By adaptive - August 28th, 2017
From first click to last click and everything in between, attribution has marketing departments obsessing over the customer journey, pondering precisely which part of it is most important. In the first part of this series, Matt Pigot takes a look at how NASCAR drives better outcomes through internal communication.
How is it possible to have the level of insight required to know at which point a browser becomes a buyer, or at which point a buyer made the mysterious transition to becoming a loyal customer? Was it a specific piece of content that made them pick up the phone; a new deal or offer; a PPC ad, or a slick piece of creative design?
Understanding what’s working and what isn’t, especially when dealing with thousands—if not millions—of customers, requires the implementation of the right data stack, fully integrated, and monitored with the obsessive commitment of Alan Turing trying to crack the Enigma code.
Where marketing and data science converge if that sounds extreme, it isn’t. With the vast explosion of channels, the weight of the attribution challenge is a growing pressure for brands. Which means more cutting edge algorithms devised by coders to deduce which platforms, devices and channels perform best, and which ones need throwing in the garbage can.
The trouble is, most companies are still relying on rudimentary forms of attribution such as first click, last click and time delay, none of which paint an accurate picture of what customers are really doing.
The result is skewed data, and that’s bad news, because once it’s gone through the brand-consumer exchange cycle, it leads to irrelevant messaging, which in turn leads to consumer disengagement.
So when it comes to getting attribution right, ensuring that the signal being sent is clear is the number one consideration. For the most ambitious companies reaching out to attain the elusive single customer view, they must go beyond basic and either find or create more sophisticated attribution models. And that means having both the right tech stack in place and a good data scientist to take full ownership.
Data: the era of monetization
With data becoming increasingly commoditized, and brands seeing the potential for realizing their fiscal goals by using it to improve communications with customers, it’s little wonder that the spotlight has panned—many would say diversified—from creative to hard stats. With creative increasingly playing second fiddle to the data, even in its simplest forms such as A, B testing, this flipped paradigm and gradual reshuffling of business priorities has many CMOs’ heads spinning.
But the myth that it’s an either/or predicament is one that needs dispelling; it is, in fact, a ripe opportunity to make unprecedented advancements and marginal gains through collaboration.
Driving outcomes through better internal communication
Jill Gregory, senior vice president and chief marketing officer for NASCAR, says, “We don’t make any decisions without a lot of data insights and analytics. We had several pockets of expertise and research that were stuck within different departments throughout the organization. So we brought them all together into one analytics and insights group. We had a lot of data but we weren’t providing a lot of context around it. If you don’t know what it means and why it matters to your fans, it’s not really helpful. We really put that group together to analyze that data and use it.”
Gregory highlights the importance of desiloed departmental organization and combined thinking to get to the core of the data, understand the story it reveals and, with the insights of attribution, take action.
“What is the data telling us we need to do?” she adds. “If it’s telling us we need to evolve, be more aggressive, try new things, that’s a bit easier to sell into the culture than, hey, ‘this feels right, or I feel it in my gut’.”
Gregory’s comments suggest that successful attribution entails making the optimized management of human resources pivotal.
Fostering better communications between increasingly interconnected—but still separate—working entities on the marketing and data sides is central to that success.
Back to the future of attribution
Tracing back through a single customer journey to see what’s worked and what hasn’t is where the reciprocity between marketing attribution and personalization comes into play. Being able to zero in on a specific detail of any given journey to establish exactly what engaged the customer, what made a browser become a buyer, and what triggered a conversion are all critical when it comes to securing buying at board level, and sign off on budget for new marketing initiatives.