Global T-card screening, how to quickly classify and organize cross-country number data

When making global number data, the most confusing thing is not the quantity, but the source and type. Numbers from different countries such as the United States, the United Kingdom, France, India, Vietnam, Japan, etc. are mixed in the same file. Some international area codes are complete, some are still in local format, some operator information is clear, and some number types need to be reconfirmed. Once there is too much data, the restScreening on WhatsApp, Telegram, LINE and other platforms will also be slowed down. Global T-card screening is more suitable in the number data compilation stage. First, clearly distinguish the country, number format, operator and number type, and then decide which numbers will enter the next round of testing.

The first step to split the global number is by country.

If the numbers of dozens of countries are placed in a table at the same time, no matter what detection is done later, it is easy to make mistakes. First, you can sort out the country fields and international area codes, and classify markets such as the United States, Canada, the United Kingdom, France, Germany, Japan, India, and Vietnam respectively. Numbers with only local format need to be converted into a unified international format first; if there is already an international area code, you must also check whether the country field matches.

After this processing, the original hundreds of thousands of numbers mixed together became multiple national data pools. Do it laterDuring T-card screening, operator query, or social platform detection, batch processing can be performed by country, without the need to re-judge where the number belongs each time.

In the second step, look at the number type and operator information.

After the country sorting is completed, the next level is the number type. Different data sources may contain data from different operators, different number types, and the status needs to be confirmed. If the business itself needs to be globalT card filtering allows you to save target number types and ordinary numbers separately, so that all results do not continue to be stuffed in the same column.

A more practical approach is not to simply write aT card or non-T card, but keep the country, operator, number type, and original source separately. In this way, when you re-screen in the future, you don't need to run it all over again.

For example, the original data only has mobile phone numbers. After sorting, you can add:

US + CarrierA＋Target number type

UK + OperatorB+ordinary number

India + number type to be confirmed

Vietnam + target number type + advertising form source

This will make the subsequent use of the data much clearer.

Before T-card screening, remove duplicate numbers.

Another common problem with global data is duplication. The same customer may come once from the advertising form and submit it again on the official website, but there is still a record in the historical customer database. If only deduplication within the current file is not enough, it is best to compare it with the historical database again.

For example, this new importThere are 80,000 global numbers. After deduplication in the current batch, 70,000 numbers are left. After comparing with the past customer database, it is found that 15,000 of them have appeared before, so only 55,000 new data are actually added.

This number is closer to the actual number of new customers.

Don’t delete historical data directly if there are duplicate numbers. If the same customer had an order before and now makes another inquiry, the two records should be merged into one customer data instead of being treated as duplicate invalid data.

Digital Planet can be placed at the stage of number classification

worldwideT-card screening itself is a data organization requirement, and Digital Planet can be used directly in the middle process. Existing customer numbers are first unified into international formats, deduplicated and classified by country, and then continue to filter by number type, operator and related issues through Digital Planet, and split the different results into independent data pools based on business needs.

For example, after a batch of global numbers are sorted, they can continue to form:

United States + Destination Number Type +WhatsApp to be screened

India＋Destination number type＋Telegram to be screened

Vietnam＋Normal number＋Zalo to be screened

Japan＋Number type confirmed＋LINE to be screened

soT-card screening is not the end of the process, but a basic classification before subsequent social platform detection. The role of Digital Planet is to sort out the originally chaotic number status first, and then continue to deal with it according to the market and communication channels.

Why can't you get it?As a result of the T card, we will directly engage in customer development.

The number type is just a data attribute and does not represent the customer's intention. Even if a certain number matches the target type, it does not directly indicate that the user is interested in the product, nor can it be used to judge consumption ability or purchase demand just because of a number label.

Whether you can actually enter the sales pool depends on where the numbers come from. The official website's active inquiry, advertising forms, historical orders, and event registrations all have different values.

For example, both numbers belong to the targetFor T-card types, one just submitted a product quotation yesterday, and the other just registered for an event two years ago. Sales will definitely follow the former first.

soT-card screening solves the problem of number classification, not precise customer judgment.

Don’t apply the same set of rules to data from different countries.

The biggest taboo in global number screening is to treat all countries as one market. The number structure, operator environment and common social platforms are different in different regions, and the subsequent processing methods should also be separated.

For example, a market mainly usesWhen developing customers for WhatsApp, they will continue to screen for WhatsApp activation after the number classification is completed; in some markets, LINE, Zalo or Telegram are more preferred, and they will continue to be sorted according to the corresponding channels.

So the worldIt is better for T-card screening to form a national-level data pool, rather than just producing a global table of mixed results at the end. After being managed by country, it will be easier to control which batches need to be re-screened and which batches are to be handed over to sales.

After T-card screening, you can continue to do platform testing

After the number types are sorted, the next step is usually not to contact directly, but to continue to determine the target communication channel.

For example, a batch of Indian numbers have been sorted out. If we mainly doFor WhatsApp, we will continue to screen WhatsApp account status; a batch of Vietnamese numbers may need to further check Zalo and WhatsApp; the Japanese market may continue to sort out LINE related data.

Eventually it can form:

Country + number type + target platform status + customer source + recent interaction

Putting these fields together, the actual value is higher than that of a single columnT card results are much higher.

for example:

India＋Destination number type＋WhatsApp has been activated + official website inquiry + submitted 5 days ago

Vietnam＋Target number type＋Zalo related users + historical customers + no interaction for half a year

After the salesperson sees it, he basically knows which category to deal with first.

Don’t delete numbers with unclear status in a hurry

There will always be some numbers in the global data that cannot be clearly classified for the time being. The format may need to be checked, the operator information may be incomplete, or the number type cannot be confirmed temporarily.

There is no need to delete these data directly, they can be put into the waiting pool separately.

It will be updated later when the data is completed or retested.

This is safer than directly clearing all data that does not meet the current conditions, because some numbers just have insufficient current information, which does not mean that the customer itself has no value.

Especially data that already has orders, inquiries or historical business relationships cannot be thrown away just because a number label is unclear.

Hundreds of thousands of global numbers can be processed in a fixed sequence

If you frequently handle large batches of numbers, it's best to formalize the process. First unify the international format, then classify by country, then deduplicate the current batch and historical database, and then proceedFilter by T card, operator and number type. After the basic results are released, the corresponding platforms such as WhatsApp, Telegram, LINE, and Zalo are then tested according to the country, and finally the customer source, product interest, and recent interactions are re-merged.

In this way, every time new data comes in, it will follow the same set of logic. It will not be divided by country today and platform tomorrow, and the entire customer database will be messed up again in a few months.

Ultimately, the global mixed number will be turned into a data pool for different purposes.

worldwideAfter the T-card screening is actually completed, it is best not to just output a results table. It can be split into target number pools, ordinary number pools, and status pending confirmation pools according to actual services, and then further split according to countries and subsequent platforms.

It turned out to be a number file with hundreds of thousands of entries and dozens of countries mixed together. After sorting it out, it became the target number of the United States, the target number of India, and the target number of Vietnam.Different data pools such as Zalo filtering and Japanese to-do LINE filtering.

At this point, the numbers really start to be easy to use. Sales do not need to re-judge the country, operations do not need to rearrange number types, and subsequent social platform detection can also be performed directly in batches.

worldwideThe focus of T-card screening is not to simply divide all numbers into two categories, but to first sort out the formats, countries, operators, number types and duplicate records in the cross-country data, and then decide which platform to use next and which business process to hand over. The list of numbers that was originally mixed together can finally be separated by country, type and purpose. This time the screening is really completed.

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