Lead Scoring Decay: What It Is and How to Set It
What lead scoring decay means
Lead scoring decay is a rule that lowers a lead's behavior score over time when engagement goes quiet. A standard lead score has two parts: a fit (demographic or firmographic) score that says who they are, and a behavior (engagement) score that says how interested they are right now. Decay applies only to the behavior half, because interest is the part that gets stale.
Without decay, points only ever accumulate. A lead who downloaded one ebook eighteen months ago can sit permanently above your MQL threshold, even though they've gone cold. Decay reverses that drift: as time passes without new activity, the behavior score erodes, and the lead eventually drops back below the threshold unless they re-engage.
Why decay matters
Decay matters because a lead score is meant to predict current sales-readiness, and engagement loses predictive value the older it gets. A click from last week says far more about buying intent than a click from last year. Without decay, your MQL pool slowly fills with leads who looked hot once and never came back.
What goes wrong without it
- Sales loses trust in MQLs. Reps keep getting handed "qualified" leads who don't remember your brand, and they start ignoring the score entirely.
- Inflated MQL counts. Marketing reports a growing pipeline of MQLs that never convert, hiding the real MQL-to-SQL conversion rate.
- Wasted nurture. Long-cold leads keep triggering high-touch sequences meant for active buyers.
How to set a decay window
Set a decay window by anchoring it to your sales cycle, then subtracting points on a recurring schedule after a defined period of inactivity. Follow these steps:
- Measure how fast leads go cold. Look at how long an engaged lead typically takes to convert or disengage. Your decay window should be a bit longer than that natural cycle. A common rule of thumb is 30 to 90 days of inactivity.
- Decide what counts as "inactivity." Define the activity reset trigger: any meaningful behavior (email click, page visit, form fill, event registration) resets the clock. Email opens alone are usually too weak to count.
- Choose a decay rate. Either subtract a flat number of points per period (for example, −5 points every 30 days of inactivity) or remove a percentage of the current behavior score per period. Percentage decay is gentler on high scorers.
- Set a floor. Stop decay at zero so behavior scores never go negative and drag a good-fit lead below where they belong.
- Protect the fit score. Make sure your rule touches only behavior points. Demographic and firmographic fit should never decay.
- Test and tune. Run the rule for a quarter, then check whether decayed leads were actually inactive and whether re-engaged leads climbed back correctly. Adjust the window and rate from there.
applied once per decay period after the inactivity window is exceeded
A worked example
Suppose your MQL threshold is 50 behavior points, your inactivity window is 60 days, and your rule subtracts 10 points for every 30 days of continued inactivity.
- Day 0. A lead attends a webinar and clicks two emails, reaching a behavior score of 70, well above the MQL line.
- Day 60. No further activity. The inactivity window is now exceeded, so decay begins.
- Day 90. First decay period: 70 − 10 = 60. Still an MQL, but cooling.
- Day 120. Second period: 60 − 10 = 50. Right at the threshold.
- Day 150. Third period: 50 − 10 = 40. The lead drops below 50 and is no longer an MQL.
Now say on day 155 the lead returns and books a demo worth 25 points: 40 + 25 = 65. They jump back above the threshold instantly, exactly the behavior you want. Decay never punished them; it simply made sure old engagement couldn't hold the MQL flag while they were silent.
Common mistakes
| Mistake | Why it bites | Fix |
|---|---|---|
| Decaying the fit score too | Penalizes a perfect-fit account for not clicking | Decay behavior points only |
| Window shorter than the sales cycle | Decays leads who are mid-evaluation, not cold | Anchor the window to real cycle length |
| No score floor | Negative scores distort segments and reports | Stop decay at zero |
| Counting email opens as activity | Auto-opens reset the clock falsely, so nothing decays | Reset only on clicks, visits, and form fills |
| Set-and-forget | The window drifts out of sync as the funnel changes | Re-check the rate and window each quarter |
Frequently asked questions
Should I decay demographic or fit scores too?
No. Decay only the behavior score, not demographic or firmographic fit. A lead's job title, company size, and industry don't get less true over time, so decaying them is wrong. Engagement is what goes stale, so engagement is what you decay.
What is a good decay window for lead scoring?
Anchor it to your sales cycle. A common rule of thumb is 30 to 90 days of inactivity before decay starts. Short B2C cycles lean shorter; long, complex B2B deals lean toward 90 days or more. Test against how quickly your real MQLs go cold.
Does lead scoring decay delete points permanently?
Usually no. Most platforms reduce the behavior score on a schedule, but fresh activity adds points back, so a returning lead can climb above the MQL threshold again. The decay simply ensures old, one-time engagement can't hold a lead there indefinitely.
Can I add lead scoring decay in HubSpot and Marketo?
Yes. Marketo has native scoring with time-based decay rules in smart campaigns. HubSpot score properties don't decay natively, so teams usually build a workflow that subtracts points after a set period of inactivity, or rebuild the engagement score on a rolling window.
Last updated: 14 June 2026