Recommendation Agent
The right product, right when they want it.
Turn your online store into a personalized shopping experience. This agent analyzes browsing behavior and purchase history to surface dynamic product recommendations.
Deploy this AgentWhat it does
The Product Recommendation Agent powers the 'Trending Now', 'Best Sellers', 'Frequently Bought Together', and 'Similar Products' widgets on your eCommerce site. It uses collaborative filtering to understand what products naturally pair together.
Native Integrations
- eCommerce
- POS
- CRM
- Inventory
Powered by your real-time unified data warehouse.
How it works autonomously
Analyze
Continuously processes all transaction data to find item correlations.
Personalize
Factors in the current user's browsing history and past purchases.
Display
Dynamically populates recommendation widgets on product and cart pages.
Frequently Asked Questions
Does this only work online?
While it powers eCommerce widgets, it also prompts cashiers on the POS with suggested add-ons during in-store checkout.
What if it recommends an out-of-stock item?
It is deeply integrated with inventory and will never recommend an item that cannot be purchased.
How does 'Frequently Bought Together' work?
It analyzes thousands of past receipts to find statistically significant pairings (e.g., people buying this specific coffee also buy these specific filters).
Is this AI agent an add-on or included with SalesVu?
It is part of the SalesVu AI Workforce that ships with the platform. Your account team can confirm what is bundled in your specific plan and whether any optional modules apply.
Does it require new hardware?
No. It runs against the data already flowing through your SalesVu account. Same iPads, terminals, kiosks, scanners and printers you already use.
How long does it take to turn on?
Most operators enable agents during their onboarding session. Once your products, orders and locations are in SalesVu, the agents have what they need to start producing drafts and recommendations.
Does it work across multiple locations?
Yes. Agents are configured per-location and roll up to a corporate view, so a multi-site operator sees both the per-store drafts and the consolidated picture.
Where does the agent get its data?
From the SalesVu data layer — POS sales, eCommerce orders, Inventory on-hand, vendor history, CRM and loyalty events — all the operational data the platform is already collecting.
Will the agent ever take an action I have not approved?
By default agents draft and recommend; the human approves. You can later opt to auto-send specific actions once you trust the outputs.
Does this work for restaurants and retail or just one?
Both. SalesVu is one platform across retail, restaurants, salons, studios, venues and grocery, so the same agent works whether the SKU is a t-shirt, an entrée, a service or a class.
Where do the recommendations appear?
In your eCommerce product pages and cart, on kiosks and at the POS customer lookup. Same engine, surface-appropriate placements.
Are recommendations based on what really sells together?
Yes. The Cross-sales Analyst feeds the recommendation model with real co-purchase patterns from your stores, not a generic catalog model.
Can I exclude items from being recommended?
Yes. You can exclude SKUs, categories or any product attribute.
Will recommendations respect inventory?
Yes. The Recommendation Agent reads live on-hand from SalesVu Inventory, so it stops recommending an item that just went out of stock.
What do the Website Builder Recommendation Widgets actually render?
You Might Also Like, Similar Products, Frequently Bought Together, Past Purchases, Trending Now, New Additions and Best Sellers — each a standard component you can place on any page. You get the full merchandising stack without integrating an external personalization platform.
What do the same widgets do inside OrderUp QR ordering?
The kiosk and table-QR flow render the same AI-driven suggestions as your website. Average ticket grows on every channel, not just online.
What does Product Tagging give the recommendation engine?
Tags refine 'similar' so the model knows a sundress is similar to other sundresses, not to every dress. Recommendations land instead of feeling random.
Ready to deploy the Recommendation Agent?
Join thousands of brick-and-mortar operators automating their back office with SalesVu.