▶” title=”The TRUE Success Metrics for Ecommerce Growth” width=”560″> After iOS 14, businesses stopped trusting the numbers they were seeing in Facebook. Understandably, brands started looking for a third-party tool to give them the clarity they once relied on Facebook to provide. Enter: Multi-touch attribution tools. What started out as a helpful way to understand customer metrics has turned into over-reliance, and dare we say, an over-hyped understanding of the data presented. Which raises the question: Is there such a thing as too much data? Despite CTC’s data-centric reputation, our answer is a resounding “Absolutely.” As we continue to work with third-party attribution tools like Rockerbox and Triple Whale, we’re seeing some discrepancies and pitfalls to be wary of. Yes, the reporting and visibility on the data has changed. But that’s no reason to put all your chips down on tools that promise to give that visibility back. That’s because there’s a difference between measurement and decision-making. The Basics: What Do Multi-Touch Attribution Tools Do? How Do They Work? The main purpose of attribution tools is to assign credit for a sale to a specific channel within the marketing or media mix (i.e. Facebook, Google, TikTok, etc.). These tools serve two main purposes for DTC businesses: Reporting & analytics Attribution Reporting & analytics within these platforms are meant to show you the full customer journey, rather than just consumer behavior as it pertains to a single channel. Attribution requires some sort of modeled framework (each tool has different ones) to understand how much each channel contributes to parts of that customer journey. Practically, media buyers analyze the data reported in these platforms to provide strategies for enhanced customer acquisition. What is multi-touch attribution? Multi-touch attribution applies different weights to each channel in the marketing mix. Ultimately, all channels add up to 100% of the businesses actual revenue outcome. Typically, performance will look a lot worse than what Facebook is showing. Anecdotally, we’ve seen platforms like TikTok and Google (branded search campaigns in particular) seemingly perform higher than expected. So what’s going on here? Here’s an illustration: You see an ad on Instagram, click on it, browse a little bit, but you don’t convert. Later on that evening, you Google that brand, branded search comes up, and now you buy . Both Facebook and Google will take credit for that purchase. This double-dipping is exactly what multi-touch attribution tools try to solve — and retailers try to use these insights to better understand where to put their marketing dollars. In the above example, the multi-touch attribution tool might report that Google’s getting 75% of the credit for that purchase and Facebook’s getting 25%. So . you just cut the efficiency of Facebook by three quarters. Is that really accurate? Problem 1: Pulling Back Spend Based on Attribution Data When it comes to multi-touch attribution, you don’t get any of those subsequent touches — and you don’t get the conversion — without the first touch. And the data backs that up: across the board, a decrease in Facebook spend correlates with a decrease in overall revenue. “Is this exact number in Facebook accurate?” is the wrong question. Because even if Google is “75% responsible” for a sale, that sale would never have happened without that initial 25% from Facebook. Beware of getting so caught up in the discrepancy between the two numbers that you pull back on Facebook. Problem 2: Attribution Data Isn’t Passed to Facebook There’s another major flaw with multi-touch attribution tools — none of them pass their information back to Facebook. And that means that Facebook can’t price your ad or optimize against that data. Inevitably, you’ll start to see your CPMs go up, since you’re telling Facebook to optimize for people that its own data shows to not be profitable. This perpetuates the problem, creatin...