Tired data: all databases become obsolete over time, unless they are regularly cleaned and restocked.
In many ways they are like the human body. We all benefit from washing regularly, to stay fresh, and maintaining a proper nutritional balance, to keep energised. Leave either to its own devices and decline sets in quietly, long before it becomes obvious.
Data decay refers to the gradual degradation of the accuracy and completeness of data over time, as contacts change jobs, companies merge or go out of business, and countless smaller changes accumulate beneath the surface. None of it happens because anyone made a mistake. It simply happens, the natural consequence of people and businesses moving forward while our records stand still.
We are powerless to avoid these influences, and the rate of annual decay is steep. Estimates by Experian and Forrester Research put the range between one quarter and one third of our marketing lists each year. More recent industry research lands in a similar place, with B2B contact data decaying at somewhere around 22.5% annually on average, and considerably faster in high-turnover sectors like technology and SaaS. Whichever figure you trust most, the underlying message is the same: roughly a quarter of what sits in your CRM today won’t be reliable by this time next year, regardless of how carefully it was compiled.
Why data decay happens so quickly #
Job changes are the single biggest driver. People move roles, get promoted, or leave a company entirely, and the moment they do, their old email address and phone number become dead weight. Company changes compound the problem further. Mergers, acquisitions, rebrands, and closures can wipe out entire segments of a list in one go, sometimes without any obvious warning sign in your data to flag it.
Even when someone stays exactly where they are, their relevance to your campaigns can shift. A contact who was a Marketing Director eighteen months ago might now be a VP with a different set of priorities and a different level of authority over the decisions that matter to you. The data isn’t technically wrong. It’s just no longer telling the full story.
The cost of letting it slide #
It’s tempting to treat this as a minor housekeeping issue, something to deal with eventually. But the impact compounds quickly. Every bounced email damages sender reputation. Every disconnected number wastes a call that could have gone to someone reachable. Every outdated company detail skews how a campaign’s performance actually looks, making strong messaging appear to underperform when the real problem was never the message at all.
Research into the broader cost of poor data quality puts the figure in the billions across US businesses each year, once wasted marketing spend, lost sales opportunities, and the sheer hours spent chasing invalid leads are added together. Most of that cost is invisible until someone actually audits the list and sees how much of it no longer holds up.
Five ways to slow data decay #
- Data Cleansing. Implement regular data hygiene processes to verify and update contact information, company details, and other relevant information. This can involve using third-party data providers, conducting manual research, or bringing in automated data verification tools. It’s rarely glamorous work, but it’s the foundation everything else depends on.
- Continuous Data Enrichment. Research new information to help fill in gaps and keep data fresh. A record with a name and an old email tells you far less than one with a current role, a verified number, and a recent point of contact.
- Data Management Processes. Have regular audits to strip out duplicate information and ensure information is stored consistently, using a standard template. Inconsistent formatting across a list might seem cosmetic, but it quietly erodes the accuracy of any search or segmentation built on top of it.
- Consistent Updates. Ensure information is updated across all in-house platforms, to help maintain data consistency and reduce the risk of working with outdated information in one system while another has already moved on.
- Bring in More Raw Materials. Acquire fresh data from reliable sources, or manually research new information, to grow our list of contacts in specific commercial sectors or geographic regions. Cleaning what exists only solves half the problem; the list still needs to grow.
A practical rhythm worth adopting, rather than waiting for an annual deep clean: a quarterly hygiene pass catches decay while it’s still manageable, rather than letting a year’s worth of drift accumulate into something that feels too daunting to tackle.
Tired data makes our work tougher. It’s draining to work an out-of-date list, and it has a dramatic impact on the effectiveness of our marketing campaigns. Worse still, it’s easy to misread the symptoms, assuming a campaign’s poor performance reflects weak strategy or messaging when the real culprit was the list underneath it the whole time.
Time for a data spring clean, I think!
“Data isn’t units of information. Data is a story about human behaviour – about real people’s wants, needs, goals and fears. Never let the numbers, charts, platforms and methodologies cloud your vision. Our real job with data is to better understand these very human stories, so we can better serve these people. Every goal your business has is directly tied to your success in understanding and serving people.” – Daniel Burstein.
Thank you for reading.
Author: Richard Bull-Domican, founder of New Era Financial Introductions, a B2B lead generation consultancy with over twenty years of experience. The perspectives shared here come from two decades in the field; not theory, but practice.
I create small, digestible guides on Gumroad for business owners who hate aggressive tactics and prefer relationship-led approaches. New resources are added regularly. For longer reads on lead generation and the human side of sales, follow me on Medium and join the daily conversation on LinkedIn.
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Gumroad: https://richardbulldomican.gumroad.com/
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