In-Store Shopper Analytics for Bedding: 3 Things to Know

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by Lisa Cramer

We all know the mattress sale has changed. Consumers now purchase online. And, their needs, expectations and demographics are shifting.

So, how do you not only keep up, but stay ahead of the competition? Advances in anonymized facial detection and wireless devices are helping mattress retailers and manufacturers to increase shopper conversion and grow in-store revenue. How? By using new shopper behavior and demographic KPIs around specific points of influence in-store to measure and adapt brick-and-mortar stores just like online stores. So, what is this technology really?

Here are the 3 things you need to know about in-store shopper analytics for the mattress industry:

  1. What Does In-Store Analytics Mean Today?

    For years in-store shopper analytics typically meant door counts or even heatmapping. But, growth in technology and falling costs have dramatically expanded the depth and precision of KPIs that can be gathered in-store, as well as the ability to understand what’s converting shoppers and driving sales.

    The mattress industry is one industry well-positioned to leverage this opportunity. As consumers continue to visit mattress stores less frequently and more sales shift online, optimizing conversion on every in-store visit is increasingly crucial. To optimize these in-store visits, we now need to know not just how many consumers come in the door, but who walks by each product, of those that walk by who glances at each bed, what gets them to stop, how many lay on each bed, and of those, who purchases. With this view of the in-store funnel, we can take control of the customer experience and start to predict and drive mattress sales. Instead of time-lagged, post-purchase sales data, now we can capture and act on real-time metrics around consumer behavior and demographics.

    So, how does it work? All data is captured through anonymized facial detection and wireless devices and served up on a real-time dashboard, with advanced filtering and comparative analysis capabilities. This data can be crucial in immediately identifying why a particular mattress store, brand or product is underperforming and in staying competitive by providing constantly changing consumers with exactly what they want.

  2. What Can You Measure?

    We’ve touched on a few of these new metrics afforded in-store with analytics above, but let’s take a closer look. You’ll see that many of the metrics that are gathered online, now can be gathered in-store. And there are specific measurements that can only be tracked in-store where mattresses are actually laid on and tested. Here are a few examples of baseline metrics:

    • # of people that enter a store
    • # of people that walk by each bed
    • # that glanced per bed
    • # that laid on each bed
    • How long they dwelled around each bed
    • Gender and age counts for each of the above
    • Mood (smile) counts
    • Day/time/location breakouts
    • And more…
  3. What Can You Do With It?

    Just as important as uncovering missed revenue opportunities with real-time analytics, is the ability to understand that data to make more informed marketing decisions in-store. Some specific applications of these insights include:

    • Determining which mattresses get no attention
    • Determining which personas (demographic and behavior) interact with which mattresses
    • Optimizing product layout
    • Testing content/promotions throughout the store and per product or category
    • Comparing stores and layouts to determine the most successful
    • Understanding which promotions resonate with which segment
    • Utilizing responsive content and its impact on influencing shopper behavior

 
How could your mattress store or brand benefit from in-store shopper analytics discussed here? Click here to learn more.

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