Customer Analytics Is Picking Up Steam
In his recent blog post, “My Customer Analytics Epiphany,” my colleague Ben Gaines described what customer analytics is and how it’s different from digital analytics. Adam Jenkins, another Adobe blogger, also wrote a great piece on the importance of customer analytics to digital marketing.
Customer analytics is a hot topic around here because it’s a hot topic for you.
As marketers mature their digital activities, they’re finding more sources of information about how customers interact with their brands. There’s data from websites, mobile apps, call centers, social media, and more. By combining all this and looking at people as full customers rather than fragmented interactions, marketers can have much more meaningful conversations with them.
That’s what customer analytics is all about. The problem is there’s a huge gap between the potential of customer analytics and making it actionable from a skills standpoint. Traditional data science is usually looked to for solutions. But the field as we know it is failing to bridge the gap in some important ways.
For one thing, traditional data science tools are complex enough that you need an impossibly smart, flexible, and business-savvy individual to run them and generate the insights you need about your customer. In my opinion, Rob Bearden, the CEO of Hortonworks, nailed it when he said, “[Finding] truly qualified data scientists … may be the biggest imbalance of supply and demand I’ve ever seen…. The talent pool is, at best, probably 20 percent of the demand.”
Enterprises seeking to hire their way out of this problem have a pretty tough row to hoe.
Second, if you’re lucky enough to have found the data science professional you need, getting customer insights to your marketers—the folks tasked with creating a great conversation with your customers—is nearly impossible. Making that data live on your digital property is harder yet.
I’m sure by now that you’ve heard about the Gartner report stating that the typical CMO will spend more on technology than the CIO by 2017.
We think that’s true. It’s similar to the trend we saw 10 years ago when marketers were starved for information about how customers were navigating their websites. Adobe solved the problem by democratizing access to that information. This enabled a new depth of understanding about how customers interact through digital properties and opened up a new world for marketers who wanted to use that understanding to make life better for their customers.
Now, our customers are looking for solutions that allow them to extend that understanding beyond the IT organization, disseminate insight throughout the enterprise, make that data live on their digital properties (or in any customer interaction), and do it at huge organizational scale.
That’s what customer analytics means to us.
We’re pretty good at allowing enterprises to self-serve customer information and making that data live on our customers’ properties. However, we’re still innovating aggressively in this area, adding predictive analytics capabilities, making it easier than ever to share insights throughout the enterprise, and more closely tying customer analytics to the rest of the Adobe Marketing Cloud. Many of our most sophisticated customers are already using these capacities to delight their customers.
Our goal is to enable digital analysts to produce the insights that currently require a data scientist to produce. We also want to dramatically improve on the tools data scientists themselves have to choose from. By doing so, we hope to give CMOs exacting control over how they interact with their customers and provide fantastic experiences with their brands.