A lead record is not one thing that goes stale on one date. It is a composite of fields, each decaying at its own rate. Job titles erode fast. Company names barely move. Treating them the same is like assuming all isotopes have the same half-life.
The Numbers
annual decay rate
annual decay rate
annual decay rate
annual decay rate
Job titles have a half-life of 7.5 months. After two years, a stored job title has been through more than three half-lives. The probability it's still correct is roughly equivalent to a coin flip.
Email addresses are more durable: 18-month half-life. Phone numbers sit between the two at 14.5 months. Company firmographics and industry classification can last years without changing.
Temperature Accelerates Decay
In food science, the Arrhenius equation describes how temperature accelerates chemical degradation. A 10-degree increase roughly doubles the spoilage rate. Data decay works the same way, with industry velocity serving as the temperature.
| Environment | Decay Multiplier |
|---|---|
| Post-M&A company | 3.0x for 12 months |
| Post-layoff company | 2.5x for 6 months |
| Early-stage startup | 2.0-3.0x |
| High-growth SaaS | 1.5-2.0x |
| Established enterprise | 1.0x (baseline) |
| Stable manufacturing | 0.5-0.7x |
| Government entity | 0.3x |
A SaaS startup that just went through a funding round is operating at extreme temperature. Data decays 2-3x faster than baseline. A government agency with 6.2-year median tenure is deep freeze. Same data, radically different shelf life.
What This Means for Your CRM
If you're sitting on a two-year-old lead list and assuming it's roughly 80% accurate, the math says otherwise.
A two-year-old lead list targeting SaaS companies may have fewer than 20% of its job titles still correct. The emails and company names are probably fine. The contact-level data is not.
The practical implication: stop thinking about "data freshness" as a single metric. Think about it field by field. Your company-level data may have years of useful life. Your contact-level data may already be expired.
The Decay Equation
Field_Confidence(t) = Initial_Score × e(-λ × t) × volatility_multiplier
Each field has its own decay constant (λ). The volatility multiplier adjusts for industry conditions. Event-driven triggers (layoffs, acquisitions, leadership changes) can override gradual decay with immediate invalidation.
This model was extracted from nuclear physics (radioactive decay), food science (Arrhenius equation), and information theory (Shannon entropy). Three domains, same underlying math, applied to contact data.
This concept is one of seven frameworks in the ENRICH series, built by reverse-engineering lead enrichment from six unrelated source domains. The methodology that produced this insight is the same one behind 421 frameworks and counting.