify truly active users in just three steps. Leveraging ITG's full-domain filtering enables automated batch identification, ensuring every outreach receives a response and every penny of your budget is spent on genuinely active users.