AI in Retail: Beyond The Hype and Into Reality for Store Operations.
The Top 10 AI use cases that Retail Operators at every level told us would transform their daily work. AI for Retail Operations is...
With the launch of Chat GPT, AI suddenly feels real and a top priority again.
It is, of course, impressive that Chat GPT can write a poem or pass an exam. But if you’re a Store or Field Leader with a complex store or district to run, that isn’t particularly useful.
So we sat down with 40 Store and Field Leaders to ask them what the most valuable questions are that AI could answer for them. They came up with 10 use cases which – if AI could successfully deliver them – would transform their daily work.
I.e., With different issues facing each store each week, how can AI decipher where I should focus my efforts?
I.e., With Retail Managers often solving the same issues across the country at different times, how can AI surface and share best practice insights in an automated and timely way?
I.e., How can AI scientifically analyze the $ impact of changes that my team and I make, so that we know what to keep doing…and what to stop?
I.e., With increasing spans of control and finite time, how can AI help Field Leaders identify the stores that most urgently need their help?
I.e., Given every store’s unique issues, how can AI ensure Field Leaders are equipped with the relevant information they need to make each store visit easy and effective?
I.e., What actions did we agree or implement last week? Have they been completed? And what has been the $ impact of those changes? How much value am I creating as a manager? And how can I generate more?
I.e., With Field Leaders now digitally connected, how can AI put streamlined data at their fingertips in real-time so that they can coach and congratulate from the road?
I.e., While BI dashboards give broad brush direction, how can AI be used to aggregate crowdsourced insights and impact from across the network? E.g., what are customers telling store teams about your products?
I.e., While BI takes a top-down approach to performance, how can AI flip this around and automatically ladder-up frontline opportunities to central teams?
I.e., With most actions now logged in online systems, how can AI calculate impact at the individual level so that performance can be accurately measured and rewarded? (Rather than just rewarding those managers who run the most advantaged stores.)
At Quorso, we’re privileged to be working on these, and other AI use cases, for some of America’s smartest and largest retailers. Our experience so far is that technology can be up to 6x as effective at prioritizing and guiding managers’ daily work as the more traditional “management by walking around” approach. But this is still a new area and further improvements are very likely.
Got questions or ideas about the future of AI in Retail? We’d love to hear from you!
Quorso is an intelligent management system that embeds AI into retail store operations. First, AI-driven analytics identifies and prioritizes issues at the Store and District level. Then, smart workflows guide action based on proven past successes. This creates a virtuous data cycle whereby every new action improves the system’s ability to both find and fix performance issues.
Quorso is being used in 28,000+ stores at some of America’s top retailers. It was voted a ‘Technology Game-Changer’ at the World Retail Awards and ‘Best Quick Impact Technology’ at the 2023 NRF VIP Awards.