Data Decay: Your CRM Loses 2.5% of Valid Numbers Every Month
There is a silent killer lurking in your CRM. It is not a software bug or an integration issue. It is something far more insidious: data decay.
Every month, approximately 2.5% of the phone numbers in your database become invalid. That is 30% per year. A database that was 100% accurate in January will have nearly one-third bad numbers by December - even if you never added a single new contact.
This decay happens automatically, invisibly, and relentlessly. And if you are not actively combating it, your connect rates are deteriorating right now.
What Is Data Decay?
Data decay is the natural degradation of contact information over time. Phone numbers that worked yesterday stop working today for a variety of reasons:
Job Changes The average professional changes jobs every 2.8 years. When someone leaves a company, their direct line often becomes invalid or gets reassigned. Their mobile number might stay the same, but if you only have their work number, you have lost them.
Phone Upgrades and Carrier Switches Consumers change phones and carriers regularly. While number portability helps, not everyone ports their number. New plans, new carriers, new numbers - and your CRM does not know about any of it.
Company Changes Businesses restructure, merge, relocate, and close. When a company moves offices, phone systems often change. When a company is acquired, direct dials may be consolidated. When a company closes, all numbers become invalid.
Personal Changes People move, divorce, retire, and otherwise reorganize their lives. Each change can invalidate contact information that was once perfectly accurate.
The Math of Decay
Let us put numbers to this problem:
Starting Point: 10,000 phone numbers, 85% valid (8,500 good numbers)
After 6 Months (15% decay):
- 8,500 x 0.85 = 7,225 good numbers
- New valid rate: 72.25%
After 12 Months (30% decay):
- 8,500 x 0.70 = 5,950 good numbers
- New valid rate: 59.5%
After 24 Months (60% decay):
- 8,500 x 0.40 = 3,400 good numbers
- New valid rate: 34%
A database that started at 85% quality drops to 34% quality in just two years with zero maintenance. This explains why so many CRMs are full of useless data.
How Decay Destroys Connect Rates
Decay creates a vicious cycle:
- Numbers become invalid - Decay happens invisibly
- SDRs dial bad numbers - No way to know which are bad
- Connect rates drop - More dials, fewer conversations
- Activity increases, outcomes decrease - Teams work harder for less
- Nobody investigates the cause - Blame falls on reps, not data
This is why teams often experience mysterious connect rate declines. They did not do anything wrong - their data just aged into uselessness.
Detecting Decay in Your Database
How do you know if decay is affecting you? Here are the warning signs:
Connect Rate Trend Analysis
Pull your connect rate by month for the past year. Is there a downward trend that is not explained by other factors? That is likely decay.
Age Analysis
Segment your database by data age. Calculate connect rate for:
- Contacts added in the last 90 days
- Contacts added 90-180 days ago
- Contacts added 180-365 days ago
- Contacts added over 1 year ago
If connect rates decline significantly with age, decay is your problem.
Disconnected Number Rate
Track how many dials result in disconnected tones or carrier messages. If this number is increasing, decay is accelerating.
Wrong Number Rate
Track how often dials reach someone who has no idea who you are trying to reach. This indicates reassigned numbers - a symptom of decay.
The Sources of Decay
Different data sources decay at different rates:
Third-Party Data Providers (fastest decay)
- Initial accuracy is often lower than claimed
- No ongoing verification
- Multiple customers calling the same stale data
- Expected decay: 35-40% per year
Marketing Leads (moderate decay)
- Initial accuracy depends on capture method
- Self-reported data can be intentionally wrong
- Job changes still apply
- Expected decay: 25-30% per year
CRM Historical Data (varies widely)
- Quality depends on original source
- Often neglected for years
- No refresh mechanism
- Expected decay: 30-40% per year
Customer Data (slowest decay)
- Actively maintained through interactions
- Changes often surfaced through service issues
- Still affected by personnel changes
- Expected decay: 15-20% per year
Fighting Decay: The Validation Cadence
The only way to combat decay is regular validation. Here is a recommended cadence:
For Active Calling Lists (Weekly)
If numbers are being dialed actively, remove bad numbers immediately. Flag disconnected calls. Track wrong numbers. Keep active lists clean.
For Prospect Database (Quarterly)
Validate your entire prospect database every 90 days using phone validation technology. This catches decay before it significantly impacts connect rates.
For Customer Database (Semi-Annually)
Customer numbers matter for retention and expansion. Validate twice per year to catch personnel changes before they become problems.
For Long-Term Archives (Annually)
If you maintain historical databases, validate at least once per year. Numbers that have been inactive for over 12 months should be assumed bad until proven otherwise.
The ROI of Validation
Let us calculate the return on regular validation:
Scenario: 10-person SDR team
Without Regular Validation:
- Database starts at 80% quality
- After 12 months: ~55% quality
- Average connect rate: 4% (with decayed data)
- Daily conversations per SDR: 6
- Monthly meetings booked (team): 120
With Quarterly Validation:
- Database maintained at 75-80% quality
- Connect rate maintained: 12%+ (with clean data)
- Daily conversations per SDR: 18
- Monthly meetings booked (team): 360
The Difference:
- 240 additional meetings per month
- At $50K average deal size and 20% close rate
- $2.4M additional annual pipeline
Investment: ~$50,000/year for validation Return: $2.4M additional pipeline ROI: 4,700%
The math is not close. Regular validation is one of the highest-ROI investments a sales team can make.
Building Decay-Resistant Processes
Beyond validation, several practices help minimize decay impact:
Capture Multiple Contact Points
When adding prospects to your database, capture:
- Direct line
- Mobile number
- Personal email (in addition to work)
- LinkedIn profile
Multiple contact points provide backup when one decays.
Document Data Age
Track when each contact was added and last validated. This metadata enables age-based prioritization and helps identify decay patterns.
Implement Feedback Loops
Create easy mechanisms for SDRs to flag bad numbers:
- Quick "disconnected" buttons in dialers
- Automatic flagging after multiple failures
- Regular data quality reports
The faster bad numbers are identified, the less they pollute your calling lists.
Clean New Data Immediately
Never add new contacts without validating first. Data providers lie about accuracy. Catch bad data at the door, not in your connect rate.
Related Reading
- Your CRM's Dirty Secret - The full story on CRM data quality
- The Hidden Cost of Bad Phone Data - Calculating the true impact
- Your Data Provider Is Lying to You - Why initial data quality is often poor
Conclusion
Data decay is inevitable. Your phone numbers will become invalid over time - that is simply how the world works. People change jobs, change phones, and change lives.
What is not inevitable is the impact of decay on your sales performance. Teams that implement regular validation maintain high connect rates year after year. Teams that ignore decay watch their connect rates mysteriously decline while wondering what went wrong.
The choice is yours: accept decay as inevitable and watch productivity erode, or invest in validation and maintain the data quality that drives results.
Ready to fight data decay? ConnectRate makes database validation fast and affordable, helping you maintain the data quality that drives connect rates.