On May 9 Wharton Customer Analytics Initiative (WCAI) celebrated its 10-year anniversary with a reception prior to its annual conference, Successful Applications of Customer Analytics. During the past decade, the discipline and practice has taken hold across industries, and Wharton marketing professors Eric Bradlow and Pete Fader, founding directors of WCAI, have been on the front lines working with research partners, students, and alumni.
Knowledge@Wharton sat down with Prof. Bradlow and Prof. Raghu Iyengar, both current co-directors of WCAI, and Prof. Fader to discuss the changes in customer analytics over the past 10 years. You can find the full story and podcast at Knowledge@Wharton, or read highlights here:
Analytics are everywhere.
Iyengar: “What you see now is that there are many companies who have their own analysts. They are thinking about what are the problems that they want to solve at the company. At the same time, there is a limited bandwidth – the in-house analysts can’t work on everything.”
Bradlow: “The set of companies that have very little analytics capabilities is shrinking — and that’s a good thing. It’s shrinking fast.”
More “translators” are needed.
Bradlow: “What every company wants is someone who knows business, has the softer skills, but also knows analytics. If you want to think of it, we always talk about this Venn diagram. On the one side you have people with business knowledge. Well, there are a lot of graduating MBAs. There are a lot of people who know analytics. But people that sit at that intersection — that intersection really has not grown as fast as I thought it would.”
Iyengar: “Translators, people who are well versed in the analytics part of it, that’s great. But they also know how to manage teams. They know how to manage people who are also doing the analytics. One of the things that we’ve done with WCAI is run a very successful executive education program where we talk about three things: tools, talent, and metrics. And this idea of talent, how do you hire the right set of people? There is a difference between, let’s say, a data analyst, a data engineer, and a data scientist, and a person who can in some sense talk to all of them.”
Barriers are breaking down.
Fader: “It used to be that we’d be appealing just to those geeks and nerds within the marketing organization. But we’re seeing that analytics is a great way to break down some of the barriers. And we’re seeing just genuine conversations happening between the marketing folks and the CFO office and research and development, talent management, and so on…. We’re also seeing a greater sophistication in the skills that they have. It used to be, ‘Can we do this for them?’ And now it’s, ‘Can we help them do it better on their own?’”
Analytics still can’t solve problems without human understanding.
Iyengar: “You want to always start with a business problem. I think it’s becoming increasingly easy for many of us, when you have a conversation with companies, to start with a business problem, but that’s something we’ve seen all along, which is many times they get so involved in the problem itself or the solution that they don’t understand the problem.”
Bradlow: “There are lots of different what I would call ‘rote’ tasks where computers, artificial intelligence machines and [other applications] can actually replace [humans]. In some sense at the end of the day, we need things that are scalable and automated. That’s true. But there is also still going to be an art to it. …
“But wouldn’t it be great if in some sense all the decisions that can be made in a large-scale automated way are made in that way? That leaves us humans, who have limited capacity, actually spending time on those more subtle and difficult decisions.”
The next wave of analytics is not just customer behavior but neuroscience.
Fader: “Most of our research is about watching what people have done and projecting what they’re going to do next.
“But the really cool stuff coming up is the stuff that isn’t necessarily behavior: Neuroscience. And when we were first setting up it was kind of Star Wars far out there, ‘this will never happen.’ But, it is happening and it’s happening fast…. Once we can really get inside people’s heads and once we can really integrate what people are seeing and thinking and planning, it brings a whole new dimension to the kinds of data that we have and therefore the kinds of analytics that we’d want to use and the kinds of decisions that firms would make.”
Find the full story and podcast at Knowledge@Wharton.
Posted: May 14, 2018