By Are Traasdahl
Retailers and brands lose billions of dollars per year due to out-of-stock items, waste and overstock. Better data collaboration can help retailers and brands understand exact demand levels per location, diminishing the frequency of these gaps between shopper behavior and merchandising decisions.
A typical grocery retailer’s in-stock goal is 98%. Anything below that rate generally leads to lost revenue. A rule of thumb is that for every 3% reduction in product availability, there is typically a 1% reduction in revenue. So, if a $100B retailer’s in-stock rates decreased by 3%, the potential lost sales would equal $1B. According to recent NielsenIQ research, empty shelves cost retailers over $82B in missed sales last year.
By sharing data on shopper demand and product availability in real-time, retailers and brands can ensure they do not have too much or too little of a product, and they can reallocate resources to better serve both brands and shoppers.
Everybody wins in this scenario of better data collaboration. Retailers get more sales and happier shoppers. Brands get shopper intelligence, less waste and better market penetration. Brands and retailers can manage logistics more effectively, decreasing costs passed on to the shopper, and shoppers get the products they want when and where they want them.
Retailers must improve data collaboration to reduce waste and improve performance
Retailers are developing more robust data sharing with brands, as evidenced in the recent rapid growth of retail media networks. This is especially important at a time when privacy changes in digital advertising are making it harder for brands without first-party data to target ads to shoppers.
Retail media networks allow retailers to monetize their first-party audiences by connecting brand advertisers with those audiences. But to earn advertisers’ dollars, retailers need to be able to help them understand demand per location and allocate media dollars effectively to drive product velocity in the right place at the right time. So, to build effective media networks, retailers will need to provide more transparent data on product availability and shopper demand, presenting the opportunity to fulfill both media and supply chain needs with better data collaboration.
Retailers building media networks know they need to help brands understand their shoppers to target ads effectively. But if they go beyond that to provide brands with visibility into how shopper demand and inventory levels fluctuate across locations, they can also save significant money for their brand partners on logistics and reduce waste.
Improved data collaboration between brands and retailers is at the foundation of the retail media boom. Shoppers see advertising from an entity they recognize, the retailer, and those ads intuitively reflect their past shopping experiences and demonstrated preferences. At the same time, supply chain data collaboration works behind the scenes to build shopper trust that the retailer always has what they need — the same customer obsession and high standard of convenience that has propelled Amazon to the top of the retail food chain in the digital era.
Building a competitive edge through greater data collaboration
Retailers require their systems to track product demand and inventory levels, transform data into actionable insights, and securely share that information with brand partners.
In retail, superior data collaboration goes back to delighting the shopper. Shoppers do not like getting targeted with irrelevant ads, nor do they enjoy personalized third-party ads that catch them off guard because they do not stem from a previous first-party experience with a business. Shoppers also dislike searching for an item online or — even worse, going in-store — to find that their desired product is out of stock.
For investors seeking to identify retail brands that will thrive, it is important to understand the forces at the forefront of industry’s digital transformation. There are flashy tech stories like, say, metaverse innovations, and then there are bread-and-butter (i.e., brick-and-mortar) opportunities to use newly available data and collaborative tools to harvest low-hanging fruit and eliminate waste.
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