EN- Industry Focuses

How can building a deeper understanding help retailers? ey can identify developing themes, such as which items are being picked up and put back, or where people are walking and stopping. ey can see why people are abandoning their carts, and why conversion rates aren't higher. It means getting an understanding of what you're getting right and what you aren't, what's engaging and what isn't. Do retailers understand the potential of analytical data? All retailers understand it, but I don't know how many realize the value of it. It depends on where they are in their maturity curve, but we've seen some retailers that say things like, "I already have too much data; I don't need more." Other retailers believe the operational decision-making distracts from the business. en you've got retailers who really get it, who want to get into deep learning and machine learning. ey're starting to understand that it can drive more business understanding, and make them more competitive. Are retailers aware of the analytical tools available? e tools are better, but retailers don't know it yet. On the spectrum, it's moved from printed reports to digitized reports, and being an employee who looks at numbers and gets a gut feeling to one who gets prescriptive instructions that say, "Do these three things for these reasons." As the toolset gets better, the understanding will change. Retailers need data, analytics, and insights at the speed of conversation, but that doesn't mean that you should be refreshing your dashboard more oen. It means you need a better tool that will give you better insights and allow you to get ahead. Is the loss prevention industry in need of disruption? ey've been using outdated tools for a long time. Loss prevention has historically been about watching the camera, then getting staff on the ground to intervene, but most of the loss in a big chunk of retailers is white-collar crime: very organized, and not as opportunistic. Catching offenders takes additional intelligence, and a better toolkit to do that. Being able to leverage predictive, deep learning, and machine learning technologies to see patterns in fraud should be the goal. Loss prevention teams can't afford to have an army of people watching cameras anymore; they need to start automating camera- watching and putting intelligence behind finding. en those cameras can have multiple functions, such as improving merchandising and operations. What's on the horizon? We're seeing a drive toward automation to free up salespeople so they can focus on the customer, and the business can leverage spending by using technolog y for more than one purpose. at's how they're going to fund a better-quality customer experience. "Loss prevention teams can't afford to have an army of people watching cameras anymore." A proactive approach to planning can make all the difference when attempting to stay ahead of the curve with evolving technologies and business models. 38 39 Retail Retail reality check

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