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How Shopper Journey Data Can Deliver ROI for Retail COOs

May 19, 2023

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From planning labour to managing supply chains to overseeing purchasing and more, chief operating officers (COO) in retail have a lot on their plates. With so many decisions to make, what COO wouldn't want the right decisions to be crystal clear — backed by hard data served up on a single, easy to understand dashboard?

Let's examine what shopper journey data is available, why it matters, and how that data can leveraged to deliver value across retail operations — and the entire enterprise.

Location, location, location

One of the most fundamental questions operations heads have to contend with is very simple: "Where should we put our stores?" And that question is likely to be top of mind at the moment, considering a staggering 71% of Asia Pacific's (APAC) surveyed retailers plan to open more stores in 2023, according to CBRE's 2023 Asia Pacific Retail Flash Survey. Unfortunately, as simple as that question may be, the path to finding an answer is anything but.

Of course, there can be a staggering number of factors to weigh in the balance when choosing locations. That's why location strategy planning often involves specialists and expensive consulting firms and is notoriously slow and laborious. But with the right data — namely, Shopper Mobility data — COOs can take some of the pain out of the process. Shopper Mobility data can tell you what other stores customers visit when passing by a given location, and whether there are competing or complementary stores in the surrounding area — which can help you both estimate visitor demographics and, more specifically, income levels of potential consumers.

Even better, for any location you're considering, Shopper Mobility data can show you valuable data points, like the volume of potential customers that pass through that area any given time, distance travelled, and where they're coming from, which allows you to estimate whether they're commuters or just locals running errands.

Think of it as a way of removing potential locations — retail parks versus city centre, shopping centres versus standalone — so you can focus more on potential locations with high traffic value. Sure, that doesn't alleviate all the pain from location planning, but it can answer some vital questions that, in short order, make a very long process mercifully shorter.

Optimizing in-store operations

For your existing stores, the right in-store and beyond-the-store data can tell your operations team a number of solutions you can use to refine and eventually optimise a given store's performance. APAC shoppers are notoriously comfortable with online shopping — and not just Click & Collect or home delivery. Consumers in APAC are leading the world in adoption of live and social commerce, thanks in part to China's online retail juggernaut event Singles Day. It's critical for retailers to understand this enthusiasm for online channels does not decrease the importance of in-store operations — on the contrary.

In fact, 60% of Asia Pacific shoppers prefer visiting physical stores, and 54% of shoppers prefer retailers who create a more personalised shopping experience, according to a MartechAsia 2022 Retail Report. How can retailers capitalise on this reality in their stores? You guessed it: shopper journey data. For operations teams specifically, the three most applicable solutions are Traffic Counting, Computer Vision, and Shopper Mobility. Here's a sample of what you can do with the data each solution delivers:

Traffic Counting

  • Understand your peak traffic times for each day, and staff accordingly. Likewise, see what shifts can operate with minimal associates to avoid unnecessary labour spend.
  • Understand your ideal shopper-to-associate ratio (STAR) to provide the best possible customer experience.

Computer Vision

In-store analytics

  • Benchmark dwell time and draw rate, and use this data to optimise both layout in a zone or department, as well as promotional display location.
  • Trace customer pathing from one department to the next to strategically enhance in-store layouts.

Parking facility analytics

  • Better understand parking lot usage and, if necessary, refine its layout.
  • Improve service levels by knowing how long shoppers wait in their cars for Click & Collect orders to be fulfilled.

Shopper Mobility

  • Understand where you customers shop before and after they visit your stores, and use this data to evaluate potential partnerships or services with those properties.

Each of these potential use cases provides operations leaders with actionable ways to improve the customer experience, increase profitability, and streamline operations. (Many of these also overlap with use cases for CMOs — read more on that here.) This is hardly an exhaustive list, but it should give you an idea of the potential this data has for impacting operations across the enterprise.

Takeaways

At Sensormatic Solutions, we know retail. That means we know there's no magic bullet solution, analytic, or metric that will solve all of your operational challenges. It also means that when we say we know there are a variety of valuable use cases you can deploy to improve the areas of performance that keep you up at night, you can trust us. As COO, no one knows what those challenges are better than you. As leaders in retail and technology — with decades of experience and expertise — no one knows solutions better than us.

To see the entire picture of how in-store and beyond-the-store data can be used to deliver outcomes that improve operations and drive profitability, get your copy of our latest white paper, Creating Experiential Retail Along the Shopper Journey, today.

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