Time decay attribution model: What it is and how it works

Last ads before a conversion often get all the credit. The time decay attribution model challenges that assumption by spreading credit across multiple touchpoints, giving more weight to the ones that happen closer to the conversion.

It feels like a smarter, more balanced approach than the last-click attribution model. But does it solve the full problem? Not quite. In this article, we’ll break down what the time decay model is, how it works, and the blind spots you need to know before relying on it to allocate marketing efforts.

What is time decay attribution model?

The time decay attribution model is a recency-based system for assigning weighted credit to marketing touchpoints. It assigns more credit to the touchpoints closer to a conversion. Interactions that happened further back in time still count, but their influence gradually decreases or “decays.”

Time decay attribution reflects recency bias: the belief that what happened most recently deserves more importance. 

Read more: What is attribution in marketing?

Why do marketers use time decay attribution?

Marketers often choose the time decay model because it feels like a practical step up from last-touch attribution models. It’s appealing for a few reasons:

• More balanced than last-click: It spreads credit across multiple touchpoints while still giving more weight to the ones closer to conversion
• Easy to set up in platform analytics: Many analytics tools, including Google Analytics and Adobe Analytics, offer time decay as a built-in option
• Intuitive logic: It aligns with the belief that recent customer interactions have more influence than those that happened further back in time

For teams that want a straightforward way to account for the customer journey, time decay often feels like the safest choice.

How does time decay attribution work?

Time decay attribution gives some credit to every touchpoint. But the closer the interaction is to the conversion, the more weight it carries. Here’s how it works step by step:

1. Credit is assigned to every touchpoint

In time decay attribution, no interaction is ignored. Every touchpoint a customer has with your brand and marketing campaign contributes to the conversion.

2. Recent customer interactions get more weight

The closer the touchpoint is to the conversion event, the more influence it is assumed to have. Later-stage interactions carry more weight than those that happened earlier.

3. Attribution credit decreases over time

Earlier touchpoints gradually lose value or “decay.” This method creates a sliding scale of credit, where each step away from the conversion carries a smaller share.

How the time decay model distributes credit

The time decay model uses a concept called half-life to decide how much weight to give each touchpoint. The half-life is simply the time it takes for a touchpoint’s credit to drop by half.

• With a short half-life (like 7 days), recent interactions dominate
• With a longer half-life (like 14 or 30 days), credit spreads out more evenly across the journey

Let’s take a simple time decay attribution model example to illustrate how credit might be assigned during a 30-day customer journey. In the following case, the email right before conversion gets the most credit, while the social ad at the very beginning of the journey gets the least.

Marketing touchpoint	Days before conversion	Credit assigned (example %)
Social media ad	29	5%
Display ad	15	15%
Organic search	5	30%
Email link	0	50%

Time decay vs. other marketing attribution models: Key differences

Time decay is just one of several rule-based attribution models you can use. Each marketing attribution model has its own way of assigning credit across the customer journey, and each comes with built-in biases.

Attribution model	How it works	Key limitation	Best for
Time decay attribution model	Credit is spread across all touchpoints, with more weight on the most recent ones	Skews credit toward lower-funnel interactions	Longer sales cycles, retargeting, email nurtures, and short-window promotions where late-stage interactions drive action
Last-click attribution model	All credit goes to the final touchpoint before conversion	Overvalues bottom-funnel channels like search	Direct-response, short cycles, branded search optimization, simple media attribution reads
Linear attribution model	Credit is split equally across all touchpoints	Assumes every interaction is equally important	Marketing attribution modeling where the team values each interaction equally across longer customer journeys
Position-based attribution model	40% of credit goes to the first touch, 40% to the last, and 20% split in between	Overemphasizes entry and closing channels	Valuing discovery and close while still recognizing mid-funnel assist

Read more: The differences between marketing mix modeling and multi-touch attribution model

Limitations of time decay attribution

Of all the attribution models, time decay is often seen as a fairer alternative to last-click. But it still carries serious blind spots when you’re trying to measure true marketing effectiveness. The most common issues of time decay attribution are:

• Overvaluing lower-funnel channels: Paid search, retargeting, and affiliates usually happen right before conversion, so they end up with most of the credit even if awareness campaigns sparked the journey
• Undervaluing brand and awareness efforts: Upper-funnel tactics like display, social, or content marketing get little recognition because they typically occur earlier in the path to conversion
• Assuming recency equals impact: The model automatically favors the latest touchpoints, but a recent click isn’t always the true driver of conversion
• Ignoring external factors: Elements like marketing seasonality, competitor promotions, or organic growth can heavily influence conversions, yet the model doesn’t account for them

Read more: The ultimate guide to full-funnel optimization

Is time decay attribution enough for modern marketers?

No. Time decay is a step up from last-click, but it’s still a rule-based model built on assumptions rather than evidence. It spreads credit more fairly across the journey, but it only reflects when touchpoints happened, not whether they actually caused the conversion.

If you’re running simple, short-path campaigns, time decay may feel useful. But as soon as you’re dealing with multi-touch, cross-channel media journeys, its weaknesses show fast.

You need marketing measurement that goes further with:

• Marketing incrementality: This shows whether a channel drove lift or if the conversion would have happened without it
• Causal analytics: This isolates cause-and-effect relationships, giving you confidence in what actually drives results.
• Evidence-based insights: This moves beyond timing assumptions to reveal what’s fueling growth across every stage of the funnel.

Move beyond time decay attribution with Keen

Time decay and other rule-based models stop at describing the path to conversion. What marketers actually need is proof of which channels caused growth and a way to forecast what will work next. Keen’s MMM platform delivers that clarity by measuring the incremental impact of every channel. 

Instead of guessing which touchpoints mattered most, the platform uses marketing mix modeling (MMM) with machine learning to test what would have happened without the spend. That means you see which channels actually cause revenue growth, not just the ones closest to conversion.

With Keen, you can

• Forecast sales: Go beyond reporting on past performance and model what different investment scenarios will deliver.
• Get clearer ROI by channel: Understand the real value of both brand-building and performance investments.
• Allocate marketing budgets with confidence: Shift spend toward the channels that deliver measurable lift.

If you’re still relying on the time decay model, it’s time to test what’s actually incremental. Start a free trial to see how Keen shows you the drivers of revenue.