Affiliate Attribution: Putting the Pieces Together

Originally Posted on the Adometry M2R Blog
Recently I was reminded of an article from a little while back, titled, “2013: The Year of Affiliate Attribution?” It’s an interesting take and worthwhile read for those interested in affiliate marketing and the associated measurement challenges. Given that some time has passed, I thought it would be interesting to take a look at progress to date towards realizing a more holistic and accurate view of affiliate performance as part of a comprehensive cross-channel strategy.
Most affiliate managers have a similar goal to manage affiliate holistically, meaning investing in those that predominantly drive net-new customers independent of other paid marketing investments. Ultimately, this model allows them to optimize CPA by managing commissions, coupon discounts, and brand appropriateness based on true “incremental value” provided to business. Unfortunately, due to a lack of transparency and inadequate measurement, many marketers find themselves short of this goal. The result is the ongoing nagging question, “Is my affiliate strategy working and am I overpaying for what I’m getting?”

Why ‘Affiliate Attribution’ Is Hard

Affiliate marketers’ challenges range from competing against affiliates in PPC ad programs to concerns about questionable business practices employed by some “opportunistic” affiliates offering marginal value, but still receiving credit for sales that likely would have happened regardless. Which brings us to the central question:
How do marketers determine how much credit an affiliate should receive?

As you may know, opinions about how much conversion credit affiliates deserve for any given transaction vary widely. While there are a number of factors that influence affiliate performance (e.g. where they appear in the sales funnel, industry/sector, time-to-purchase length, etc.) for most brands the attribution model that is utilized will have a significant impact on which affiliates are over- and under-valued.
For example, in a last-click world affiliates that enter the purchase path towards the bottom of the funnel often hold their own; yet, when brands begin measuring on a full-funnel basis incorporating impression data, many struggle to prove their incremental value as the consumer has many exposures to marketing long before they reach the affiliate site. Conversely, affiliates that act predominantly as top- or mid-funnel (content, loyalty, etc.) are usually undervalued using last-click but can garner more credit using a full-funnel, data-driven attribution methodology. I should also mention these are broad generalizations only meant as examples, and it’s not necessarily a zero-sum game.
Another challenge is that fractional, data-driven attribution is difficult to implement for some types of promotions. One instance of this is cash back, loyalty and reward sites that must know an exact commission amount they will receive for each transaction so that they can pass on discounts to members. Given the complexity of more sophisticated attribution models, this data isn’t readily available.
Lastly, there several organizational challenges that inhibit the use of data-driven attribution among affiliate marketers. Some industry experts have indicated that many publishers, as much as 70-80%, strip impression tracking code from affiliate URLs. Another measurement challenge we see frequently is brands managing affiliates at the channel level leaving little sub-channel categorization which is where significant optimization opportunities exist.
Affiliate Attribution and the Performance Marketing Goldmine
Of course, part of our work at Adometry is helping customers address these challenges (and more) to ensure they are measuring affiliate contributions accurately and able to take appropriate action based on fully-attributed results.
Some key advantages of using data-driven attribution to measure affiliate sales include:
  • The ability to create a unified framework to compare performance (clicks and Impressions) in which affiliates compete for budgets on equal footing,
  • Increased visibility into which publishers are truly driving net-new customers through specifying which are an integral part of a multi-touch path and which are expendable,
  • The knowledge required to implement a Publisher category taxonomy to allow more insights into how different types of publishers perform by funnel stage and areas to improve efficiency,
  • Insight into the true incremental value publishers are providing and the offering commission rates to reflect this actual value,
  • A better understanding of affiliate’s role in the overall mix, further informing marketers use of complementary tactics to maximize affiliate contributions in concert with other channels,
  • The ability to use actual performance data to counter myths and frustrations with affiliates (cookie stuffing, stealing conversions, etc.)
Taken separately, each of these represents a significant opportunity to both be more effective in how you identify and utilize affiliate attribution to drive new opportunities. Together, they represent a fundamental improvement in how you manage your overall marketing spending, strategic planning and optimization efforts.
Top-performing affiliates, particularly those at the top and middle of the funnel, also stand to benefit from more transparent, accurate and fair system for crediting conversions. In fact, several large-scale, forward-thinking affiliates are already investing in data-driven attribution to arm themselves with the data required to effectively compete and win business in the market as brands become more sophisticated and judicious with their affiliates budgets.
It’s an exciting time for performance marketing. Change is always hard, but in this case it’s absolutely change for the better.  And frankly, its time.  What are your thoughts and experiences with measuring affiliate performance and attribution?

Posted by Casey Carey, Google Analytics team