10 Best Practices to Manage & Clean your Phone Number Database
Posted 1st October 2021 in Guides
Manage and clean your phone number database with our 10 best practices in our latest blog post. The main gist is to verify correct data entry, standardise it, validate it, and finally scrub and clean your phone number database for any duplicates.
Bulk phone number cleaning removes dead numbers from your existing data set. By removing dead telephone numbers you are maximising the efficiency of your marketing campaigns and crucially saving a lot of money by not ringing or sending messages to inactive telephone numbers.
The key to fully controlling your customer communications is to regularly clean your phone number database so that you know very quickly if a client has stopped using the telephone number you think they are using. Whether you outsource data cleansing services or maintain your data management in-house – it should be one of your business priorities to manage and clean your phone number database efficiently.
67% of businesses rely on CRM data for marketing and sales. Yet, an astonishing 94% of B2B companies suspect inaccuracy in their database. Are you confident in the quality of your data? How do you clean and manage your database?
Maintaining your phone number database can be a long and tedious task for any employee. The number of hours required to manually check data can be time-consuming, inefficient and commonly leads to human error. Here are 10 best practices to help your business to manage and clean your phone number database:
1. Verify the phone number at point of capture
When you collect the contact details for your customer, it’s vital to verify the telephone number at the point of capture – this ensures a customer hasn’t “accidentally” entered a different number and is very useful when your data officer comes to ask why you’ve sent an SMS to someone. If you capture telephone data via a web form then you can HLR Lookup the number in real-time whilst the customer is filling in the form (if you need help with that, contact us and we will be happy to assist with coding).
If the number passes the HLR Lookup, i.e. the telephone number is real and active, then send the customer a code to their telephone number via SMS or an automatically generated voice call and request the customer enter this code on your website or app. By requiring the customer to confirm the code with you, then you can prove the customer had that telephone number at that point in time – your data officer will love you for it.
2. Standardise phone number formatting
When you capture telephone data, either directly from the customer or via an ingress from a data supplier, you should standardise the telephone number format. Ideally, you should use the industry-standard E.164 format – there are tons of advantages to this, most of all that it’s very easy to catch duplicates by checking if you already have the E.164 telephone number in your database. If you can’t use the E.164 format for some reason, always make sure to remove spaces commas brackets and non-digits from the telephone number.
Once you have standardised the telephone number, it’s a good idea if you aren’t going to HLR Lookup the number to at least verify the formatting to ensure the country code exists and that the telephone prefix has been assigned to an operator and that the number of digits is correct for that country and area code. Try checking a number against the world’s numbering plan here>. Inputting wrong data or leaving incomplete text fields are common problems that can cause issues when importing into your CRM system.
If you prefer to display a telephone number in a nice to read human format you can still store the number in your database in E.164 format but present the number on the screen in a friendly format. For example, our office number in E.164 format is 0044 113 3910781 but if we wanted to tell someone in the UK our phone number we would probably present this because this formatting is how someone in the UK would expect to see a telephone number written.
Rectifying phone numbers manually can be an arduous task and can lead to human error. If you have a large dataset that isn’t standardised, get in contact with our support team and we might be able to programmatically repair the numbers to E.164 for you. If you know the country that the telephone number is for, we have a feature on our latest API where you can pass a non-standardised telephone number with the country code and we can work out what the E.164 formatted version of the number is.
3. Regularly check existing phone data is still valid
If you don’t regularly check telephone numbers you won’t know if your customer has changed their telephone number. 55% of people change their mobile telephone number within 2 years, that’s a lot of change and can cause headaches if your targeted communication is sent to a dead number (or, worse, the number was recycled and now someone else is receiving a message meant for your customer).
Job roles, emails, addresses and phone numbers will change every so often. Using an API will help with keeping your data valid as you can programmatically check if a telephone number is still active without having to re-request this from the customer. Using automated tools doesn’t require anything like the time it takes to do this manually. The less manual work, the easier it is to keep on top of data management.
If a data point has changed (for example the mobile telephone number is now inactive), then you can immediately flag this and automatically contact the customer to ask for updated contact details. Some of our customers check and clean their phone number database every month to see if a user has become inactive but depending on your use case we would expect most companies to check all their customers’ contact details at least once per year and flag any data field which has become inactive.
4. Verify purchased phone data for quality
The quality of purchased, compiled or crowdsourced data can vary. Some data suppliers like to get around this by “oversupplying” data – you purchase 1000 lines but they supply 1100 lines to allow for “inaccuracies”. That feels good at the time, but when your response rate is super low on the data and you start manually ringing all the telephone numbers to find 30% are dead, it’s not a good feeling in the long run. By oversupplying, the data provider is passing the responsibility of having “good” data onto you.
Verify the data you are purchasing and check if the telephone numbers are real and active at the time you purchase the data. Most data suppliers already integrate with HLR Lookup to verify their numbers before passing them to their clients. If your supplier doesn’t integrate with us, make sure to HLR Lookup the list of telephone numbers and flag all the inactive, dead, invalid or strange numbers (we can detect premium rate, pagers, stage & screen and fake numbers). You won’t be able to contact a potential customer if their telephone number is dead!
5. An one-off clean
If you haven’t cleaned your data in the past, it’s a good idea to prepare and clean your phone number database in one go so you know what the current state of your data set is and what your starting point is from “today”. You can export the data from your CRM with a reference code, upload the telephone numbers with reference to us, we will append the status of each telephone number alongside your original data and then you can then reimport this back to your CRM. Once the data is back in your CRM you know that your sales, marketing, customer support and management have valid and live telephone numbers for your customers.
You can use your CRM to highlight customers where the telephone number is no longer active and contact them via a different channel to see what their new telephone number is.
6. Data scrubbing
Regular data scrubbing is the process of amending or removing data in a database that is incorrect, incomplete, improperly formatted or duplicated. Industries like banking, insurance, retail, telecommunications and transportation use data scrubbing tools to examine data for errors. A database scrubbing tool includes programs that are capable of correcting specific types of mistakes, such as adding missing fields or finding duplicate records. Using a data scrubbing tool can save a database administrator a significant amount of time and can be cheaper than fixing errors manually. Make sure you have standardised your phone data before scrubbing so that the scrubbing tool can easily find duplicate values while maintaining to clean your phone number database.
7. Blacklisted phone numbers
Calling or sending SMS to phone numbers that are on a ‘Do Not Call list’ (DNC) or ‘Blacklist’ can end up wasting a lot of money for your business. With tools available online, consider cleaning your phone number database against your national ‘Do Not Call list’ if one exists. In the UK for example we have the Telephone Preference Service and you should always check any telephone number you will be calling (or texting) against the Telephone Preference Service if you do not have an existing business relationship with the customer. Check blacklisted numbers against the TPS register here>
You should run your own DNC locally where you keep a list of people who have specifically requested that you do not contact them.
8. Data management access rights
Too many users can damage your data. A good data list is priceless and it’s an important resource for your sales and marketing team. Limiting the number of people who can access this data should be a priority due to data privacy and security, especially under GDPR (or your local equivalent). Instead of providing whole datasets to staff who don’t need the whole list, consider providing a simple web interface to allow staff members to view a telephone number on the screen when needed, without having access to the whole dataset at once. Assigning a designated data management officer can help to avoid misuse.
9. Landline, mobile, pager, premium-rate phone numbers?
Do you know if the telephone number you have is a mobile phone or a landline? What about a premium rate number, pager or a fake number used in films and TV shows?
Knowing the type of telephone number is useful when contacting a customer so you know if you might be calling them at home (landline) or if you can send them an SMS (mobile phone) or if the user is trying to trick people into ringing a premium rate number (for a big fee!). When you check a telephone number with HLR Lookup we detect which type of telephone number it is and you can store this in your dataset.
10. GDPR regulations
GDPR stands for General Data Protection Regulation. It addresses data protection, privacy, and transfer of personal information. Cleaning your phone number database ensures the importance of GDPR and while it requires a large amount of work for businesses, it will ultimately benefit from the steps they take on the journey to compliance. Poor quality data dampen even the best marketing efforts, and though it may be a tedious process, revamping your data cleansing and management process and system is bound to improve your business growth.
To summarise what we’ve covered to manage and clean your phone number database, firstly ensure correct data entry, standardise it, validate it, and scrub and clean for any phone number duplicates.
Validate the accuracy of your data either in real-time or by cleaning your existing database regularly to ensure it is complete and up to date. Do your research and invest in automated solutions that will clean and verify your data. Effective marketing and sales occur when high-quality data and cutting-edge technology are used together.
Increase the performance of your marketing campaigns by cleaning your database from invalid or outdated phone numbers. This will save money and time, giving you the capability to focus on your customers.
Written by David MorrisChief Executive Officer & Founder at HLR Lookup
The 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 email@example.com.
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