When doing cross-border advertising, what is more worthy of screening recently are high-active users or high-quality device

In cross-border advertising, an increasingly common disagreement is whether to prioritize high-active users or high-quality device users. Both approaches have their supporters, and the results vary significantly in different projects.

In essence, this is not a technical issue, but a target issue. Different filtering dimensions solve completely different delivery goals. If the scenarios are not distinguished, it is easy for the screening logic and actual needs to be misaligned.

Why did the filtering logic start to split into two directions?

As the level of data refinement increases, filtering no longer just filters out invalid data, but begins to affect the delivery strategy.

Highly active users are closer to immediate behavior and represent short-term reachability; while high-quality device users reflect more consumption capabilities and user levels. These two dimensions correspond to different goals, so the screening logic is naturally differentiated.

This difference is further magnified as the data scale increases.

What are the core advantages of highly active users?

The biggest characteristic of highly active users is their fast response speed.

Such users usually have recent usage behavior and can see information and generate feedback in a relatively short period of time. Therefore, in scenarios that require quick verification of results, such as short-term conversions, limited-time activities, and instant communication, highly active users have an advantage.

At the same time, this type of user is more suitable for initial testing because the feedback is more concentrated.

Where is the value of high-quality equipment users reflected?

Device information more reflects the user's usage environment and consumption level.

For example, some device users are more stable in terms of spending power and application usage habits. Although such users may not necessarily interact frequently, once they enter the conversion path, their quality is usually higher. Therefore, in high-customer single products or long decision-making links, high-quality equipment users have more reference value.

This dimension is more biased toward mid- to long-term value judgments.

When is it more appropriate to prioritize active users?

When the goal is to increase response rates or produce results quickly, it is more effective to prioritize high-active users.

Scenarios such as short-term e-commerce promotions, private domain cold starts, and batch reach tests all require users to have instant feedback capabilities. In these cases, if the filtering device is prioritized, it is likely that the response speed will be reduced.

Therefore, active priority is suitable for short-term goals.

When is it more appropriate to prioritize screening equipment users?

When the goal is to increase customer unit price or screen out high-value groups, priority screening equipment is more suitable.

For example, scenarios such as high-end product promotion, financial services, and long-term customer development focus more on user quality rather than immediate response. At this time, even if the activity is slightly low, it still has value as long as the user has the spending power.

Equipment is given priority and is more suitable for mid- to long-term transformation.

A more stable approach is not to choose one or the other.

In most cases, a more reasonable approach is to use a combination.

You can first determine the main screening dimensions based on business goals, such as giving priority to active short-term conversions, and prioritizing equipment for medium- and long-term conversions; then add another dimension for optimization. For example, after screening active users, screen devices again to extract higher-quality people.

This approach can take into account both response speed and user quality.

In actual operation, active user screening can be completed first through Digital Planet, and then secondary filtering can be performed based on device identification to divide the data into different levels, making it easier to match different delivery strategies.

How filtering dimensions affect the finalROI

The choice of filtering dimensions will directly affectROI structure.

If all high-active users are used, the short-term effect may be better, but the unit price may not be stable; if all high-equipment users are used, the conversion quality will be higher, but the feedback cycle may be longer. Therefore, a balance needs to be made based on business goals.

Screening itself is part of resource allocation.

Changes from data selection to target selection

The core of cross-border delivery is shifting from data selection to target selection.

Different filtering dimensions essentially correspond to different results. When the goal is clear, the screening logic only makes sense. Highly active users and high-quality device users are not more important, but who is more suitable for the current stage.

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