With The Right Data, Retailers Can Reach That Coveted ‘One Consumer’

In the growing discussion about online and offline retail convergence, a simple but devilishly difficult-to-embrace truth has emerged: While a person sees a retailer as one brand, regardless of which channel a consumer choose to use, the same can’t be said of the retailer.

With The Right Data, Retailers Can Reach That Coveted ‘One Consumer’

by CMO.com Team

Posted on 11-10-2017

This article is part of CMO.com’s November series about commerce and consumerism. Click here for more.

In the growing discussion about online and offline retail convergence, a simple but devilishly difficult-to-embrace truth has emerged:While a person sees a retailer as one brand, regardless of which channel a consumer choose to use, the same can’t be said of the retailer.

This level of insight and discovery can happen only by matching in-store and online behavioral data. Regarding the latter, retailers know practically every aspect of how their e-commerce channel performs–from click-by-click and browse-by-browse views of the consumer path, to heat maps that inform how activities convert to sales, to what gets in the way of conversion. Online retailers know what a person is searching for and whether that search leads to a purchase. They can even tell whether someone looks at a product, then abandons that consideration, goes somewhere else, and buys a whole different category.

The story is not quite the same for brick and mortar. While retail marketers know a lot about how their physical stores perform, they don’t know a lot about what shoppers are actually doing in their stores. They know sales volumes by item, category, and department. They even know which stores and cities are delivering the most sales. But their understanding about where store traffic is the highest and why is observational and assumptive at best.

One way they can better understand what motivates store visitors–their interests and what makes them buy or not buy–is by evaluating how they move through the space. The missing element is the ability to capture those insights directly and piece them together with the online data.

Imagine what a retailer could do if it had a single, unified full view of the consumer path–online and offline. It would be able to see “one consumer,” understand what products that person is looking at, and understand how the consumer is looking at them across all channels.

For example, a consumer may tend to use a department store’s online site for buying children’s clothes for a growing toddler, while she may prefer to go into the physical store to try on clothes for herself before buying there. If the retailer were to only look at one behavior or the other, it might actually see two consumers–one who buys women’s clothes and one who buys children’s clothes–and make incorrect assumptions. But if that retailer could match the online and in-store behaviors by overlaying the different data points, it could see a single consumer who has a different mission when shopping different categories.

Matching online and in-store behavioral data points leads to new insight into how mindset determines the channel that the “one consumer” uses to shop and purchase. This insight can inform a number of product merchandising strategies and opens the door to upsell and cross-sell opportunities, such as positioning in-store pick-up near the women’s clothing to tempt her to check out the new fashions.

Acquiring the capability to see the one consumer might seem like a no-brainer, and every retailer should be doing it. But the truth is, surprisingly few retailers are. It begs the question: Why?

The simple answer is that they don’t have the data. Most often, this is because they fail to treat their brick-and-mortar spaces as important data assets for informing the full and improved customer experience. Just as retailers test and learn in the digital space because every webpage is so valuable, they need to do the same in the physical space, because every square foot is valuable.

That’s not to say retailers don’t collect shopper data in their physical stores. But they typically do it via proxy means that can–at best–triangulate on insights. Methods such as Net Promoter surveys, shop-alongs, and checkout surveys are labor-intensive and usually generate fairly small sample sizes that can be prone to human error and bias. Beacons and cameras can collect traffic data, but it is typically not high quality and usually misses a lot of the traffic because of opt-in requirements or camera angles. Ultimately, none of these methods comes close to providing the depth and accuracy available from the online channel.

To solve for this, savvy retailers are taking advantage of new sensing and pathing technologies, which can provide real-time views into shopper behavior across the entire store. These technologies deliver the same always-on, movement-by-movement capture that lets the retailer understand how consumers move through the store, where they visit, and where they dwell. Unlike beacons that engage mobile loyalty apps, these sensing devices don’t collect personal information and can run independently of the retailer’s technology network.

Real-time sensing data allows retailers to “run back the tape” and observe where shoppers convert and fail to convert in the store. The data gives highly accurate insights into in-store performance, with answers to questions like: What is each store’s busiest days and times? How are our endcaps performing? How did our marketing affect store traffic? How many customers stay on the perimeter of the store? How many go down every aisle? And how many come in and leave right away?

Layering information about how these customer segments behave in-store, along with detailed online activity insights, takes the guesswork out of creating a great experience—from getting the right staffing in place in key departments and checkout, to ensuring that the messaging, promotion, and signage address the consumer’s needs.

The convergence of offline and online retail channels is a necessary response to viewing the consumer online and in-store–as one consumer, not separate entities. Retailers have a future vision of what their store environments need to be, and they need the best available data and insights to make those decisions. For the brick-and-mortar store, this means better data on shopper behavior that tells the full story of what’s happening in the store. Every retailer’s DNA is different, and deciding how to best use augmented store insights depends on that DNA.

The important thing is to see that “one consumer” across all channels, understand his mindset and purpose, and meet him where they choose to interact with the right offer in an easy, friction-free shopping experience.

Topics: Retail, Experience Cloud, Insights Inspiration, Digital Transformation, Digital Foundation, Analytics, CMO by Adobe

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