All affiliate systems attribute, but not all attribution systems affiliate. Wait, what?
af·fil·i·ate mar·ket·ing: noun, a marketing arrangement by which an online retailer pays commission to an external website for traffic or sales generated from its referrals. (Oxford, 2019)
The structure of affiliate marketing presumes a set of constructs which dictate how traffic suppliers—frequently publishers—are compensated. By and large, this occurs on a last-click model. However, there are complex rules that allow marketers to pay different bounties based on category, product, customer engagements, even attribution timelines.
The rules governing which traffic provider receives what credit is known as Attribution.
This service has spawned a generation of martech companies in mobile known as mobile measurement partners (MMPs). MMPs synthesize enormous amounts of media and traffic data, then report on channel performance, LTV, fraud, even organic data.
Picture this, I’m on the subway—L train to be specific—playing Candy Crush on my phone. To play the next level, I watch an ad from Calm the meditation app thanks to its quality context targeting. I click the ad just as the train hits the East River and signal dies. The next day, I’m retargeted with another Calm ad on Instagram. This time, I click, install, and convert.
If Calm’s methodology is last click, Instagram receives credit for conversion; if first click, Candy Crush wins; if split, they each get a slice of the pie.
Attribution is focused on measurement, primarily the measurement of click- and impression-based media data which results in conversion events after an ad is shown. It is not, however, the abacus which determines financial obligations owed to traffic sources for completed sales. That’s decided by its cousin, Affiliate.
MMPs are massive and sophisticated tech companies who facilitate this measurement, attribution, crediting, reporting by traffic sources and more.
Appsflyer, Branch, Kochava, and Singular are among the most popular.
The ability to move beyond crediting to finalizing payment is called affiliation. This is reserved for companies who sieve the complex rules marketers enforce on traffic suppliers. Compensation for traffic which results in sales takes the form of commissions (most frequently a percentage of revenue generated). Importantly, the financial relationships underpinning these transactional partnerships necessitate a high fidelity of data transfer.
Target pays traffic sources varying commissions for shoppers who purchase in their app: 10% for baby products and 3% for automotive. The retailer offers a flat $100 for every credit card application. Groceries are excluded (at 0%) and commissions are payable only once the return window elapses on all products shipped. Lastly, all above commissions are halved if the purchaser is an existing Target customer.
If we follow the same crediting path with affiliation as we did with attribution, where multiple parties share responsibility for driving this conversion, we quickly lose direction in a marketing labyrinth of overlapping payments and jumbled data.
Say a new customer is driven to Target from an influencer’s blog, adds a couple tires and baby stroller to the cart then bounces. Prompted by a Facebook ad a day later, that person applies for a credit card and buys everything held in the cart including a newly-added bushel of produce. Then, returns the stroller a month later (well within the 90-day warranty).
Does Facebook receive all credit for conversion even though it drove grocery sales and a return? How about the poor influencer who unleashed this avalanche? How is the cost-per-click ad from Facebook, which is charged at the time of click, reconciled against the downstream purchase conversion the influencer drove?
And just like that, I’m halfway to an ACT-like mental pretzel trying to figure out when the first train left the station.
If you credit Facebook because they won last-click, you may be right. But that would be done at the expense of marginalizing quality traffic sources and rewarding the wrong behavior, not to mention pigeon-holing your growth mix and misrepresenting data. In the above example, most prudent marketers would prefer compensating the influencer who drove a monster purchase from a new user.
Herein lies a fundamental difference between the systems: Affiliation fulfills payment obligations with traffic sources for qualified and completed sales. It is not a holistic measurement system that provides insights into when and where conversions happened through attribution. These two systems are deeply intertwined in the app ecosystem, however. It is crucial that app affiliation data be exposed in attribution systems, such as MMPs, to properly measure channel performance and how it stack ranks against others; not to mention, it provides the vital function of deduping post-click transactions from media campaigns. Most importantly, it empowers app marketers to make informed decisions about the revenue and data they generate and the partners with whom they work. This is why Button partners with all major MMPs.
For more on how Button works in tandem with MMPs, stay tuned for my next blog post. If you're interested in learning more, reach out to us today.
.png)
.png)
