Build better digital commerce with Salesforce Commerce Cloud

Personalized storefronts based on shopper behavior

Generic “customers also bought” recommendations may not reflect what a shopper is viewing or considering at that moment. We implement Salesforce Commerce Cloud to build storefronts that respond to browsing and cart activity, rather than relying only on past purchases.

With Data Cloud and Agentforce, recommendations can change based on current activity. A conversational shopping assistant can also answer product questions and add the right variant to the cart. This helps reduce the steps that can lead to cart abandonment.

What our Commerce Cloud experts do for you

Storefront Strategy & UX

Design the storefront journey from landing page to checkout based on how your shoppers browse and make purchase decisions.

Product Catalog & Merchandising Setup

Organize products, variants, and merchandising rules so shoppers can find relevant products quickly.

Checkout & Payment Configuration

Configure checkout flows and payment integrations to make the purchase process simple and reduce unnecessary steps.

AI-Powered Recommendations

Configure Data Cloud-driven recommendations that use browsing and cart activity to suggest relevant products, including cross-sell and upsell options.

Conversational Commerce Enablement

Deploy an Agentforce-powered shopping assistant that answers product and specification questions and can add items to the cart.

Order Management & Fulfillment Integration

Connect the storefront with order management and fulfillment systems so order, inventory, and shipping information stays in sync.

Commerce Cloud in action

Here are two examples of what we’ve built with Commerce Cloud, Data Cloud, and Agentforce as part of the broader storefront services we deliver.

AI-driven product recommendations at checkout

Standard “customers also bought” recommendations may not reflect what a shopper is viewing during their current session.

How it works

Data Cloud captures browsing and cart activity. Recommendation logic uses this information to adjust cross-sell and upsell suggestions at checkout based on what the shopper is currently viewing.

Conversational shopping assistant

Shoppers may leave when they cannot quickly find the right product variant or get answers to sizing and specification questions.

How it works

An Agentforce-powered storefront assistant answers product questions using catalog and specification data. It can also add the relevant product variant to the cart based on the conversation.

A simpler path from product questions to checkout can help reduce cart abandonment.

FAQs

Will real-time recommendations slow down our storefront?

No. Recommendation logic is designed to work within normal storefront performance expectations, similar to standard merchandising widgets.

Both. We configure the checkout flow and payment integrations as part of the implementation.

It can do more than answer questions. The assistant can add the relevant product variant directly to the shopper’s cart based on the conversation.

No. We can work with your existing catalog structure and configure recommendations and the shopping assistant around it.

Yes. We integrate the storefront with order management and fulfillment systems so order, inventory, and shipping information stays in sync.

The recommendations and shopping assistant can use the customer and behavioral data captured through Data Cloud across connected Salesforce clouds.