Time Decay Attribution in Marketing: A Complete Guide to This Multi-Touch Model
Time Decay Attribution in Marketing: A Complete Guide to This Multi-Touch Model
TL;DR — Quick Answer
2 min readTime decay attribution is a multi-touch model that weights recent touchpoints more heavily, offering a middle ground between simple last-click models and complex algorithmic attribution.
"Attribution is dead." That is a sentiment echoed all the time within marketing circles. But if single-touch models distort the picture, it does not mean attribution is dead. You should consider alternatives, such as multi-touch attribution models, that let you see the full picture.
Time decay attribution is one such model.
What Is Time Decay Attribution?
Time decay attribution is a multi-touch model that assigns more credit to touchpoints closer to the conversion. The more recent the touchpoint, the greater the weight.
The model assigns credit based on a half-life you set. If your half-life is seven days, a touchpoint that occurred a week before conversion receives half the credit as one that occurred on the day of conversion. More than two weeks out, it receives a quarter.
An Example
Consider a hypothetical journey over three weeks:
- Day 1: Blog post about business financing (21 days out)
- Day 8: Email newsletter highlighting rates (14 days out)
- Day 15: Product comparison page visit (7 days out)
- Day 22: Direct return and application submission
| Touchpoint | Days before conversion | Normalised weight | Attributed value |
|---|---|---|---|
| Blog post (organic search) | 21 | 7.73% | $773 |
| Email newsletter | 14 | 15.45% | $1,545 |
| Product comparison page | 7 | 30.90% | $3,090 |
| Application page (direct) | 0 | 45.92% | $4,592 |
The application page and comparison page receive the largest share because they were closest to the decision. But the blog post and email also get credit.
Comparing Attribution Models
| Model | Type | Credit distribution |
|---|---|---|
| Last-click | Single-touch | 100% to final touchpoint |
| First-click | Single-touch | 100% to first touchpoint |
| Linear | Multi-touch | Equal credit to all touchpoints |
| Position-based (U-shaped) | Multi-touch | 40% first, 40% last, 20% split across middle |
| Time decay | Multi-touch | Weighted by recency |
| Algorithmic (data-driven) | Multi-touch | Weighted by statistical analysis |
Last-Click Attribution
Assigns 100% to the final touchpoint. Simple to report on but ignores every earlier interaction. Best for short sales cycles.
First-Click Attribution
Assigns all credit to the first touchpoint. Spotlights awareness channels but ignores what happened afterwards. Best for brand awareness campaigns.
Linear Attribution
Distributes credit equally across all touchpoints. Balanced but treats a casual blog visit the same as a demo request. Best for understanding channel health in long nurture cycles.
Position-Based (U-Shaped) Attribution
Assigns 40% to first, 40% to last, 20% across the middle. Balances awareness and conversion. Best for B2B environments.
Algorithmic (Data-Driven) Attribution
Uses machine learning for the most nuanced view but requires large data volumes. Best for enterprises with high traffic and technical resources.
Benefits of Time Decay Attribution
Gives a Better Picture of the Customer Journey
It looks at the entire journey, weighting credit based on timing. This helps stakeholders see the whole picture.
Supports Long Sales Cycles
It handles long journeys well, crediting late-stage touchpoints without completely ignoring earlier ones.
Three Limitations
1. It Undervalues Early Interactions
Top-of-funnel activity receives the least credit, even if it was the reason a prospect found you.
2. It Is Difficult to Find the Optimal Half-Life
Most platforms default to seven days, but this is arbitrary. You need to adjust based on your sales cycles.
3. It Is Misaligned with Long-Term Strategy
It favours short-term optimisation and may cause over-investment in bottom-of-funnel channels.
Choosing the Right Model
Ask yourself:
- Does your sales cycle span multiple weeks?
- Are you optimising bottom-of-funnel performance?
- Do you need a middle-ground approach?
- Do you need to justify marketing spend to stakeholders?
- Are most conversions influenced by multiple channels?
Time decay attribution is also useful when combined with another model -- for instance, running first-click alongside it to see which channels introduce prospects versus which ones close them.
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