Nike's AI ambitions. Storefronts as a service. $1.9B for pet food.
Data per square foot
Brick-and-mortar retail is changing, and the metrics we use to judge its success need to evolve in response.
Stores are closing. Store formats are shrinking. And with US retail as overbuilt as it is, more downsizing is likely on the way.
Meanwhile, sales are moving online and the channels are mixing. We’re all increasingly likely to view things in stores then buy online later, and vice versa.
In this world, we can do better than sales per square foot.
Sales per square foot is a simple calculation — retail revenue divided by square footage of sales space — that retailers and investors have historically used to judge store productivity and compare the success levels of different brands. (For a typical rundown, check out CNBC’s retail ranking last year).
But, what if stores’ main purpose is no longer to sell things? Stores now are launching as experience centers, as wellness hubs, as frenzied hotspots for Instagram profile-boosting. Many pop-ups, like those hosted by Appear Here, stock few if any products.
As retailers expand the goals for their physical stores — beyond sales to engagement, virality, loyalty program enrollment, and more — they should consider looking to a new metric: data per square foot.
Data per square foot: driving growth
Data per square foot wouldn’t necessarily be a public, quantitative metric for retailers; rather, it’s a way of re-conceptualizing brick-and-mortar objectives and store design priorities.
These data sets range from the traditional (basic demographic data, email addresses, billing info) to the more modern: product try-on data, shopper emotions, in-store social media activity, and more.
Dozens of tech startups have sprung up to help retailers squeeze more data out of less real estate. Some of these technologies observe and analyze shopper activity behind the scenes, while others actually improve the store experience while soliciting personal data.
We’re also seeing the rise of tech companies offering holistic retail platforms focused on data collection — what we proposed calling RIoTaaS (retail-IoT-as-a-service) in a prior newsletter.
Luxury e-commerce startup Farfetch, for example, piloted a brick-and-mortar platform featuring smart mirrors and other features to monitor shoppers, and just yesterday, startup retailer B8ta announced plans to sell a tech-enabled storefront service on a subscription model. These new, holistic platforms can help retailers shape their stores around consumer analytics from day one.
Of course by better understanding their customers, retailers can improve everything from their marketing efforts to their product launches.
And we know data is the new battleground. Especially as more and more brands and retailers look to AI, they will need more and more data to feed their algorithms.
The company with the most data wins — and brick-and-mortar stores can become valuable data-collection foot soliders.