More and more, marketers are being tasked with not only being able to answer questions about top and middle-of-the-funnel demand performance (e.g. leads and opportunities), but greater business questions. Where do we need to invest to hit revenue goals this quarter? How do we increase deal velocity? What marketing programs can we enact to help the sales team increase win rates?
To answer these bottom-of-the-funnel questions, B2B marketers, at organizations like UserTesting, turn to their attribution data.
One of the many benefits of using a sophisticated attribution solution is the comprehensiveness and flexibility of data. If marketing teams can capture every prospect interaction and attach important details to that interaction—source, medium, campaign, content, and even things like device and location—the ways the data can be analyzed are boundless. And when those interactions are attached to down-funnel business metrics, the attribution data enables marketers to answer important business questions.
Andrew Slutzky, Manager of Marketing Operations at UserTesting, says that he likes how Bizible “tracks each session online or offline” with great detail, like source, medium, campaign, content, device, location, etc. “This granularity,” he says, “allows for numerous cross tabulation reports.”
At UserTesting, a user experience research platform, Andrew’s marketing team uses Bizible multi-touch revenue attribution to answer critical business questions, including:
- What channels are generating the most revenue?
- How long does it take for an anonymous user to become a closed-won opportunity?
- What are our conversion rates at each funnel stage?
Not only are answers to these questions critical to improving the marketing team’s metrics, they’re critical to the business as a whole. The CEO cares about these. The CFO, the CRO, and the VP of Sales care about these.
The marketing team at UserTesting uses multiple attribution models to answer various questions. “FT, LC, U, W, Full-Path and Custom all provide invaluable insights,” says Andrew. Based on which question the marketing team is trying to answer, a different attribution model could provide the right information. (Here's a description of every attribution model.)
For example, if a marketing team wants to know what channels are driving leads, a Full-Path model, which gives credit to touchpoints from the first touch to closed-won, doesn’t make sense. Instead, a U-Shaped model would be more appropriate—giving 40% credit to the first touch, 40% credit to the lead creation touch, and splitting 20% credit to all other touchpoints inbetween.
But when answering questions about which marketing efforts are generating the most revenue, a Full-Path or Custom model would be more appropriate, giving credit to touchpoints across the entire funnel.
The comprehensiveness of data and the flexibility to apply multiple attribution models, as appropriate, hinges on accurately tracking and collecting information on the entire buyer’s journey. And this enables marketers to accurately—and with granularity—answer the variety of business questions that they need to be able to answer.
Given the opportunity to provide one recommendation, Andrew says that it’s critical to “understand what business problems you are trying to solve before deciding on what attribution models you want to leverage.” After all, only after you really understand your business problem, can you go apply to the data to answer it.
Marketers are increasingly under pressure to be able to answer not just marketing problems, but business problems. CMOs are increasingly accountable to revenue, and the ability to accurately and confidently provide answers to business problems will go a long way to helping them get a seat at the revenue table.