A few things to have ready.
You do not need a large order history before installing. AI Upsell Engine can use your catalog to help find related products while genuine purchase patterns build over time.
That is fine. Real order patterns stay the priority when available, while AI product matching can help provide useful coverage for products with limited history.
From install to live recommendations in six steps.
Install and authorize AI Upsell Engine
Install the app from BigCommerce and review the requested permissions. After authorization, the app opens inside your BigCommerce control panel.
Choose a plan and approve billing
Select Starter, Growth or Pro based on your storefront count and expected usage. BigCommerce handles the billing approval screen. Your trial begins after you approve the plan when a trial is offered.
Run the guided setup
Click Start setup. The app syncs eligible products, imports the recent order history allowed by your plan, builds purchase-history relationships and prepares AI catalog matching in the background.
Review setup completion
When setup is ready, you will see your synced product count, imported orders, purchase-history pairs and AI catalog status. Continue to the dashboard once the setup reaches 100%.
Install the storefront widget
Open Settings, select the storefront you want to use, and choose Install widget. AI Upsell Engine creates the storefront script through BigCommerce Script Manager.
Open your storefront and verify recommendations
Visit a product page and cart. Depending on your settings and available recommendation evidence, you can see product recommendations, Frequently Bought Together, Smart Cart and cart recommendations.
Set up each storefront deliberately.
Your plan controls how many active storefronts you can manage: Starter supports 1, Growth 3, Pro 10, and Enterprise can be tailored for larger requirements.
Use the storefront selector in the app before changing settings or installing the widget.
Recommendation, Campaign and storefront options are resolved for the storefront you are working on.
Install or update the storefront script for each storefront you want active, subject to your plan allowance.
Where currency matters, the app uses the active storefront and checkout currency before returning shopper-facing Campaign or recommendation content.
Use this quick launch check.
- Open a product page and confirm a recommendation area appears where eligible.
- Confirm Frequently Bought Together appears on products with suitable complementary matches.
- Add a product to cart and check Smart Cart if you have it enabled.
- Open the cart and confirm cart recommendations load.
- If a recommended product needs size, color or another required option, confirm the shopper is asked to choose it before adding.
- Return to the app and verify that recommendation-view usage begins to move after qualified shopper impressions.
If something does not look right.
The app opens but asks me to choose a plan.
That is the normal fresh-install state. Choose the plan that fits your store and approve it through BigCommerce before the guided setup begins.
Setup is taking longer than expected.
Catalog and recommendation intelligence can continue in the background. Keep the app open long enough to see the current status, then check the setup progress again before retrying.
The widget does not appear on my storefront.
Open Settings, confirm the correct storefront is selected, check that the widget is installed, then run Store Health from Support. If the theme changed recently, update or reinstall the widget if the app asks you to.
I have very little order history.
You can still start. AI product matching can help find related catalog items while real purchase-history signals build over time.
I need help after trying these checks.
Run Store Health and include the support reference when you contact us. It gives support useful context without asking you to copy technical logs.
Start with a simple setup, then refine it.
Once recommendations are live, use the User Guide to learn how to manage Smart Cart, Campaigns, merchandising rules, analytics, AI tools and support features.