Moj data cleaning, how to quickly organize duplicate numbers and invalid data

DoWhen acquiring customers for Moj-related short videos, driving traffic through forms, or promoting the Indian market, when the data increases, the most troublesome thing is often not that there are no clues, but that the list becomes increasingly chaotic.

Moj currently mainly targets the Indian market, and its content is mainly in the form of short videos, Reels and other forms. If a large number of mobile phone numbers are accumulated through channels such as advertising landing pages, independent websites, and event registrations, problems such as duplicate numbers, inconsistent formats, missing country codes, and historical data mixed with new data may easily occur over time.

What Moj data cleaning really needs to solve is to sort out the messy information first, and then decide which customers are worthy of continued detection and follow-up.

The first step is to deal with the number format

got a batchAfter Moj related customer data, it is not recommended to conduct platform screening or sales distribution immediately.

Let’s look at the mobile phone number format first.

Some numbers are saved in complete international format, some only have local mobile phone numbers, and some numbers have spaces, dashes or other symbols in the middle.

Especially when dealing with markets in India and other countries at the same time, if the country codes are not sorted out clearly, it will be easy to mix data from different markets together later.

You can unify several basic fields first:

nation

country code

Complete mobile number

Customer source

data time

After the number format is unified, subsequent deduplication will be much more accurate.

Otherwise, the same mobile phone number may be regarded as two pieces of customer data just because it is written in different ways.

The second step is to remove duplicate numbers

In Moj data cleaning, number deduplication is usually the first step to see the effect.

The same user may have submitted a number once through an advertisement, then entered the independent site to fill it in again, and participated in an event a few days later and left the same contact information.

If data from different channels is always piled into the same table, it is not surprising that a customer appears three or four times.

Assume that there isOf the 50,000 numbers, only 38,000 are left after deduplication, which does not mean that there are 12,000 fewer customers.

What is really reduced is duplicate records.

If not cleared in advance, these duplicate numbers will be detected again later, or even contacted repeatedly by different salespeople.

So the smaller amount of data is not a bad thing, the number of independent numbers is closer to the number of customers that can really be processed.

Don’t just delete duplicate numbers, merge customer information.

Deduplication is not just about leaving a random number after seeing the same number.

For example, the same customer comes fromMoj-related advertising form, the second consultation came from the official website, and the third time I have already asked about the price.

If only the earliest record is left, subsequent product requirements will be lost.

A more reasonable approach is to merge useful information.

Keep a mobile phone number, and at the same time, collect the customer source, first deposit time, latest consultation time, products of interest, sales notes, etc. into one customer profile.

In the end, what the salesperson sees is no longer a string of repeated numbers, but a much more complete record.

After doing this, although there is less data, each piece of customer information is more valuable.

Obviously invalid data can be filtered in advance

After cleaning the duplicate numbers, you still need to deal with the obviously problematic data.

For example, the number of digits in the number is obviously wrong, the country code and country fields conflict, email or text appears in the phone number field, the same data lacks necessary contact information, etc.

If this kind of information is not cleared in advance, it will be entered later.When platforms such as WhatsApp and Telegram detect them, they will only increase the amount of invalid processing.

thereforeMoj data cleaning can first solve the most basic data quality problems, and then proceed to a deeper level of screening.

The order can be simply understood as:

Formatting → Deduplication → Abnormal data filtering → Country classification → Platform filtering → Customer grouping.

Solving the most obvious problems first will make every subsequent step much easier.

It’s best to keep the source of Moj data, don’t just keep the mobile phone number

If only a list of mobile phone numbers is left in the final file, the previous customer acquisition information will basically be wasted.

DoWhen it comes to Moj related traffic, it is best to keep the entrance from which the user enters.

For example:

Short video content to attract traffic

advertising form

landing page

Independent website consultation

Event registration

Historical customers

Only in this way can the salesperson know why the customer appears on the list.

People who come from product inquiries can continue the chat directly from product requirements.

People who sign up for ordinary activities can first check whether they are interested.

Those who already have purchase history should maintain it in the same way as old customers.

The clearer the data source is, the easier it will be to follow up with subsequent customers.

After cleaning, do social platform screening.

After the number format, duplicate data and obvious abnormal information have been processed, it is appropriate to continue with social platform screening.

If subsequent major passesFor WhatsApp communication, you can check which numbers have been subscribed to WhatsApp.

If the business is more biasedTelegram, you can also continue to do Telegram related filtering.

Digital Planet can be used in this step.

After the enterprise has obtained the customer number through normal business channels, it can first complete theMoj data is cleaned, and then digital planet is used to remove duplicate numbers, organize countries, and filter the status of target social platforms.

For example, after cleaning, we getAmong the 20,000 Indian customer numbers, some of them have been screened out and have been activated on WhatsApp, and some have basic usage of Telegram, so they can continue to be split according to the platform and customer source.

In this way, the list obtained from sales will be better than the original one.Moj raw data is clearer.

Digital Planet is responsible for sorting existing numbers and selecting channels, and is not responsible for removingMoj directly acquires unfamiliar users.

New data must be deduplicated together with the historical customer database

Many people only do the deduplication once, and after a while the data becomes messy again.

The reason is that each batch of new data is only cleaned internally and is not compared with the past customer database.

For example, new this weekOf the 10,000 Moj-related clues, 9,000 are left after deduplication within the current file. However, after comparison with the historical database, there may be 3,000 that have appeared before.

Then the only real new additions are6000 items.

This number is more suitable for judging the actual customer acquisition effect.

In the future, every time new data is imported, a repeated check will be done with the historical customer database, so that the number of customers will not seem to be increasing, but sales will still encounter the same faces every day.

How to hand over to sales after cleaning is completed

The final data does not need to be particularly complex.

It’s enough to keep a few fields that sales will actually use:

nation

Phone number

Customer source

target platform status

Follow products

most recent interaction

Current follow-up status

For example, a piece of data is organized into:

Indian customers

source:Moj related advertising form

WhatsApp has been activated

focus onA product

Submitted 3 days ago

Not contacted yet

The other one is:

Indian customers

Source: Historical event registration

Telegram has been activated

No specific product yet

No interaction for half a year

low priority

The salesperson will know which item to process first at a glance, without having to read the original form again.

Moj data cleaning really removes invalid work

Data cleaning is not just about50,000 entries were deleted into 30,000 entries.

What's really valuable is making the remaining data easier to use.

With fewer duplicate numbers, the number of subsequent tests will be reduced; after the format is unified, the country classification will be clearer; the source will be retained, and sales will know why they are contacted; and through digital planet screening of numbers and social platforms, follow-up channels will be clearer.

Moj data cleaning does not have to be complicated. First sort out the format, duplicate numbers, abnormal data and sources, and then proceed to number detection and customer classification. Only then will the original chaotic data truly become a customer list that can continue to be used.

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