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Lori Sherer: Customer Insights and Analytics in Agile Development

Bain Partner Lori Sherer discusses the role of insights and analytics in digital customer experience design.


Lori Sherer: Customer Insights and Analytics in Agile Development

Researchers are combining leading-edge data science with traditional marketing techniques to create digital and mobile experiences that serve the functional as well as emotional needs of customers. Lori Sherer, a partner with Bain’s Advanced Analytics practice, discusses the role of insights and analytics in digital customer experience design.

Read the transcript below.

LORI SHERER: Today, we're seeing a lot of companies that are trying to undergo what we call a digital transformation. And these are companies that are trying to design world-class digital and mobile experiences for their customers that get at not only the functional requirements of customers, but also look at the deeper emotional and aspirational needs of these customers. It's called human-centered design. And companies, as part of their digital transformation, are trying to design these experiences in a process called Agile.

And Agile is putting a cross-functional team together that stays together from the very beginning of the project through many iterations and testing against consumers on prototypes of these products until they optimize them to meet those needs. So there's an expanding role now for the consumer-insights and the data-and-analytics team that will support these Agile development projects.

And it's an exciting time for people who have been in a traditional market research function, because the very heart of this is the consumer, and understanding that consumer from many, many dimensions. So we can use traditional techniques, such as focus groups. And we can use online focus groups, which are easier and quicker, and that are location-independent. But there're many ways, including ethnographic research, that we can also get out in the wild with consumers, follow them around, intercept them, ask them what they're doing, observe their daily routine, see them when they're shopping. And we can tape those experiences.

We can also arm consumers with a mobile device, where they can record throughout the day their observations, their feelings and their experiences. So there's an expanding set of capabilities that the market research team can bring to these Agile teams to really understand and get under the hood of these consumers.

In addition to that, we're seeing the consumer insights team use Big Data analytics to observe the customer. They can pull the call center data and use text and video mining to really understand these interactions between the customer and the company in the old-fashioned channels. And this provides tremendous insight into what customers are really looking for when they connect with the company.

In the second area, the data and analytics team is responsible for building the analytic engines that will power the experience behind the scenes. And these analytic engines can range from something very simple like a data look-up, so that when you log on to the site or open up the app, it can greet you by first name. And it can display the weather in your area. And it can provide other levels of personalization by, say, populating a form for you automatically.

The second level of complexity in that arena is optimization engines. And this would be things like Amazon.com provides when you buy a product; they look at other consumers who bought that same product and they recommend to you other products that you might want to buy. This is really becoming a mainstay in most digital and mobile applications—the ability to actually personalize the experience further by recommending other things and providing advice.

And the third area of the data and analytics team is something we call test and learn. So while we have new ways of understanding and articulating what those customer-deep desires are, and we have ways to meet them using analytic engines and algorithms, now, we also have ways using statistics to vary the presentation of these experiences to consumers in a statistically-designed setup, so that we can really understand which elements of that experience are driving the satisfaction. Is it the content, is it the creative, is it the offer, is it the way it's displayed, is it the way the customer clicks through the experience, that is driving the happiness factor?

So it's really a very exciting time for people who come from traditional market research backgrounds, and/or who are coming out of a data-science background who can now join these Agile cross-functional teams to build world-class customer experiences of the future.

Read the Bain Brief: What Big Data Means for Customer Loyalty

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