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By Steve Cavolick
Retail has long been a pioneer in the collection and analysis of data, and because retailers had strong information architectures in place, most were able to pivot and to focus on eCommerce when COVID-19 surfaced.
We know that digital shopping is here to stay, as a recent survey from Accenture showed that even for consumers who did less than 25% of their pre-pandemic shopping online, their digital purchases have increased by 343% since the pandemic began.
Since consumers are more inclined to digital than ever before, one of the ways retailers are creating stickiness is with the digital shelf. The digital shelf is a way to present the right products to online shoppers at the moment they are researching or trying to buy a product.
As eCommerce becomes more competitive, here are some ways that your data and analytics can help you hone the tactics for digital shelf optimization:
- Understand How Your Customers Shop: Are shoppers more likely to purchase single items in a store and multi-pack or bulk items online? Knowing this lets retailers offer price pack architectures that can increase profits 2-5% on product lines.
- Match Promotions To Consumers: Use predictive analytics to determine the likelihood a certain customer is going to jump on a promotion such as dollar threshold deals, quantity threshold deals, and first time purchase deals. As the importance of Environmental, Social, and Governance (ESG) initiatives grow, you should understand the types of customers who make purchases with cause-based offers (donating portions of the profits to a charity, for example.).
- Pick The Best KPIs: Select KPIs that match your organization’s primary business goals. In eCommerce, some of the most important metrics you can use to measure success include Conversion Rate, Customer Lifetime Value, Customer Acquisition Cost, Average Order Value, and Return on Ad Spend.
The digital shelf also benefits in-store shoppers, too, as another survey illustrated that 69% of consumers would rather read reviews on their phone than speak with a store worker. This means having prominent likes and reviews, as well as clear descriptions and pictures of products, is key to the digital shelf, no matter where it is deployed.
But what if the shelves in stores themselves could proactively provide product information? Hyperpersonalized shopping supported by a different kind of digital shelf will become the norm. Kroger’s EDGE technology (in partnership with Microsoft) is already being rolled out and will enhance the customer journey in stores through intelligent electronic shelf displays.
The displays eliminate the need for plastic and paper labels, thus reducing waste, while providing a customized shopping experience. The shelves digitally display pricing information that can be changed in real time to outprice local competitors. Have you ever bought something and the scanned price at checkout is different from what was on the shelf? Making an extra trip to the Customer Service desk for resolution should now go away with EDGE.
The EDGE shelves can also display paid video advertisements, and in-shelf cameras integrated with facial recognition will estimate your gender and age and present you with an offer as you walk by products other customers similar to you purchased (only if you opt in to the Kroger app). Speaking of the app, if you create a shopping list in it and opt in to EDGE, the app will guide you on an optimized route to your items, and the digital displays flash your personal avatar as you approach the item on your list so you can find it easier.
The blurring of digital and physical shopping experiences is upon us, and data will lead the way in delighting customers, reducing waste, enabling green initiatives, and increasing profitability.
If you are ready to build AI applications to personalize shopping experiences and improve profit, our data science team can help. If you’re not quite there yet, the LRS Big Data and Analytics group has over 20 years of experience implementing applications in advanced analytics, information management, and data warehousing, so we can help you advance on your data analytics journey.
If you are interested in understanding how we can help you find value in your data, please fill out the form below to request a meeting.
About the author
Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.