When a customer finally makes a purchase, which marketing channel gets the credit? With last click attribution, the answer is simple: whichever touchpoint came last. This model has been a staple in digital marketing for years, but is it the right choice for your business?

What Is Last Click Attribution?

Last click attribution is a marketing measurement model that assigns 100% of the conversion credit to the final touchpoint before a customer converts. It doesn’t matter how many ads they saw, emails they opened, or social posts they clicked—only the last interaction counts.

This model answers one specific question: “What was the customer doing right before they bought?”

How Last Click Attribution Works

Let’s say a customer named Sarah is shopping for running shoes:

  1. She sees an Instagram ad for your store (no click)
  2. A week later, she searches “best running shoes” and clicks your Google ad
  3. She browses but doesn’t buy
  4. Three days later, she gets your email newsletter and clicks through
  5. She finally makes a purchase

With last click attribution, the email newsletter gets 100% of the credit. The Instagram ad and Google ad? They contributed nothing—at least according to this model.

Advantages of Last Click Attribution

Despite its simplicity, last click attribution has real benefits:

  • Easy to understand — No complex calculations or data science required
  • Simple to implement — Most analytics tools use this as the default
  • Clear accountability — Each conversion ties to one specific channel
  • Good for bottom-funnel analysis — Shows which channels close deals

For small businesses just starting with analytics, last click provides a clear starting point without overwhelming complexity.

The Limitations You Should Know

Last click attribution has significant blind spots:

  • Ignores the full customer journey — Early touchpoints that built awareness get zero credit
  • Undervalues brand marketing — Social media, content marketing, and display ads often appear early in the funnel
  • Can mislead budget decisions — You might cut channels that actually drive awareness
  • Doesn’t reflect reality — Rarely does a single touchpoint cause a purchase

In Sarah’s example, cutting the Instagram budget because it “doesn’t convert” would be a mistake—she might never have discovered your brand without that first ad. According to Google’s documentation on attribution, understanding the full conversion path is essential for accurate marketing analysis.

When to Use Last Click Attribution

Last click attribution works best when:

  • You have a short sales cycle (impulse purchases, low-cost items)
  • You’re focused on direct response campaigns
  • You need a simple baseline to start measuring
  • Your marketing primarily targets bottom-funnel customers

It’s less suitable for businesses with long consideration periods, multiple touchpoints, or significant brand awareness efforts.

Other Attribution Models to Consider

If last click feels too limited, here are alternatives (as outlined in HubSpot’s guide to attribution modeling):

ModelHow It Works
First ClickCredits the first touchpoint (good for measuring awareness)
LinearSplits credit equally across all touchpoints
Time DecayGives more credit to recent touchpoints
Position-Based40% to first, 40% to last, 20% split among middle

Many businesses use multiple models together to get a complete picture of their marketing performance.

Bottom Line

Last click attribution is a straightforward way to measure which channels drive conversions. It’s perfect for beginners and works well for direct response marketing. However, it tells only part of the story—the final chapter, not the whole book.

As your marketing grows more sophisticated, consider combining last click with other models. Understanding the full customer journey helps you make smarter budget decisions and build more effective campaigns.

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Alexander Vermeer

Web analytics specialist with over 8 years of experience implementing tracking solutions for businesses of all sizes. Passionate about helping companies make sense of their data without drowning in complexity. When not debugging GTM containers, you'll find me advocating for privacy-respecting analytics approaches.

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