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Four Primary Focus Areas for Data Analytics (VIDEO)


Video produced by Steve Nathans-Kelly

In the closing keynote at Data Summit 2019, Radiant Advisers' John O'Brien identified four focus areas for data analytics—understanding customer behavior, understanding product usage, increasing operational efficiency, and business model innovation.

When working with customers on their data strategy, one of the first things O’Brien says he often hears is: “Okay, we've got a lot of choices. Don’t worry about the tech. Actually, the people and the culture is going to be harder to solve than the tech. Skills, finding people, training. But, where are we going to focus?”

According to O’Brien, analytics falls into four categories. The first is understanding your customers. “So, if you want to understand your customers, do you have all their touchpoints? Are you pulling in everything about them? Are you tracking where you can? Are you capturing every engagement? Whether they log into your website, log into their accounts, call tech support, even do things on social media. Transactions, yeah, we've got that stuff. But, you know, one of the things we're always saying is that a transaction—a sale, or an upgrade, or something like that—is the end of a journey. You don't know the path that they took in their research, their interactions. Everything they did to get to that point of a transaction. Because that's all our operational systems will capture.”

Leading companies know that by understanding their customers better, they can build better products, O’Brien said.

The second-most-popular category O’Brien sees in customer engagements is increased operational efficiency. “The reason why this is good is because, usually, you have known processes. You've worked with the data, and you're introducing new technologies. So, from a scope perspective, you're taking something you already know really well. You've been working this.” But AI, machine learning, and other applications go from the basic analytics and leverage advanced analytics complexity that we couldn't do before. “So, that's a good place to start. You get some quick wins, or maybe some safe money back for reinvestment.”

And then, some companies are just very product-oriented, said O’Brien. “So everything for them is about thousands of SKUs, lots of products, product interactions, bundles: ‘How do we build our products, how do they interrelate, componentize?’ That's where all their analytics comes from: ‘How do people use our products? Can we instrument our products?’ And, I tend to go down that direction as well, from an instrumentation route, because my actual background, undergraduate work, and all of that, is in instrumentation and control systems, analog-to-digital signals. That's what I studied in college, and went and did early in my career, was all of that type of data capture: Where can you instrument and then do something meaningful with that data?”

Finally, there is a desire for business model innovation. “There are opportunities where people can come in and experiment and explore new business models. And new business models is where the digital or business disruption is coming in: What if we completely flip our business—the way we've been doing things for a long time—on its head and come up with something new that perhaps is data product-oriented?  Or, driven by data as a service through our customers and products that we have, can we create a new data product where we can augment the services we have?”

DBTA’s next Data Summit conference will be held May 19-20, 2020, in Boston, with pre-conference workshops on Monday, May 18.

According to O’Brien, one of his clients is in software sales and has a lot of information about all of its managed service providers. Radiant is helping the client analyze the financial data in order to turn around and help the MSPs be more efficient and come up with new models and recommendations and bundles. For this client, using data analytics to enable its customers or intermediate customers is a way to grow its business, he said.

Recently, said O’Brien, he visited a large global brewery in Europe to help with a big data integration challenge, but the company’s market department was also interested in doing new things with data to disrupt the status quo, as well.

"As an example of the business model side, in thinking truly disruptive, one of the things I would challenge you to do is when you're thinking about your business and what you do, what if you were giving your product away for free? Some of the most disruptive, data-driven companies in the world do that, or are able to do that,” said O’Brien. “So in this case, you have the idea of a large brewery giving away free beer around the world. That would be disruptive, for sure. All right, so where are they going to make their money then?”

As part of an exercise O’Brien said, various scenarios were considered in reaching beer-drinking customers. “What if you tracked all that data? What if you could get free beer if you had a QR code, a mobile app, they could scan? What if you knew every pub they went to, how much they drank, which brand? How much could you monetize that data for, in the industry? Or could you? So that was kind of, that's what you have to think about when you're thinking about being disruptive.”

Now, giving away free beer is a pipe dream—it's not going to happen, acknowledged  O’Brien. “But, maybe they can give away discounts. Maybe if they discount their beer, because they don't have customer information. How do you get that customer engagement data, right? In Hollywood, you buy a movie ticket. They don't know anything about you. They just know ticket sales. How do you get beyond that point into customers? That's where the disruptive thinking really comes in. And we came in with the fact that they were putting IoT devices on all of their kegs so they could track how much the flow was. More importantly, they could do preventative predictive maintenance on those so they could fix a keg before it broke so they never stopped flowing beer.”

And, taking that idea a step forward, said O’Brien, if the brewery knew what all of its customers drank, if it could optimize that mix, if it could have that kind of data, imagine what it could do with it. “That's what it means to be disruptive.”

Many presenters have made their slide decks available on the Data Summit 2019 website at www.dbta.com/DataSummit/2019/Presentations.aspx.

To access the full keynote, “Bring it Home: How to Advance Your Analytic Strategies,” go tohttps://datasummit.brightcovegallery.com/detail/videos/featured-videos/video/6040867209001/closing-keynote---bring-it-home:-how-to-advance-your-analytics-strategies?autoStart=true#links


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