A new e-commerce search system uses AI to understand what shoppers mean, not just what they type. Instead of keyword matching, it interprets phrases like "sparkly boots" or "outfit for Coachella" to find relevant products. Companies using it see a 20-25% jump in search volume and higher conversion rates.
It just works better. Let the customer be who they are, describe what they're looking for, understand that intent, and bring back the right results that's gonna lead to further conversions and revenue. So what's new with Agentic Commerce Search? We've been trained as consumers and as shoppers to use keywords for the last 25 years, and it's how people try to describe what they want and what they're looking for. That's not how people actually wanna search. They want to use the language and the words that matter to them. Large language models, Bard, Gemini, ChatGPT, are teaching us a different way, and frankly, it's just better. Context-aware allows you to just say whatever it is you're looking for. So if I'm searching on sparkly boots, sparkly is not gonna be in the product description, but with context-aware search, we know what sparkly means. We have a model that is multimodal that can look at images and everything about the product. I can say, give me an outfit to wear to Coachella. The model understands that and will bring back a set of products, an assortment of products that will look good. You can expect to see certainly mid-single-digit improvements. Customers are searching 20 to 25% more because they see that it works, leading them to more product detail pages. You get those numbers boost your conversion and your revenue's got a boost as well.
