Moj number generation is not just about issuing numbers in batches. The format, country and subsequent detection must be thought of in advance.

Moj number generation seems very simple. After setting the country, quantity and number format, you can get test numbers in batches. However, when it is actually used, the most likely problem is the latter part.

Whether the generated numbers will be used for system testing, interface joint debugging, or number format verification; whether the country codes are unified; whether duplicates need to be removed; and whether platform status detection will be performed in the future, all of these should be thought through before generation. More importantly, the generated numbers are only test data and do not represent real Moj users, nor can they be used directly as a customer acquisition list.

First determine what problem the number generation solves.

Moj number generation is more suitable for technical testing and data verification scenarios, such as testing whether the system can correctly identify Indian numbers, verifying different country area code formats, checking whether the import interface is normal, and simulating data processing capabilities of different orders of magnitude.

If just to test oneWhether the Moj-related system can receive mobile phone numbers normally does not require the pursuit of so-called precise users, as long as the number format meets the test requirements.

If you are verifying multi-country number rules, you must determine the country, area code, length and output format in advance to avoid rearranging it after generation.

The clearer the purpose of number generation, the simpler the subsequent data processing will be.

It is best to set the country and area code before generating

Different countries have different mobile phone number formats, including number length, international area code, and local writing.

ifMoj's business is mainly for the Indian market, and you can give priority to preparing test data according to the Indian number format; if the system is later to be compatible with other markets, you can generate different country formats and save them separately.

For example, it is best to directly bring the country field and international number field to the test file instead of just outputting a column of numbers.

This will make it easier to judge when importing the system later:

Which country the number belongs to;

Whether the international dial code is included;

Is there any error recognition in the system?

Can data from different countries be diverted normally?

Standardizing the format first saves time rather than reworking it later.

Don’t increase the number of generations too high at the beginning

The more test numbers, the better.

If you just check the interface format, dozens or hundreds of items are enough.

If you need to do batch import performance testing, you can gradually increase the number to thousands or tens of thousands.

By starting small, you can catch field errors, formatting issues, and system anomalies faster. After confirming that there are no problems with the rules, expand the quantity.

This is much easier than directly generating hundreds of thousands of data for the first time, and re-checking after the import fails.

After the number is generated, do a duplicate deletion first.

Even for test data, it is recommended to remove duplicates.

If duplicate numbers appear during the random generation process, the same test number may be repeatedly recognized by the system, affecting batch import, counting, or interface performance test results.

After the generation is completed, you can first check the internal duplication of the current file, and then decide whether it needs to be compared with the existing test library.

Keeping the unique number in the end will make subsequent test results easier to analyze.

If the test itself is to verify whether the system can recognize duplicate numbers, you can prepare a test file containing duplicate data instead of letting the duplicates appear randomly.

The random number is not equal to the real user number

This isThe most important thing to understand when generating Moj numbers.

The numbers generated according to the number rules of a certain country can only show that the format is close to the structure of a mobile phone number. It does not guarantee that it actually exists, nor does it mean that there must be someone behind it, nor can it mean that this person has opened the phone.Moj account.

Therefore, the generated result cannot be written directly asMoj user data, Moj precise customers or Moj potential customers.

Real customer acquisition should still come from normal business entrances, such as advertising forms, official websites, event registrations, customer service consultations, and other contact information proactively left by users.

Number generation solves test problems, and customer data solves business problems. The two purposes are completely different.

Subsequent testing should be determined based on the test objectives

After the number generation is completed, whether to continue testing is not a fixed process.

If you are just testing the system import function, this may be enough.

If you want to test the number cleaning process, you can continue with format verification, deduplication and country classification.

If the project itself involves the status of the target social platform, relevant technical verification can also be continued within the scope of legal and appropriate data.

Digital Planet can be used in the number sorting and detection process to deduplicate existing business numbers, classify countries, and filter target platforms. The generated number is more suitable for the testing process, and the test results should not be directly packaged into real customer resources.

Moj’s real customer acquisition starts with the user’s active entrance

If the goal is not to test, but to actually doThe process for Moj-related marketing to acquire customers should be changed.

First attract users through content, advertisements, landing pages or activities, and then let those who are truly interested take the initiative to fill in their mobile phone number, email address or other contact information.

After the data enters the customer database, the number format is unified, duplicates are removed, source tagging is performed, and subsequent platform screening is performed.

Such a piece of customer information can at least know:

fromMoj related ads or other entrances;

What products to focus on;

when to submit;

Have you taken the initiative to consult?

What channel is suitable for follow-up contact?

This kind of data has real business value.

It is best to create a separate data pool for test numbers

generatedMoj test numbers should not be mixed with real customer data.

It is best to create a separate test library and clearly mark its purpose, such as:

interface testing;

Format verification;

Batch import;

National Numbering Regulation Test;

Abnormal data testing.

In this way, during system maintenance in the future, technicians can quickly find the corresponding data and will not mistake the test number for a real customer.

If the real customer database and the test database are mixed together, errors will easily occur when doing statistics, sales allocation, and marketing analysis later.

Several types of test numbers can be specially prepared

In order to make the system test more complete, it is not necessary to generate only one standard number.

Different situations such as numbers in normal format, numbers lacking international area codes, numbers with spaces, repeated numbers, numbers with abnormal lengths, etc. can be prepared separately to test the system's data cleaning capabilities.

This way you can discover in advance:

Whether the system automatically recognizes the country code;

Will wrong numbers be blocked?

Can duplicate numbers be identified?

How to handle abnormal data during batch import.

These tests are more valuable for system optimization than simply generating a large number of normal numbers.

Moj number generation and number detection are divided into two steps

Generation is responsible for creating data that conforms to test rules.

Detection is responsible for checking whether the data meets expectations after entering the system.

Don't mix the two steps into one concept.

For example, first generate an Indian test number, and then check whether the number format complies with the system rules; after confirming that there are no problems with the format, test the functions such as import, deduplication, and country classification.

If it is a real customer number of the enterprise, you can further filter the target platform status through Digital Planet.

In this way, test data and business data go through separate processes without interfering with each other.

What really needs to be recorded is the generation rules

If number generation is used for long-term system testing, it is best to save the generation rules.

For example, which country to use, how to handle international area codes, how long the numbers are, how many numbers are generated at one time, whether duplication is allowed, and what fields are included in the output file.

After the system is upgraded in the future, when retesting is required, another set of data can be generated according to the same rules and the new and old results can be compared.

This makes it easier to reproduce the problem than randomly generating it every time.

Moj number generation is ultimately to make subsequent system testing smoother.

The number generation itself is not complicated. What really determines its value is how it is used later. The country, format, quantity, deduplication and testing goals must be planned in advance, so that the generated data can be truly used for interface joint debugging, format verification and batch processing testing.

If the target isTo truly acquire customers, Moj should obtain the data actively left by users through normal business portals such as content, advertisements, forms, official website, and customer service, and then enter the subsequent sorting and screening process. Number generation solves testing problems, and customer acquisition solves business problems. The two can be connected, but they cannot be regarded as one thing.

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