Analysis of online consumer user detection methods, targeting high-value consumer groups in 5 major dimensions

Traffic is getting more and more expensive, which has become a common feeling among many e-commerce teams, brands and private domain operators. In the past few years, we could rely on large-scale advertising to continuously acquire new users. Now, with the same budget, the number of new users we can bring is increasingly limited. Instead of continuing to blindly expand, many teams began to focus on another thing: finding people who are truly willing to consume.

After all, 10,000 ordinary users may not be as good as 1,000 continuous consuming users.

Online consumer user detection has gradually changed from an auxiliary tool in data analysis to an important part of refined operations.

Why consumer users are more important than traffic

Many teams have had similar experiences.

Advertising has brought in a large number of users, but the actual transactions are not ideal; the number of people in the community continues to increase, but the people who actually place orders are always concentrated in a small number of people.

The problem is not necessarily traffic, but user quality.

There are obvious differences in spending power, purchasing habits and activity levels among different users. If people with consumption potential can be identified in advance, operational efficiency will be greatly improved.

Therefore, more and more companies are beginning to pay attention to online consumer user detection, rather than simply pursuing the number of users.

first dimension User consumption frequency

Consumption frequency often reflects the user's activity level.

The value of users who shop online for a long time, frequently participate in platform activities, and continue to engage in consumption behavior is usually higher than that of people who occasionally place orders.

The more stable the consumption frequency is, it means that the user's consumption habits have been formed, which also means that the probability of subsequent conversion and repurchase is higher.

For e-commerce, membership services, and cross-border platforms, such users are often key operating targets.

second dimension User shopping platform preferences

The shopping habits of different users vary greatly.

Some people use it for a long timeFor Amazon shopping, some people prefer Shopee, Temu, TikTok Shop or independent websites.

Platform preferences can actually reflect users’ spending power, purchasing habits and product acceptance.

For example, users who have used international e-commerce platforms for a long time are generally more receptive to cross-border goods and digital service products.

Therefore, platform tags are also an important part of consumer user detection.

third dimension User active status

Spending power does not represent real-time value.

Although some users have strong spending power, but have not been active for a long time, their conversion value will also decline.

Therefore, when conducting user analysis, in addition to consumption attributes, it is also necessary to combine active status.

Only users who have both spending power and active behavior are the ones truly worth reaching.

fourth dimension User device characteristics

Many industries have discovered during actual operations that there is a certain correlation between equipment type and consumption capacity.

Users of different systems and different mobile phone brands often have differences in shopping behavior and payment habits.

Although device information cannot directly determine consumption capacity, as part of user portraits, it can help companies further segment groups.

Therefore, device attributes have gradually become an important reference dimension for consumer user analysis.

fifth dimension User long-term value

One consumption does not represent user value.

The real concern is long-term value.

Although some users have a low consumption amount, they have stable repurchase ability; while some users have a high single consumption, but there is almost no subsequent repurchase.

Therefore, user lifetime value is also an important basis for judging high-value users.

Through cross-analysis of multiple dimensions, user stratification can be made clearer.

What characteristics do high-value consumer groups usually have?

Taken together, high-value consumer users usually have several common characteristics.

Continuous online consumption;

Have stable and active behavior;

The consumption platform is relatively fixed;

The ability to pay is relatively strong;

The repurchase cycle is short;

High acceptance of brands and products.

Although the number of such users is not necessarily the largest, they often contribute to the majority of transactions.

So more and more teams are starting from“Acquire more users” to “Identify better users”.

Data screening is more important than post-marketing

Many companies are accustomed to focusing on marketing activities, but in fact, user quality often determines the upper limit of marketing.

If the users themselves do not have the willingness to consume, no matter how good the activity plan is, it will be difficult to produce results.

Therefore, more and more teams will complete user screening before launching and importing data.

First find people who are likely to consume, and then make follow-up contacts.

This method can not only reduce costs, but also improve overall conversion efficiency.

How does Digital Planet identify online consumer users?

In actual business, many teams will first use Digital Planet to pre-screen user data before entering the launch or private domain operation stage.

For example, after a batch of 100,000 mobile phone number data is imported into the system, Digital Planet's online consumer user detection capabilities can be used to identify users' consumption tags, screen high-value users, and analyze user attributes.

The system can classify users based on consumption attributes, activity status, device information and related tags.

After screening, the operations team can get different types of crowd packages.

For example:

High consumption user group;

Stable and active user base;

Online shopping user group;

Potential high-value user groups;

Medium and low consumption user group.

Then combined with advertising,WhatsApp marketing, Telegram community operations or private domain conversion, carry out refined operations with different strategies.

In addition to online consumer user detection, Digital Planet also supports number status identification, platform user query, device information detection and multi-dimensional label analysis, helping the team build a more complete user portrait system.

Many cross-border e-commerce, overseas marketing teams and private domain operation teams will first use Digital Planet to complete data stratification and then carry out subsequent promotion, thereby reducing ineffective contacts and improving overallROI.

In the era of user value, finding the right person is more important than finding more people

After the traffic dividend gradually weakens, refined operations have become the choice of more and more enterprises.

The significance of online consumer user detection is not to simply distinguish who has purchased something, but to help companies quickly discover truly valuable groups of people.

When resources become increasingly limited, spending budget on the right people is often more important than getting more traffic.

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