The benefits of Number Cleansing (HLR)
Posted 30th January 2023 in Guides
What is number cleansing and what are the benefits of doing it
Number cleansing is a process that organises and standardises existing telephone number data , so that it can be used in more efficient ways. This includes identifying incorrect or incomplete telephone numbers within rows of data and resolving them by either double-checking the source information or querying information from other sources. Number cleansing provides many useful benefits to organisations, including increased accuracy in their data analysis projects, greater confidence when making decisions based on collected numbers, improved customer relations through better accuracy of contact details, and optimised storage management due to less wasted database space. Number cleansing has achieved great results across many fields and continues to progress in this digital age.
How to go about number cleansing
Number cleansing is an important task for businesses, as it helps ensure the accuracy of telephone number data. Number cleansing can be a difficult and time-consuming process, so it's important to know how to go about it in the most effective way.
First, order your data by the telephone number column. After the data is ordered look through the beginning and end rows of the data to see if there are telephone numbers which are clearly outside the E164 format. For example, telephone numbers that are clearly too short or too long for the country. NOTE: if you want to get your data back into the original order, ensure to have a column with a row reference number, for example add a new column in column A, starting with 1 at the beginning, 2 underneath, then select 1 & 2 and drag the corner of the rectangle box downwards to autofill the rows. TIP - double click the corner of the box to fill all the way to the last row.
Second, depending on how your telephone numbers are stored, you may or may not want to remove non digit characters - for example brackets spaces and periods. If you intend to use HLRlookup.com for the number cleansing then you do not need to remove any non-digit characters as the service will do this automatically when you upload your data. If you do want to remove non digit characters, the easiest way in excel is to copy and paste this formula:
=ArrayFormula(TEXTJOIN("",TRUE,IFERROR(MID(A1,SEQUENCE(LEN(A1)),1)+0,"")))
This will display only the digits from cell A1. If you would like any help using this formula please contact one of our team who can help you with excel.
When possible, utilise automated solutions such as scripts and programs that can quickly detect and fix common errors.
Finally, cleanse entire databases to verify the accuracy of the telephone data and improve quality control measures. Number cleansing is essential for businesses striving for accurate data, so be sure to have a plan in place to ensure efficient processes.
The different methods of number cleansing
Data cleansing is a process used by organisations to make sure that information like phone numbers, street addresses, and customer contact information is up-to-date and accurate. Different methods are used to carry out number cleansing, from comparing data with reference databases to use of algorithms. Organisations may also implement manual processes that involve reviewing certain records and updating them based on a defined set of criteria. Number cleansing can help improve customer satisfaction as well as provide better insights for marketing and analytics purposes. Number cleansing is essential for making sure any database maintained by an organisation remains comprehensive and up-to-date.
Why you should consider adding Home Location Register cleansing for your telephony data
Number cleansing is an essential tool for keeping your telephone number data updated. Number cleansing using the Home Location Register (HLR) Lookup service, will verify that a telephone number is valid, assigned to a telephone network, assigned by that telephone network to a subscriber (a person), and can even detect if the user’s handset is switched on or off at the time of the check.
Number cleansing helps to keep your contact information up-to-date and secure, saving time, money and effort compared to manually updating and verifying contact information. Number cleaning is a crucial part of any secure digital strategy - an invaluable tool for protecting your home's connection to the world.
How often should companies do a HLR cleanup?
Home Location Register (HLR) cleanups should be completed at least twice a year. Mobile network operators ensure the database is up-to-date, as it contains vast amounts of critical information that is essential in providing services. Doing regular HLR cleanups reduces churn and enables accurate analytics, allowing you to offer a better customer service experience with defined KPIs and metrics tracking. By regularly checking telephone numbers against the Home Location Register data, you can benefit from cost savings on SMS, voice termination and customer contact centres. Therefore, it is recommended that you do a HLR cleanup at least every six months in order to keep up with industry standards.
Conclusion
Number cleansing is important for many reasons: it helps to improve your data quality, can remove obsolete or inaccurate records, and will save you money. There are a few different methods of number cleansing, so you can choose the one that best suits your needs. If you're not sure whether or not number cleansing is right for you, consider these benefits and weigh them against the cost of doing a HLR cleanup. Depending on how often your database changes, you may want to do a regular checkup every six months to ensure that your information is accurate.
Written by David Morris
Chief Executive Officer & Founder at HLR LookupThe centralised HLR lookup service. We provide dependable status lookup for mobile telephone numbers. We welcome any suggestions for blog posts and are happy to share our insights. If you’d like the team to write up an article about a specific part of HLR Lookup please email us at info@hlrlookup.com.
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