Advancements in providing frictionless online shopping experiences happen daily, and eventually, we’ll have personalized experiences. Imagine a website where a person who is gluten intolerant will only see gluten-free products when she logs into GroceryRetailer.com. Or maybe it’s vegan.
For now, we have Past Purchase lists and searches to help the shopper. Search engines are getting better, but still aren’t perfect. Filters can help refine the pages and pages of search results, but due to issues with the underlying product data, numerous products disappear even though they would meet the criteria.
Of course, no one wants these missed sales opportunities. Retailers need complete data records to improve the shopping experience; they know that filters and site navigation improvements won’t work well without them. Manufacturers also need a way to keep up with all the new data requirements across their categories. They prioritize the task of updating product data when retailers demand it, and it’s often a “drop everything” situation. This work becomes outdated when there is a change in data fields, product formulations, or packaging.
Now, there is an automated, scalable solution to meet retailers’ changing requirements and complete the fields with accurate data. Allium AI has developed a proprietary technology to complete the underlying product data of a retailer’s product catalog or a manufacturer’s portfolio of products based on the information on the package image. Since it’s based on the current package being sold, retailers and manufacturers can rest assured that the data are correct.
Imagine shoppers’ delight when they select a filter and see all available products that match that criterion. Shopping for gluten-free, here are the items. Dairy-free, here they are. Peanut-free? Plant-based? If the manufacturer claims or notes it on the package, it’ll show up.
There are several other applications for this technology. It enables more relevant “people also viewed/bought…” for increasing basket size and impulse purchasing. When people find what they are looking for quickly, they are more likely to spend time discovering other products.
It can also offer suggestions for other products that would meet the shoppers’ needs if the product they want is out of stock. This would eliminate shopper frustration and prevent a trip or order to a different store.
With other advancements in AI, returning shoppers could have preferences built in based on past purchases and other selection criteria so they have a genuinely personalized mystore.com experience.
To learn more, reach out to the AlliumAI team here!