LinkedIn business development is becoming more and more difficult. Is the data of male customers over 35 years old more stable?

existIn LinkedIn business development scenarios, declining response rates have become a common phenomenon. Even if the industry and position are accurately positioned, it is still difficult to obtain stable feedback. This change does not mean that the channel has failed, but that the user structure and communication environment have changed.

Against this background, some teams have begun to focus on more detailed population characteristics, such as age group and gender structure. in,"Male customers over 35 years old" are frequently mentioned because this group of people show more stable communication behavior in certain business scenarios.

What is the core reason why LinkedIn development is difficult to return to?

In the current environment, users have become significantly more sensitive to unfamiliar business information.

High-frequency development of information causes user fatigue, while indiscriminate access also reduces overall trust. If the target group itself is not willing to respond or has not been active recently, it will be difficult to get feedback even if the content is accurate.

Therefore, the key to the problem lies in crowd screening, rather than simply optimizing words.

Why are male customers over 35 years old given separate attention?

in partIn B2B and business decision-making scenarios, this group of people has certain similarities.

For example, they have a higher degree of participation in decision-making, a more rational communication logic, and a strong ability to filter information. These characteristics make them more likely to respond when faced with clear value information.

But it's important to note that this is just a trend, not an absolute rule.

Is the data for this group of people really more stable?

In specific industries, such as corporate services, supply chain, technical cooperation and other fields, the response stability of this group of people is relatively higher.

However, if you are divorced from the specific business scenario and only use age and gender as filtering conditions, the effect may not be ideal. Because whether users respond is also affected by multiple factors such as active status, industry matching, and current demand stage.

Therefore, this label can only be used as a secondary dimension.

Why user value cannot be judged by registration status alone

The existence of a LinkedIn account does not mean that the user is using it.

Many accounts have been in a low-activity state for a long time, and even if they send information, it is difficult to be checked in time. Therefore, if the screening logic is based only on registration status, it is easy to include a large number of low-value users into the target population.

Activity judgment is even more critical in the current environment.

Crowd screening logic more suitable for business development

A more reasonable screening method is usually multi-dimensional superposition.

You can first conduct basic identification to filter out available accounts; then conduct preliminary grouping based on age group and gender; then focus on screening recently active users and match them based on industry attributes. In this way, the quality of the target population can be gradually improved.

In actual operation, user screening, activity identification and basic data filtering can be carried out through Digital Planet.Complete initial screening before the LinkedIn development process to increase the overall response rate.

Why does filtering order affect development results?

If the filtering order is unreasonable, such as filtering by tag first and then looking at activity, it may lead to biased results.

A more effective way is to first ensure that users have usage behavior and then segment the group. This avoids investing resources into accounts that don’t have the foundation to respond.

The screening order itself is part of efficiency.

fromChange from “extensive development” to “crowd focus”

The logic of LinkedIn business development is changing.

In the past, there was more emphasis on reaching more potential customers, but now there is more emphasis on focusing on people who are more likely to respond. As the size of data continues to grow, this shift will become increasingly apparent.

For scenarios that require stable development effects, crowd screening capabilities are becoming the core competitiveness.

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