Cross-border e-commerce Telegram marketing skills: screen active ones first and then send them in bulk

Cross-border e-commerceIn Telegram marketing, many times the problem is not the traffic, but the structure. Advertising can bring inquiries, and social media can bring attention, but when these users are imported into Telegram to prepare for group messaging, conversions begin to fluctuate. Some batches have good responses, while others have almost no interaction. The real difference often appears in the activity structure.

Before scaling up, screening active users first and then mass-distributing is a key action for many teams to achieve stable conversion.

1. Why mass messaging is unstable

Cross-border e-commerce lists usually come from multiple sources. Advertising consultation, form data, historical customer import, third-party data collection. The quality of these data varies, and a large proportion of accounts have been silent for a long time.

When the proportion of silent accounts is high, even if the message is sent successfully, users may not see the message, let alone take the initiative to reply. The number of messages seems to be high, but the proportion of effective interactions is low.

Many teams will repeatedly revise their words, but ignore the problem of the data itself.

2. Structural changes brought about by active screening

Active screening is not about reducing the number of lists but optimizing the structure. By filtering, accounts with recent usage behavior can be prioritized.

A cross-border e-commerce team encountered a problem of declining response rates during the large-volume phase. The original list size is close toThere were 20,000 messages, and the response rate after mass mailing was less than 2%. They did not change their rhetoric, but first conducted a round of active testing on the list.

After checking the account opening status and activity status through Digital Planet in batches, it was found that about35% of accounts have long-term low activity status. The team decided to defer access to this part of the data and only send it to highly active and medium active users.

After optimization, the size of the first round of mass distribution was reduced to13,000 items, but the response rate increased to 4.8%, and the transaction conversion rate increased simultaneously. The quality of customer service dialogue has been significantly improved, and the proportion of subsequent repurchase users has also increased.

This adjustment does not increase promotion costs, but only optimizes the contact sequence.

3. Specific steps to screen the active ones first and then send them in bulk

The first step is to organize the list in a unified manner.

The second step is to check the account registration status and activity in batches.

The third step is to output the label results and manage them hierarchically.

The fourth step is to reach high activity first, test the rhythm of medium activity, and delay sending if low activity.

In actual operation, the team imported the list file through Digital Planet, and the system automatically output status labels such as activated, active, and high risk. After the detection is completed, the data is directly synchronized to the mass distribution system, reducing manual screening time.

This process changes the bulk reach from extensive to structured reach.

4. The long-term impact of active screening on conversion rates

Active filtering not only improves short-term response rates, but also improves long-term user pool quality. Because users who are reached first are more likely to have conversations and transactions, and the subsequent repurchase structure is also clearer.

If silent accounts are contacted repeatedly, marketing resources will be diluted, customer service time will be occupied, and statistical data will be distorted. The role of active filtering is to make every send more valuable.

Cross-border e-commerce competition is becoming increasingly fierce, and simply increasing the number of shipments can no longer bring advantage. Optimizing the data structure and allowing active users to enter the communication path first is a more sustainable way.

Filtering does not reduce opportunities, but allows users who really have opportunities to be ranked first. When the target is reached more accurately, the conversion will naturally be more stable.

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