Your rep opens the Hot lead queue. At the top: someone who replayed an integration demo last month and hasn't returned. Further down: a buyer who reviewed implementation this morning. The queue remembers enthusiasm, but it can't distinguish old interest from a live evaluation.
Lead score decay reduces the contribution of older engagement to a lead's current score. Apply it to behavioral intent, not automatically to account fit, and let meaningful new activity contribute fresh evidence. The aim is to prioritize attention, not declare quiet buyers lost.
I want a score to answer a practical question: who deserves attention today, and why? If the answer requires a rep to mentally subtract weeks of stale activity, the model isn't doing enough work.
What is lead score decay, and what should it preserve?
Lead score decay gradually reduces the scoring value of aging buyer activity. It should reduce urgency without erasing the context that makes a later conversation useful.
The distinction: Activity history tells you what a buyer has done. A decaying intent score estimates how much evidence you have of active interest now.
Say an operations director watches a product tour, replays an approval workflow and downloads an implementation document. Those actions suggest a problem worth discussing. After a long silence, they still tell you which problem mattered, but they provide weaker evidence that someone should call today.
Keep the document download in the history. Keep the workflow interest. Let their contribution to current priority fade.
This matters particularly with interactive demo software, where one session can produce many events. Video plays, Walkthroughs, replays and link clicks create a detailed record. They don't necessarily represent separate decisions to buy. Without sensible event weights and decay, a busy session can keep someone near the top long after their project pauses.
Start with the meaning of your Buying Intent Signals, then add recency. Decay won't rescue a model that gives a casual opening the same importance as a deliberate implementation review.
Should intent and fit scores decay differently?
Yes. Intent should fade as behavioral evidence ages; fit should change when the underlying buyer information or your ideal customer profile changes.
A director at a company in your target industry doesn't become a worse fit because they haven't watched another demo. Their project may have stalled. Their role, company size and likely use case may be exactly as relevant as before.
Dale, the demo automation platform, separates Intent and Fit scores in its configurable Lead Scoring model. The default weighting is 70% intent and 30% fit, with a default intent half-life of 10 days.
Here's a simplified illustration, not a forecast of a particular contact's score. Suppose intent and fit both start at 80. The blended score is 80. If intent later halves to 40 while fit stays at 80, the same weighting produces a score of 52.
Nothing about that calculation says the company stopped being worth selling to. It says the case for immediate attention has weakened.
Keep both components visible when reviewing the queue. A highly engaged student researching a category and a quiet decision-maker at an ideal account present different opportunities. A blended number alone can obscure that difference. The intent and fit scoring model provides the useful separation.
How do you choose a lead score decay rate?
Choose a decay rate around the usual gaps between meaningful evaluation steps, not just the length of your sales cycle. A buyer taking time between security reviews is different from a self-serve prospect who explored the product once and disappeared.
A half-life is not an expiry date. It describes the time it takes an aging contribution to lose half its value. Shorter half-lives make prioritization more sensitive to recent activity; longer ones preserve evidence through slower evaluations.
I wouldn't start by debating the perfect number. Start by reading actual buyer timelines:
- Identify deliberate evaluation. Look for relevant topic selections, focused replays, implementation downloads and substantive replies. Don't count every click as equally informative.
- Find the normal quiet periods. Check how much time passes between discovery, technical review and the next buyer action. Separate expected waiting from unexplained inactivity.
- Compare buying motions. A small-team purchase and a procurement-led evaluation shouldn't automatically share the same timing assumptions.
- Test recognizable cases. Include active buyers, genuinely stalled evaluations and contacts who returned after a pause. Ask whether the proposed scores match the evidence.
- Define the response. Agree what deserves a call, a focused follow-up or lower-pressure nurture before changing the model.
The score simulator lets you test settings before relying on them operationally. Use it to challenge a default, not merely confirm that the settings save.
Be especially careful with long sales cycles. A lengthy procurement phase doesn't mean an old demo replay remains a strong intent signal throughout. The agreed procurement timeline is better evidence than the replay. Keep that context alongside the score rather than stretching decay to compensate for missing deal information.
What should Hot, Warm, Cold and New mean after decay?
Hot, Warm and Cold should guide the intensity of attention as current intent changes. New means something different: the contact hasn't opened the demo, so there is no demo engagement to judge.
Don't make these labels do the job of opportunity stages. They describe prioritization, not whether a deal has completed technical validation or entered procurement.
| Status | What it tells the rep | Sensible next action |
|---|---|---|
| Hot | The model indicates strong current priority. | Read the latest signals and respond to the relevant problem. |
| Warm | Some intent remains, but urgency is less certain. | Offer a focused next step based on known interests. |
| Cold | Current scoring evidence supports lower priority. | Use lower-pressure nurture and watch for renewed activity. |
| New | The contact hasn't opened the demo. | Check invitation context rather than assume product rejection. |
An unopened invitation might reflect poor timing, an overlooked email or an irrelevant introduction. You don't know yet. Treating that contact as Cold turns missing data into a negative judgment.
The reverse mistake is just as costly. A buyer with an agreed technical workshop shouldn't lose their follow-up because their demo activity faded. Honor the commitment. Scoring should help reps choose among uncertain opportunities, not override an explicit conversation.
What should happen when a quiet buyer returns?
New activity should contribute fresh intent without automatically restoring every old point. Review what the buyer returned to do, not merely whether they appeared again.
A brief reopening of a shared link might mean someone was tidying their inbox. Reviewing deployment, downloading an implementation document and returning to pricing suggests a more focused evaluation. Neither proves a purchase, but the second pattern gives a rep a stronger reason to investigate.
Dale Radar connects website visits with contacts and their demo history, and website behavior feeds Lead Scoring automatically. That extends the evidence beyond the demo: a contact may stop replaying the product story while continuing their research on the website. The website visitor intelligence workflow helps bring those activities into the same journey.
Read the earlier history before reaching out. If approval routing was their original concern and deployment is their new interest, the useful question is whether they need help assessing rollout. Don't restart the conversation with a generic request to book discovery.
Also check whether the evaluation moved to someone else. The share graph shows demo sharing between colleagues. That can help explain why the original viewer went quiet, although sharing alone doesn't establish budget, authority or agreement.
A useful message might be: Would a walkthrough of rollout responsibilities help with your implementation review? It addresses the work the buyer may be doing. It doesn't announce that you've inspected their browsing history.
How should score decay change automated follow-up?
Decay should usually change the pressure of follow-up, not trigger another generic reminder. Use observed interests to choose the content, and check for existing sales conversations before adding automation.
Consider an illustrative case: a well-matched contact selected approval workflows, watched the relevant demo and then went quiet. A focused resource about approval setup is more defensible than repeated requests for a meeting. If they later return to implementation content, the rep has a reason to reassess.
Segments can group contacts by behaviors including selected topics, document downloads and demo sharing. Campaigns can send automatically when a contact joins a segment. Use behavior-based Segments and Campaigns to connect the follow-up to what the person actually explored, rather than assuming each score change deserves an email.
Before switching anything on, settle ownership. Who checks whether the contact is already working with an account executive? What happens if several audiences overlap? When should a human review the activity instead of sending another message? These are operating decisions, not details to leave until someone receives conflicting outreach.
Demo automation gives you specific interests to respond to. Ignoring those interests wastes the most useful part of the data.
How do you know whether your decay model is working?
A useful decay model makes the sales queue more relevant without hiding genuine evaluations. Lower average scores are not, by themselves, evidence of improvement.
Review a manageable sample containing active opportunities, stalled evaluations, returning buyers and unopened invitations. Read each timeline before revealing its score. Otherwise, the number can anchor your judgment and make the test circular.
Use this short review checklist:
- Old activity no longer keeps inactive contacts permanently Hot.
- Meaningful new activity makes returning buyers visible again.
- Fit doesn't fall simply because engagement stopped.
- Unopened invitations remain New.
- Reps can explain the evidence behind a priority.
- Agreed buyer commitments still guide follow-up.
Look closely at disagreements. If stale contacts still dominate, inflated event weights may be the problem. If active buyers disappear during normal evaluation gaps, decay may be too aggressive. Change one assumption at a time; changing weights, thresholds and timing together makes the result hard to interpret.
To inspect the workflow, explore the Dale interactive demo and check Dale pricing for Lead Scoring and website intelligence availability. Then bring real contact timelines to your next sales review. Ask reps to rank them without scores, compare that ranking with the model, and investigate the first meaningful disagreement.