A New Cross-Channel Frontier: Attribution
Columnist Roger Juntilla discusses the challenges of achieving attribution and what marketers can do to remedy the gaps in our understanding of it.
As an industry, we have the desire to achieve total attribution — a perfectly detailed understanding of how all media in our cross-channel mix are performing. But despite our aspiration and progress, the path to full visibility is generally considered a few years out. And in many ways, we are still trying to figure out how to get there.
Despite some remaining challenges, I see a few tactics that, once we embrace them, certainly get us closer to our goal, because they get us nearer to understanding the consumer’s intentions and most meaningful actions.
Interestingly, when it comes to tackling and achieving attribution, most marketers perceive themselves to be behind. According to an eMarketer report earlier this year, “Cross-Platform Attribution 2015: Device Identification, Big Data Pose Continued Challenges,” while we see that 21% of marketers are “looking at all influencing touch points,” it’s significant that 38% have no attribution model in place whatsoever.
And there are other degrees of adoption in between — where marketers and presumably their agencies deal with slices of the complete picture, but not the whole thing. Planning silos are a big reason for this.
Practically speaking, if you look inside the agency at how media still is planned, bought, and measured, there are compartments. This creates a silo effect, where teams are charged with planning, spending, and performing only against their own platform. They optimize what they own and handle, each channel or platform specialist operating on a parallel path. This isn’t a setup for cross-platform planning and buying, let alone seamless attribution.
So inside the agency or on the marketer’s desk, there is still a lot of cross-referencing and manual work to create the full picture. That cobbled picture lets us look at how we are marketing to different phases of the funnel, with which media types, forcing us to still draw quite a few inferences on performance.
Perhaps it’s because when we dig into performance, our tendency is to analyze from the bottom up. It’s those digital channels and platforms that are most easily held accountable for performance. So we review and credit them, while glossing over the rest of the mix.
The challenges that marketers express about their own attribution readiness seem to reflect this somewhat unconnected state. When it comes down to it, there are gaps in our understanding.
Leveraging Intention Data
So how do we remedy the gap? Graduating from light content preference or even more robust behavioral data and looking at consumer intention data is the best start. It seems that a more granular understanding of the consumer is the first new frontier on this quest for better attribution.
When we work with data models that leverage expressed commercial intent, we find ourselves at the heart of the purchase funnel. There, we know more about what consumers are planning to do and actions they are planning to take.
Consumer intention data is the next level that strengthens the targeting and therefore the performance. Yes, you or your agency may still want to use robust behavioral targeting — but this is an incredibly powerful alternative that strengthens your targeting and likely the outcome of well-executed media exposure.
For example, we know through classic behavioral targeting that someone who goes to an auto site may or may not be in market for a new car.
However, if through intent data, we uncover actions such as the person comparing different car models online, sharing or socializing articles with friends about vehicles they are considering buying, or visiting car dealerships for test drives — voila! It’s a certainty that this person is in the market for a new ride and is a perfect candidate for an auto manufacturer ad.
Layering On Micro-Actions
Micro-actions are all those smaller, more meaningful actions that convey a consumer’s specific activity online. More attention to these micro-actions is a key layer to add to our closer look at intention. These represent another frontier that brings us more authentic info, when we personalize and localize our ad marketing to capture true interest and drive across platforms.
Looking beyond the typical actions into micro-actions, as we study and optimize across platforms, let’s talk about how we can break down different actions in order to understand and optimize them.
Putting an item on a wish list; signing up for a price alert, so notification happens when a price drop occurs; adding an item to a shopping list; downloading a coupon; searching for something; comparing products — any combination of these actions is stronger and more declarative than a consumer simply going to a website or browsing particular content. We need a wider scope on the actions we track and use to understand a consumer’s true path.
That brings us to the ultimate frontier: tying it all together, with our systems, in an automated fashion. Once we can serve the ad and then track and optimize one known user’s micro-actions across platforms and touch points, we are there.
Our ability to systemically deliver attribution across the media plan and at the individual level is very much the future, a few years out perhaps — but it’s where we need to go. In the meantime, embracing the new frontiers will keep us moving forward and achieving more useful understanding in the process.