How do you turn your marketing team into an organization that’s dedicated to data?
That’s exactly the challenge Brandon Proctor had when he came on board as president of AutoAnything in early 2017. At the time, the automotive retailer was already leveraging Adobe Analytics. But Proctor quickly realized the eCommerce brand wasn’t using the software to its fullest extent – and missing out on big opportunities along the way.
“I’m a believer that in today’s world, as far as marketing, as far as merchandising, as far as eCommerce is concerned, it’s a requirement that everybody is technical to some degree, and everybody is kind of an analyst,” Proctor said. “So with that edict in mind…whether it was looking at the customer journey, looking at how different marketing channels actually interact, and making sure they [AutoAnything] were tracking things at the lowest levels – there wasn’t a lot of that.”
Building the analytics framework
What AutoAnything lacked was proper attribution. The brand struggled with identifying how to measure and assign value to different channels on a granular level. They also lacked the ability to collect and organize their data in a way that allowed them to completely and accurately understand their customers.
“Being able to pull all that [data] together to create a very accurate picture of who your customers are is really the start,” Nate Smith, group product marketing manager at Adobe Analytics Cloud, said. “There’s just so much interconnected data, and we as humans just simply can’t process all of that data. So it’s imperative that providers [like Adobe] have machine learning, and artificial intelligence, to find those proverbial needles in the haystack.”
For Proctor, this meant new taxonomies (and a whole new set of tracking codes) needed to be put in place to make sure every effort within a marketing campaign could be tracked and measured for success. AutoAnything also needed a way to take all of that data and bring it under an umbrella so their marketing team could track it on a customer level.
By restructuring their Adobe Analytics process, the AutoAnything team was able to assign unique, individual IDs that aggregated all customer data points into one, complete, digital footprint.
“Basically, we’re combining a bunch of values into an ID that we would assign to a user. That ID would include any information that we had on the user, but it also might include an email, or an IP address,” Proctor said. “And that gives us a unique view of the customer no matter how they shop, or if they switch devices.”
Seeing the full picture
This new process allows AutoAnything to see the full picture when it comes to the customer journey. For example, if a customer opened an email, AutoAnything can use Adobe to see where they accessed the email (on mobile, or desktop) and compare that data to other ways they may have interacted with their brand – whether it be by visiting their website, clicking through specific product pages, or even interacting offline through a telephone call or direct mail.
These data points together paint a much more realistic picture of where certain customers may be in the purchasing process. The AutoAnything team can then allocate their budgets to ensure they’re connecting with customers through the right channels at the right time.
“It’s great insight because there’s certain people who shop by mobile, or may do research by mobile and then purchase on desktop – and then there’s people who do the exact opposite,” Proctor said. “We’re able to see those customers, no matter what device they’re shopping with us on — which means it allows us to allocate funds according to success we see across all channels.
This also helps when it comes to prioritizing high-value customers that have shown consistent engagement, and shifting away from marketing efforts that may not have as much of an impact. A more targeted approach allows for more thoughtful spending, with dollars spent on those who are more likely to convert.
The difference in attribution was a game-changer, especially when it came to understanding their customers on mobile. Before their restructure, AutoAnyhing attributed mobile interactions (or ‘touches’ as Proctor described them) were only a contributing factor in 25% of their total sales. After implementing more precise analytics, however, the brand quickly realized that number was closer to 40%. This allowed the marketing team to quickly shift focus on their mobile efforts.
“Just having that insight changes how we go to market,” Proctor said. “Everything kind of changes now because we can see the actual contribution of all these channels, when previously, it may have looked like they weren’t contributing.”
