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12

2026-06

Data batch cleaning solution to quickly improve customer data quality

Batch data cleaning has gradually become a basic link in the enterprise operation process from the work of the data department in the past. Many companies pay more attention to data growth in the early stages of business development, hoping to accumulate more customer resources. However, as time goes by, the amount of data becomes larger and larger, and data quality problems begin to be exposed.

29

2026-05

The whole process of marketing number screening: a method to filter invalid mobile phone numbers in batches

The efficiency of marketing actions never starts from the moment of sending, but from the moment of data collection. When promoting private messaging, text messages, WhatsApp or Telegram contacts, many teams focus on words, rhythm and frequency, but ignore a more basic question - whether the mobile phone number is real, usable and worth reaching.

28

2026-04

There is a lot of cross-border traffic flow data, how to filter out low-quality customers who will not make transactions?

When doing cross-border traffic attraction, many teams will go through a stage: more and more data, but transactions do not increase simultaneously. It seems that there are enough leads in the background, and there are even new ones every day, but once you get to the follow-up stage, you will find that a large number of users cannot be reached, barely respond, or do not meet the conversion conditions at all.

23

2026-04

Is LinkedIn customer development effect unstable? A practical way to choose between job tags and age tags

When doing LinkedIn development, many teams have a common confusion: the screened customers seem "right", but the actual conversion rate is obviously low. Especially when the filtering conditions focus on standard labels such as position, company size, and industry, the results are often not as expected.

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