Can multi-dimensional data filtering reveal the registration time? Digital planet social app data i detection
Multi-dimensional data screening is an important method to accurately identify user life cycle stages, especially in social platform marketing, multi-dimensional data screening is no longer limited toBasic judgments such as "whether there is registration or not" extend to deeper applications, such as registration time filtering. Through the dimension of "registration time", the team can effectively determine whether the user is a new user or an old user, thereby formulating a more matching conversion strategy, operation rhythm and content recommendation logic.
existOn social platforms such as WhatsApp, Telegram, Facebook, and Line, more and more marketing teams are discovering thatRegistration time is closely related to user behavior characteristics. Newly registered users tend to interact frequently and respond quickly, but lack stability; while users who registered earlier may have less activity, but have greater potential for retention and conversion. therefore,“Registration time filtering” has become an indispensable part of data management on social platforms.
What role does registration time play in social platforms?
byWhatsApp is an example. Users enter the platform identity system after registration is completed. In subsequent marketing, their registration time directly affects the account risk level, information acceptance and account suspension sensitivity:
lNew registration number (0-30 days): suitable for short-term stimulation, such as coupons, red envelope fission, and guidance for the first interaction
lmid-term number (1-6 months): Suitable for stable training, such as group guidance, content push, and service experience improvement
lLong-term number (More than 6 months): Suitable for in-depth conversion, such as member guidance, brand building, and secondary sales
existThe same is true in Telegram and Facebook. The longer the registration time is, the more stable the platform behavior is and the less likely it is for users to lose; while users with a short registration time, although active in interaction, are more likely to be fleeting.
Brought by registration time filtering4 core advantages
1. Precise delivery: different life cycles, different content strategies
If you send the same content to everyone, no matter how clever you write it, most of the users will be indifferent. The greatest value of registration time screening is that it allows youCustomize the information type and push frequency according to the stage of the user.
Example:
lWhatsApp new account: push welcome message, first activities, newbie tasks
lTelegram old users for more than 3 months: Send community rules optimization suggestions and exclusive discount codes
lNew followers on Facebook Page: automatic private messages to guide greetings and interactive messages
lLine friends have been registered for more than half a year: send anniversary rewards, participate in lucky draws, and upgrade membership tips
2. Control account risks: old accounts are safer, new accounts are more sensitive
Many social media automation teams know that new accounts are more likely to be flagged by system risk control, especially in scenarios where there are many batch account registrations and script operations. By filtering registration time,You can avoid accounts with short life cycles, give priority to old and stable accounts, and reduce the probability of account closure.
Real case: One company does itThe team informed by WhatsApp customers that before the registration time screening was done, a large number of new accounts sent messages in a short period of time, which directly caused 30% of the accounts to be restricted; after the screening, only numbers registered for three months were used, and the system stability was significantly improved.
3. Improve operational efficiency: Old users are more suitable for in-depth operations
Users who have been registered for a long time are often accustomed to the rhythm of the platform and have strong anti-interference ability, making it easier to enter the closed loop of community operation.
for example:
lexistIn the Telegram group, users who have been registered for 90 days or more are invited to participate in core discussions and become managers or volunteers.
lexistIn the Line friend system, one-to-one customer service channels are opened for customers who have registered for more than 6 months.
lexistOn Facebook Messenger, automatically identify and mark "old customers" and push VIP exclusive content or reservation service links.
4. Data cleaning: eliminate invalid new numbers and temporary numbers
Registration time filtering can also help youEliminate number resources with unknown origins and extremely short life cycles, especially among the large amounts of user information obtained from external data providers and script collection, to determine which ones can be used for the long term."Clean data".
How to accurately identify user registration time? Interpretation of data support from social platforms
Different social platforms support different ways of identifying registration time, but they can all be used through tools orAPI interface indirect implementation:
WhatsApp:
By analyzing the time when the user establishes a connection (such as the time when adding friends, the time when the first message is sent), and then combined with the activity level to determine the registration interval.
Telegram:
Some detection platforms can extract fields such as account creation time, first joining group time, and user name first binding time as reference.
Facebook:
Determine its activity cycle through page fan interaction time, first message time, account activity track, etc.
Line:
Combining the time when friends are added, the time when the user sends the first message, and the interaction history, a registration time model is constructed.
It should be noted that although not every platform directly opens the registration time field, it can be determined through data traces and behavioral models.Accurate estimation, which is enough to support marketing judgment and operational layering.
Practical case reference for social platforms
WhatsApp guides new users to join the group:
In an overseas educational institution, a user added a company for the first timeAfter creating a WhatsApp account, the system will determine whether it is a new user based on its registration time. If it is a new registration number, the system will automatically guide them to enter the "exclusive group for freshmen"; if it is a user who has registered for more than six months, exclusive retraining information or preferential upgrade plans will be pushed.
Telegram robot delivery optimization:
A company that does content subscriptionsThe Telegram team screened accounts registered for more than 60 days and set up access to advanced modules only to such old users. It was found that the secondary subscription conversion rate of old users was 60% higher than that of new users.
Line customer service label classification:
E-commerce brands inLine creates "last 7 days", "near 30 days" and "old customer" tags based on the first time the user was added. The customer service side sends different words and activity content based on the tags. New users get a welcome guide, while old customers get points redemption, annual benefits, etc.
Facebook ad audience remarketing:
via pageAPI and Pixel data are used to screen new users who have interacted for the first time in the past 90 days and deliver educational content; while remarketing for old users focuses on attracting coupons and promoting orders.
Registration time is just the starting point, multi-dimensionality is the future
Although"Registration time" is a very effective way to judge user stages, but it is only one part of the entire multi-dimensional data filtering. combineActivity filtering, online status filtering, device type filteringand other dimensions, can we truly establish a complete set of structured user operation systems.
For example: aThe value of a user who is "registered for more than 90 days + active in the last 7 days + uses an iPhone + has interacted in the community" is much higher than a potential user who is "just registered + not online + Android emulator device".The more dimensions, the more accurate the screening; the more accurate the screening, the more efficient the operation.
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