The second day of GroceryShop was much more technical than the first. I attended the AI track, where I absorbed a lot of information thick and fast about the applications of AI in retail and consumer packaged goods (CPG.) Retail, groceries, and consumer packaged goods are perfect for AI applications, simply because there are so many points on the journey for the goods themselves, going from warehouse to shelf. Then there is the customer journey that takes a wandering path form entrance to checkout.
The supply chain and customer experience have largely been analog, and as customers’ expectations continue to rise, there’s no way to optimize without an algorithm that learns as it goes. How can you figure out which store needs a certain brand of detergent based on how quickly it had sold in the last 30 days? Sure, you can pull up a spreadsheet and search for the SKUs, but what about that shipment with the diet dog food? How do you get those off the shelf faster? What about POS? You heard customers huffing about long lines again. Oh, and don’t forget to print those reminders that dairy is 20 percent off this week. And don’t forget to dispose of unsold merchandise!
It’s a lot, too much really, for one person to handle. Creating an efficient, adaptable system is impossible for one person to do.
Personalization Is Still Big, But A Challenge
At GroceryShop, Coresight CEO and founder Deborah Weinswig shared the insights of a survey of retailers to demonstrate their priorities. For them, personalization is very important, but it’s proving to be moving target. Retailers sell so many different products to changing consumers with changing needs. In the next year, 40 percent of retailers plan on investing in AI, but that’s not necessarily going to help personalizing if the human manger doesn’t point AI in the right direction. Personalizing a physical object takes more time than customizing an email, but consumers are looking for a personalized experience as they shop. “We expect so much when we go to these [big box] stores,” so and so said. There is a lot of room for AI to fill when it comes to shaping the overall experience, either through gamification or personalizing items around the experience, such as emails or coupons. In addition, retailers want to reduce waste, but if they are creating a personalized experience, then there is a better chance that the goods will be sold, reducing overall waste.
SCORE-ing Big
Weinswig debuted their proprietary SCORE model, to help retailers to configure their AI strategy to give them the right frame of mind as retailers set out to maximize both profits and efficiencies. SCORE is an acronym, broken down this way:
S is for smarter customer engagement
C is for communication
O is for operational efficiency
R is for removing friction
E is for eCommerce/Omnichannel
This isn’t the typical awareness and decision funnel that most marketers and salespeople are familiar with. The CORE model is a new methodology and guide for retailers to re-examine how they can interact better with their customers with the help of AI. What is the customer wants, and how can the retailer get the customer faster and with less friction? AI isn’t a magic wand. But how you can make it best serve your business? That is where the CORE model can be useful.
The Customer Journey is Key
“If you think about how AI can best serve your business, it’s really sales and anticipating demand,” said Weinswig. This is a unique challenge that AI is equipped to help with, because AI can tell you which products are selling fastest in which stores, and which customers are buying them. But the rest is up to the retailer and, by extension, the marketer. Once you have successfully narrowed down which customers are buying what, how do you reach them faster? How do you evaporate their pain points and shorten their journeys? This is where the marketer can really shine. Armed with a framework and toolkit to place the customer front and center, the retailer can strategically place product on the shelves with confidence it meets the consumers’ ever-changing needs.
