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Set Up and Maintain Retail Execution
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          Create Agent Topic: Product Recommendations

          Create Agent Topic: Product Recommendations

          The Product Recommendations topic uses the Recommend Products to Upsell action to give telesales reps recommendations for upselling while they're taking orders.

          Required Editions

          Available in: Lightning Experience

          Available in: Agentforce 1, Einstein 1, Enterprise, and Unlimited editions with Consumer Goods Cloud Retail Execution and Agentforce for Consumer Goods Cloud add-on licenses.

          User Permissions Needed
          To create the product recommendations topic:

          Manage AI Agents AND Manage Agentforce Employee Agents

          OR

          Customize Application

          Before you begin:

          To create an agent topic:

          1. From Setup, in the Quick Find box, enter Agents, and then select Agentforce Agents.
          2. Select the Customer Service Assistance agent and click Open in Builder.
          3. Click New, and then click New Topic.
          4. Click Next.
          5. For Topic Label, enter Product Recommendations.
          6. For Classification Description, enter Gives ‌customer care executives recommendations for upselling while they're taking a customer's order. The recommendations also include information about frequently ordered products, top and low performance products.
          7. For Scope, enter Your job is to take the accountId to get the customer's information and only recommend the top 10 products, which includes the product sales pitch.
          8. For Instruction, enter Find the customer's information using the account ID and then call the Recommend Products To Upsell action to get the top 10 product recommendations, which includes the product sales pitch.
          9. Delete other instructions.
          10. Click Next.
          11. To assign agent actions, select Recommend Products to Upsell and Identify Record by Name.
          12. Click Finish, and then activate the topic.
          Example
          Example Here're few utterances for the dummy account NTO Store #201 that trigger this topic.
          • Recommend products for NTO Store #201 Store.
          • Which products has NTO Store #201 store frequently ordered in the past?
          • Can you recommend top-selling items for NTO Store #201 store based on past orders?
          • What are the most frequently out-of-stock items reported for NTO Store #201 store?
          • What products should I recommend to NTO Store #201 store based on their purchase history?
          • Which items have the highest reorder frequency for NTO Store #201 store?
          • Which products have seen the highest demand during recent NTO Store #201 store visits?
          • What products should I recommend to address the NTO Store #201 store’s reported OOS issues?
          • What items have the best performance in NTO Store #201 store?
          • What are the top cross-sell opportunities based on NTO Store #201 store’s historical orders?
          • Which fast-moving products should I prioritize for NTO Store #201 store?
          • Are there any under performing items NTO Store #201 store?
          • What products have the highest sales velocity for NTO Store #201 store?
          • Are there any under performing items NTO Store #201 store?
          • What products should I prioritize recommending for NTO Store #201 store today?
          • What products can I recommend to address low-stock issues in NTO Store #201 store?
          • What products have generated the most revenue for NTO Store #201 store in the last year?
          • Can you suggest products with a high repeat purchase rate for NTO Store #201 store?
          • What products should I recommend based on NTO Store #201 store’s top-selling categories?
          • What items have had strong performance in NTO Store #201 stores during the last Month?
          Note
          Note The data you provide, such as an account name, is case, space, and character sensitive. The agent interprets the data as is.
           
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