Many of us couldn’t run a business without an effective CRM. But how reliant are you on maintaining a clean customer and prospect database?
After speaking to many business professionals, one thing became apparent. Many businesses have no idea how clean their phone number data actually is.
An effective CRM and the maintenance of data often don’t go together. But they should.
Most of the conversations we had at Technology for Marketing in September 2026 focussed on customer data, and one thing kept coming up: businesses often have a fairly good idea of how many customer or prospect records they hold, but much less certainty about whether the phone numbers attached to those records are actually useful.
They look like phone numbers. They sit neatly in the correct CRM field. They might have been there for years.
But are they still active? Are they mobile numbers? Have they moved networks? Are they correctly formatted? Could they now belong to somebody else? And, perhaps most importantly, when was anybody last checking?
That's where the perceived health of CRM data can start to drift from reality.
How can you tell if a phone number in your CRM is still valid?
Phone data can be deceptive. An email address will often give you fairly obvious signs when something has gone wrong. A phone number can continue looking completely normal long after it has stopped being useful.
07700 900000 still looks like a mobile number whether the subscriber is reachable or not.
Formatting checks are useful. They can tell you whether a number appears structurally possible and help standardise it into formats such as E.164 (provided by e164).
But formatting alone doesn't tell you what's happening behind that number.
Depending on the number and available network information, deeper validation can help establish the following:
- whether the number is valid and usable
- whether it is mobile, fixed-line or another number type
- its current network
- whether it has been ported
- whether network information indicates that it is active or reachable
- whether it is suitable for the communication you are planning
That gives CRM teams a very different view of data quality.
Should you validate phone numbers before importing them into your CRM?
How many lists make it into a CRM before anybody actually checks the phone numbers on them?
Not just purchased data.
Event leads. Old spreadsheets. Historic customer records. Competition entries. Data migrations. Partner data. Prospect lists assembled by sales teams. Records inherited from another system. That CSV somebody found in a shared folder and decided might still be useful.
CRM managers will understand this all too well.
Do businesses validate phone numbers before uploading lists to their CRM?
Not always. And that's one of the easiest ways poor-quality phone data becomes trusted CRM data.
8,000 records need to be imported. The data slots beautifully into the right columns, and the import is successful.
Except the CRM is now 8,000 records larger, but nobody knows whether it's 8,000 records healthier.
Once that data is inside the CRM, whatever the CRM (Salesforce, HubSpot, Monday, Pipedrive, you name it) that data magically becomes credible (without a single validation check taking place).
Why does phone number data in a CRM become outdated?
Even perfectly good phone data has a shelf life.
Customers change numbers. Numbers are disconnected. Mobile subscribers port between networks. Numbers are eventually recycled and allocated again. Data is entered incorrectly. International formats get mangled. Landline numbers end up in fields intended for mobiles.
None of this means your CRM is poorly managed. It simply means telephone data changes.
A record that was correct when somebody created it three years ago doesn't automatically remain correct today.
That's particularly important when phone numbers are used for operational processes rather than simply sitting as contact information.
Think about:
- SMS notifications
- OTP and authentication
- appointment reminders
- deliveries
- payment and arrears communications
- customer service
- account recovery
- fraud and risk processes
- marketing communications
Bad phone data doesn't just make the CRM untidy. It becomes a communication problem.
What does healthy phone data actually look like?
For most organisations, it shouldn't mean running a massive CRM cleanse once every few years and declaring victory.
It makes more sense to validate numbers where their quality matters.
Validate phone numbers when they're first captured
Check numbers when customers enter them.
Basic validation can catch formatting problems immediately, while deeper number intelligence can provide additional information where the use case requires it.
Stopping poor data at the door, and dealing with it, is much easier than finding it again later.
Validate phone numbers before CRM imports
Before another spreadsheet becomes another few thousand CRM records, check what you're actually importing.
That might sound obvious, but judging by the conversations we've had, it isn't always happening.
Validate CRM data before important communications
A number sitting unused for eighteen months shouldn't necessarily be treated exactly the same as a number confirmed yesterday.
If you're preparing an important SMS campaign, customer service exercise or operational communication, validating the data beforehand can identify records that deserve another look.
Make phone number validation part of CRM maintenance
Data quality isn't really a project with a finishing date.
For organisations that depend heavily on telephone communication, number validation can become part of normal CRM hygiene alongside duplicate management, email validation, consent management and record enrichment.
Should CRM managers be responsible for all of this?
Not entirely, because no single team creates poor CRM data.
Marketing captures data. Sales imports it. Customers provide it. Operations use it. Developers send messages against it. Legacy systems contribute to it.
CRM teams often end up becoming custodians of problems created much further upstream.
A better question is whether your organisation has rules for phone data before it reaches the CRM and before it is used.
For example:
When is a number validated? What information do we need to know about it? When should it be checked again? What happens when a number fails validation? Which processes depend on that number being correct?
Those questions tend to reveal rather more about data health than the number of complete fields on a CRM dashboard.
Your CRM might be tidy, but that doesn’t mean the data is healthy.
There is a difference between having a phone number and having a phone number you can confidently use.
Acudo provides phone number intelligence that helps businesses validate and understand telephone numbers held in CRM and customer databases.
The best time to discover a customer number isn't useful, isn't after you've tried to contact them.
Validate. Then communicate.