Time-Decay Attribution

A multi-touch attribution model that assigns increasing credit to touchpoints closer to the conversion event, based on the assumption that more recent interactions had greater influence on the purchase decision.

Also known as: time decay model, recency-weighted attribution

Why It Matters

Time-decay attribution strikes a practical balance between giving credit to all touchpoints and recognizing that recency matters. A product demo yesterday likely influenced the purchase more than a blog post three months ago, even if both played a role.

This model is particularly well-suited for businesses with longer sales cycles where many touchpoints accumulate over time. In a 90-day enterprise sales process, the early-stage awareness touchpoints receive some credit but are appropriately weighted less than the late-stage evaluation and decision touchpoints.

Time-decay also produces results that align with how most marketers intuitively think about attribution. The gradual reduction in credit over time feels more natural than the sharp cutoffs of first-touch or last-touch, making it easier to get organizational buy-in for the model's results.

How to Calculate

Time-decay models typically use a half-life parameter. If the half-life is 7 days, a touchpoint 7 days before conversion receives 50% of the credit of the most recent touchpoint, a touchpoint 14 days before receives 25%, and so on. The credits are then normalized to sum to 100%. The decay function is: credit = 2^(-time_since_touchpoint / half_life), normalized across all touchpoints.

Industry Applications

E-commerce

A consumer electronics retailer uses a 7-day half-life time-decay model. Retargeting ads and abandoned cart emails receive the most credit (being closest to conversion), while social media awareness campaigns receive less but measurable credit. This balanced view prevents the team from cutting social entirely.

SaaS

An enterprise security company uses a 21-day half-life for their 90-day average sales cycle. The model shows that late-stage touchpoints (demo, pricing page, ROI calculator) receive the most credit, but early-stage analyst reports and industry events still receive 15-20% of total credit, validating continued investment.

How to Track in KISSmetrics

Configure time-decay attribution in KISSmetrics by selecting the time-decay model in the Attribution Report. Adjust the half-life parameter to match your business - shorter half-lives for impulse purchases, longer half-lives for considered B2B decisions. Monitor how credit distribution changes as you adjust the half-life to find the setting that best reflects your business reality.

Common Mistakes

  • -Using a half-life that does not match your actual sales cycle, which over-credits or under-credits early touchpoints
  • -Applying time-decay to short journeys with only 2-3 touchpoints where the decay effect is negligible
  • -Not testing different half-life settings to understand how sensitive your channel rankings are to this parameter
  • -Forgetting that time-decay still undervalues awareness channels that are structurally positioned early in the journey

Pro Tips

  • +Test half-life values of 7, 14, and 30 days and see how channel rankings shift - stable rankings across settings indicate robust attribution
  • +Use a shorter half-life for ecommerce (7-14 days) and a longer one for B2B SaaS (14-30 days)
  • +Combine time-decay with position-based attribution for a hybrid model that values both recency and position
  • +Use time-decay for operational channel management and incrementality testing for strategic budget decisions

Related Terms

See Time-Decay Attribution in action

KISSmetrics tracks every user across sessions and devices so you can measure what matters. Start free - no credit card required.