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Last click attribution models undervalue the contribution of Facebook ads by up to 30% in cross-channel advertising campaigns.

The last click attribution model, which credits the last ad clicked before a sale or other conversion with all the value for that conversion, is still widely used to measure the contribution of advertising.  

However, a recent Kenshoo study focused on Facebook advertising helps expose its weaknesses.

In reality, most digital marketers appreciate that consumers tend go through a number of interactions or clicks throughout the buying cycle from awareness and consideration to intent and purchase.

Giving credit to Facebook, or any other channel, solely when it is the last ad clicked before the conversion does not properly reflect its value. 

But there is not a lot of data to highlight the flaws of last click. So we tested the model by analysing the campaign performance data for our clients who manage ads across multiple digital marketing channels.  

As not all marketers define conversions the same way, we used a Cost-Per-Acquisition (CPA) metric across all advertisers in the sample. We calculated CPA by aggregating all recorded conversions and dividing that number by the total media cost of the ads which drove them.

We then compared the last click model to five other industry standard attribution models.For each comparison, we found that last ad/click under-valued Facebook ads: 

  • First Only (first click receives all credit): Facebook was undervalued 30%.
  • Prefer First (first click gets most credit, subsequent click get decreasing credit): Facebook undervalued 20%.
  • Divide Equally (credit is shared equally across all clicks): Facebook undervalued 16%.
  • Prefer Last (credit given increases from first to last – last click gets most credit): Facebook undervalued 12%
  • U-Shaped (first and last clicks get majority weighting with middle clicks getting less): Facebook undervalued 15% 


The study underlines why marketers who rely on last click attribution to optimise their campaigns could be making million-dollar decisions based on flawed data. 

They need to make use of models and techniques that better reflect the reality of consumer behaviour. The upshot will be improved budget allocation and campaign performance.

Here's the full whitepaper: Quantifying the Impact of Multi-touch Attribution

Matthew Whitehead

Published 25 September, 2013 by Matthew Whitehead

Matthew Whitehead is Lead Solutions Consultant, EMEA at Kenshoo UK Ltd  and a contributor to Econsultancy.

15 more posts from this author

Comments (6)

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Great article! Please fix the link: Quantifying the Impact of Multi-touch Attribution, is not working. Thanks.

about 3 years ago


sumudu tharanga

i hope maxmum

about 3 years ago



Link to white paper not working. Please fix.

about 3 years ago


Rens van Boxmeer, Online marketeer at Vodafone

Just remove the "."at the end of the URL

about 3 years ago

Graham Charlton

Graham Charlton, Editor in Chief at ClickZ Global

Links should work now.

about 3 years ago



Good article - thanks.

In the industry I work in (social strategy for professional services B2C and B2B) First Click is the best way for me to show ROI and I'm fascinated to know that Facebook was undervalued by nearly a third. But all of these models only asses click data not data reflecting the process.

Looking forward to those improved processes soon!

about 3 years ago

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