
Managing a large retail catalog, one of the biggest challenges is making sure customers can actually find what they’re looking for. With thousands of products across brands, categories, and seasonal collections, search and product discovery play a huge role in how smooth the shopping experience feels.
What I like about Marqo is how well it handles that discovery layer. The platform trains an LLM on the product catalog and learns from customer behavior like browsing, clicks, and purchases, so results feel much more aligned with what customers are actually looking for.
The Merchandising Studio is another highlight. Being able to apply rules like pinning products or supporting campaign visibility is really helpful, especially when certain products or brand initiatives need to be surfaced while the system still optimizes the rest of the results.
The analytics are also very strong. It’s easy to see what products are trending, how customers are interacting with search, and what queries are driving engagement, which provides valuable insight into how customers are shopping the catalog.
Overall, Marqo combines strong search relevance, personalization, merchandising controls, and analytics in a way that fits very well with how modern ecommerce teams manage product discovery. Review collected by and hosted on G2.com.
There is a natural adjustment period when shifting from manual merchandising to AI-driven optimization. Once teams gain confidence in the system, it becomes much more efficient. Review collected by and hosted on G2.com.


