Yotpo's WordPress integration brings ratings, review widgets, and (depending on which Yotpo modules are active) loyalty data into the site. The underlying product information still lives in WordPress: WooCommerce or EDD products as wp_posts with wp_postmeta, taxonomies for categories, and any custom fields you added. Yotpo's plugin exposes review and loyalty data either through its own option records and shortcodes or via webhook output written into the database.

SleekAI's data-source wizard reads from whichever of those layers Yotpo exposes on your install, plus the underlying WooCommerce or EDD records. The result is a system message that can reference live product details and the latest Yotpo-driven ratings and loyalty events at the same time. The bot can quote an average rating, mention a recent review highlight, and explain how many loyalty points the logged-in customer has, all in one conversation, without inventing any of those values.

Display conditions scope each bot by post type, taxonomy, user role, and URL pattern. Multibot lets a product-aware shopper bot run alongside a loyalty-focused account bot. Every conversation logs inside WordPress with model name and page context attached.

Yotpo gives WordPress stores two strong layers of social proof and retention: real customer reviews and a loyalty program with points and tiered rewards. Both of those layers tend to live in separate widgets on the page, and shoppers have to read carefully to extract a clear picture. The result is a steady stream of questions in chat, support email, and product Q&A: what is the actual rating, has anyone mentioned a particular concern, how many points do I have, which tier am I close to.

A generic chatbot trained on the open web cannot answer any of that, and a guess will undercut the trust the Yotpo widgets are meant to build. The Yotpo WordPress plugin already brings review and loyalty data into the install in some form, and the underlying products live in WooCommerce or EDD. SleekAI's data-source wizard maps both layers into the chatbot's system message at request time, so a single conversation can move from a product review summary to a loyalty balance check without leaving the page or breaking context.

Display conditions keep each bot scoped to the right surface, multibot supports separate shopper and account bots, and the conversation log makes it easy to see which Yotpo-related questions show up most often. The result is that Yotpo's hard-earned data drives an interactive chat layer instead of sitting passively in widgets the visitor has to interpret on their own.