This is the subhead for the blog post
The great retailer John Wanamaker is famous for having pioneered modern advertising and is frequently attributed with saying “Half of the money I spend on advertising is wasted; the trouble is I don’t know which half.” Mr. Wanamaker would probably not be surprised to learn that close to 100 years after his death, advertising measurement and attribution remains a significant challenge for most marketers, especially in today’s multi-channel world, in which brands have to interact with consumers in their channels on their terms.
Of course, tremendous advances have been made in advertising performance measurement, especially in digital marketing. With our ability to track and report on virtually every touch-point in the customer journey, it is surprising that most marketers continue to measure the performance of their marketing initiatives with outdated attribution models that obscure the true value of any given ad or campaign.
I’m talking about “Last Click” or “Last Ad” attribution. We’ve grown accustomed to using last-click, partly due to the history of search engine marketing, which I won’t go into here, and partly due to its perceived simplicity. But most marketers intuitively understand that using last-click to measure and optimize campaigns really doesn’t make much sense in today’s complex marketing ecosystem.
Change can be difficult and scary, but change can be good — and, some change is essential in order to maximize performance of your marketing campaigns. Using an appropriate attribution model provides a critical element.
For example, let’s say I can see all the touch-points and interactions that a particular customer had with my brand prior to completing a purchase. The customer may have:
– discovered the brand on Facebook or Twitter
– engaged with and shared organic content about the brand or product with their friends
– visited a search engine to do some research on the brand or product
– clicked on a search or Product Listing Ad (PLA)
– arrived at the brand’s website
– viewed a variety of products without making a purchase
– gone back to Facebook, where they were presented with a dynamic Facebook Exchange (FBX) ad
– clicked on the FBX ad
– completed a purchase.
Whew! Should I give all the credit for the sale to the FBX ad that received that last click? What about the value of the preceding touch-points? The first interaction on Facebook or Twitter that started that journey should receive some credit, right? What about the search engine activity? It seems reasonable to apply some credit there also.
The fact is that “Last Click” or “Last Ad” attribution disregards the complexity of the customer journey, and using it to measure performance, allocate budgets, and optimize campaigns can and frequently does lead to poorer overall performance.
What we did
This is why Kenshoo decided to look more deeply at single-point versus multi-touch attribution by analyzing millions of converting click paths across a wide breadth of clients managing ads across multiple digital channels during March, April, and May of 2013. The brands in this study spanned a wide range of industries including retail, home improvement, and financial services.
Using Cost Per Acquisition (CPA) as the key performance indicator (KPI) to measure the efficiency of the media channel, we compared five alternative attribution models with Last Ad. These included First Only, Prefer First, Divide Equally, U-Shaped, and Prefer Last.
To understand how individual channel performance would be valued via Last Ad versus other standard attribution models, the CPA was first run through a Last Ad model, and then those same customer paths were analyzed under various MTA models. For example, if the Last Ad CPA for a campaign was $10, and the multi-touch attribution model being compared reported the CPA as $9, then the channel is undervalued by 10% versus Last Ad. In other words, that channel was getting 10% less credit than it should have received for its role in driving conversions.
What we found
Last Ad measurement undervalued Facebook advertising 12-30% relative to each of the five alternate attribution models.
The data in this study clearly show that, under any other attribution model, Facebook generates significantly more value than what is being reported by Last Ad measurement.
For many marketers who already accept that crediting full value for a conversion to the last touch-point in the customer journey is flawed, this research should be a strong motivating factor to explore new, more accurate models for measuring and optimizing campaign performance.
No single off-the-shelf attribution model works for every advertiser in every scenario. Each path to conversion is distinctive and original, built from various touch-points throughout the funnel. As such, a proper attribution model must be adaptive, account for these activities, and assign value accordingly.
The five standard models we reviewed are considered passive in that they retroactively apply a certain predefined, rules-based distribution of credit to all conversion paths. As a result, even though they are considered superior models to Last Ad, they should all be considered somewhat limited when trying to build a complete measurement and performance picture.
This is where dynamic attribution comes into play. Digital marketing technology platforms are evolving so that attribution decisions can be made in real-time using sophisticated mathematical modeling, machine learning and advanced algorithms. But, this is a topic to delve into more deeply later.
Suffice to say that if you are still using “last click” or “last ad” attribution, you could be allocating your spend in a much more logical manner. Try modeling what campaign performance would look like under different models, and most importantly, how your optimization, bidding, and budget decisions might change as a result.
You can download the full report here.