As an Enterprise Account Executive, I often get asked about multi-touch attribution and why 6sense takes a different approach to reporting on the impact of marketing/sales campaigns and activities. So, I decided to compile some thoughts on how I’ve seen marketers consider multi-touch attribution, and why attribution platforms have consistently failed to survive and thrive.
To put it plainly, multi-touch attribution in a complex B2B buying cycle is notoriously difficult to properly set up, maintain, interpret, and validate. 6sense customers are successful without it because we’re solving for the underlying business challenge of designating investment priorities across accounts that are 5-10x more likely to result in qualified pipeline (which we can validate with our predictive model backtest).
Configuring a multi-touch attribution model is rooted in guesswork, and there’s no validation mechanism to ensure it’s accurate even after waiting 6-9 months to gather initial results — that’s if UTM parameters have been properly assigned to every single possible interaction and enough data has been collected. 6sense provides a variety of marketing effectiveness reports, such as our buying stage progression and segment analysis reports. These reports enable 6sense users to understand which campaigns are influencing funnel progression and generating qualified opportunities, given that’s what affects most organizations’ bottom line and is likely what your executives care most about.
What you miss with multi-touch attribution
Consider this scenario. You work on the marketing team at BenCo, an employee benefits provider, and your team is using a 6sense competitor with multi-touch attribution. Last quarter, the following activity happened with one of your target accounts — only some of which you’re aware of:
First, ABC Company’s employee benefits director hears about BenCo. from his daughter, who works for one of their customers. This isn’t accounted for in the multi-touch attribution report.
Next, the VP of HR at ABC Company searches for BenCo. online, clicks on a Google Ad, browses for a few minutes, then leaves your website. A week later, she sees a BenCo. ad in her LinkedIn feed but keeps scrolling, which is also not accounted for in the multi-touch attribution report.
Additional ABC Company employees from the HR and people ops teams in the UK, Germany, Colombia, and Brazil also receive LinkedIn ads. Assuming a 0.5% CTR on 1,000 impressions served, you “track” five clicks, but miss four of them because you can only identify 20-30% of traffic outside of the U.S. with your current vendor’s account identification capabilities. So that’s one click accounted for with multi-touch attribution.
Meanwhile, your CEO is featured in a Forbes article, but you have no way of knowing who saw this article as it’s also not accounted for in the multi-touch attribution report.
At the same time, more organic, anonymous traffic from ABC is browsing the BenCo. website in the U.S., but organic traffic is also not accounted for in the multi-touch attribution report.
A BDR at your company sees on-site traffic from ABC, but doesn’t know where to start prospecting since they have 1,500+ HR-related titles in the U.S., and she can’t discern traffic location to narrow down the possibilities. This is also not accounted for in the multi-touch attribution report.
A month later, the AE assigned to ABC Company gets an introduction to their new chief people officer from another current BenCo. customer, who happens to be a friend of the CPO, and a validated opportunity is generated.
What’s the real goal here?
While this is a fairly oversimplified example of a path to generating a qualified opportunity, it illustrates the complexity of the modern B2B buying journey. And as a result of this complexity, and the shortcomings of multi-touch attribution reporting, only a few of the interactions in our scenario above are accounted for in an attribution report (and again, that’s only if all UTM parameters were perfectly configured and captured).
There’s no proof that assigning an arbitrary weight to click interactions with some of your marketing campaigns will drive more qualified opportunities. At best, it will require a heavy lift on your part to gain fractured, incomplete insight into which accounts have the highest likelihood of clicking on an ad. (It’s also worth noting here that the average CTR across display ads is 0.5-2%, while Google Ads averages 2% and LinkedIn averages 0.45-0.6%).
If you’re considering the relative importance of multi-touch attribution to your ABX program, I’d encourage you to keep the end goal in mind: generating qualified opportunities through full visibility into your prospects’ buying cycle. And if you found this post to be helpful, you might also be interested in this article from Heinz Marketing for more on 3rd-party validation and the challenges with B2B attribution.