What to look for when verifying account activity: Activity detection, online behavior and long-term user identification ideas

In the past year, more and more teams have begun to"Activity"Take it out separately for screening. In the past, after many projects obtained data, the first thing they usually did was to check whether they were registered, whether they had avatars, and whether they could send messages. But now more and more people are discovering that just knowing that an account exists has increasingly limited meaning. Because although many numbers and accounts are still there, users may no longer use them.

especially inWhatsApp,Telegram,LINE,FacebookAnd in the local social platform scene, account availability and account activity have begun to become two completely different concepts. Many teams appear to have a large list of names on the surface, but in reality, the back-end results include: large sending volume and low response rate; a lot of customer service work but few effective users; good advertising data but poor private domain accumulation. Many times the problem is not words or marketing actions, but the data itself.

Why"Existing an account" no longer represents user quality

In the past few years, when many teams were screening, the focus was on the activation status. As long as you have registered on the platform, you will be an operational user by default. But now the environment has changed.

Because of the large number of accounts though:

The avatar can be seen; it can be displayed normally; it can even send messages;

But the user himself may not have used it for a long time.

For example:

Numbers have changed; devices have changed; social habits have changed; and even platforms have migrated.

In particular, user behavior in overseas markets changes rapidly. Although many accounts exist, their activity levels have dropped significantly.

So now more and more people are starting to focus on"Do you have an account?"turn"Is the account still in use?".

What does activity really look like?

When many people mention active detection, they will understand it as online time by default. But in real long-term operations, being active is not just"Are you online today?".

Really valuable active identification usually combines several dimensions:

Recent interaction behavior; long-term usage frequency; online regularity; continuous usage cycle; account status changes.

The reason is simple.

Just because an account is online today does not mean it has been active for a long time; being online today does not mean it is willing to reply later.

Really high-quality users usually leave lasting traces of use.

For example, long-term stable login, continuous interaction, fixed usage cycle, and long-term online behavior.

After the accumulation of this information, the value will be much higher than a single online visit.

Why more and more teams are starting to look at"Long term active"

Many projects will find a situation later: it is easy to get short-term users, but it is increasingly difficult to get long-term users.

Especially in the private domain, customer service and membership systems, what really determines the outcome is often not who adds more, but who stays longer.

Because long-term active users usually mean:

It is easier to reply; it is easier to form long-term communication; it is easier to enter the private domain; and the probability of subsequent repurchase is also higher.

In contrast, although a large number of short-term users can bring data growth, the subsequent value will usually become lower and lower.

So now more and more teams are starting to do long-term active identification from the beginning.

Why online behavior is increasingly important

Recently many teams have started to add another dimension: online behavior.

Because many users will show significant differences even if they are active.

Some users are used to going online every day; some users appear at fixed times; some users continue to browse and interact; and some users only open it occasionally.

These behaviors themselves can actually reflect the value behind the users.

Especially in advertising and customer service scenarios, the subsequent performance gap between high-frequency online users and low-frequency users is usually very large.

Therefore, many mature teams have begun to:

Account opening status; activity detection; online behavior; long-term use tags;

Together as the basic judgment logic.

Why do many teams now test first and then market?

In the past few years, many teams were accustomed to sending messages first and then screening users based on the results. But now more and more people are starting to adjust their order.

Because as advertising becomes more expensive, customer service becomes more demanding, and private domain maintenance becomes longer and longer, the cost of low-quality data has become higher and higher.

So many projects will now be completed first:

Data detection; activity screening; user tag classification; long-term behavior recognition.

In actual operation, you can first use Digital Planet for screening number detection, and then combine active and long-term use tags for further screening. Digital Planet supports free trial screening test.

In this way, subsequent marketing actions, customer service undertakings and private domain operations will be much more stable.

Liveness detection is changing from an auxiliary action to a basic action

In the past, many teams would think that active detection was just a supplementary action. But now more and more projects have put it at the forefront.

Because what really matters in the future is no longer who has the bigger list, but who has a higher proportion of high-quality users.

Especially in long-term operation scenarios, what really determines the results is never the number of accounts, but the number of people who continue to use it.

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