MicrosoftProductionEvidence: Low40/100

Personalized Shopping Experiences Drive Retail Operational Efficiency

A retail-focused AI agent, built using Microsoft Copilot Studio and the Power Platform, enables personalized product discovery for both in-store associates (B2B) and end customers (B2C). The Copilot Studio-based shopping agent can be embedded across multiple user interfaces, allowing contextual suggestions and sales assistance via channels of choice. It integrates with both core business applications and third-party data to make relevant product information easily accessible, supporting faster, data-driven sales closures. Designed to address operational inefficiencies and labor shortages, the agent helps retailers adapt to fluctuating demand while enhancing shopper experiences. By leveraging out-of-the-box connectors and robust flow design on the Microsoft cloud, the solution accelerates deployment and scales effortlessly within retail environments.

Organization
Unspecified
Industry
Retail
Location
Global
Published
May 2025
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
Unspecified
Provider
Microsoft
Maturity
Production
Linked source
learn.microsoft.com

Designed to address operational inefficiencies and labor shortages, the agent helps retailers adapt to fluctuating demand while enhancing shopper experiences

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

  • 1AI-powered Personalized Product Discovery Agent
  • 2Assisted Omnichannel Shopping Experience
  • 3Retail Sales Agent Powered by Copilot Studio
  • Deployment of a personalized product discovery AI agent using Microsoft Copilot Studio and Power Platform.
  • Integration with core retail applications and external data to deliver contextual guidance and recommendations across digital and in-person channels.
  • Headless, embeddable AI agent that can be tailored to multiple personas (store associates or customers) and accessed through various interfaces.
Sources & evidence1
Evidence: Low40/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • Technical implementation details available
Published: May 3, 2025Publisher: learn.microsoft.com

AI-generated summary. Verify important details with the linked sources before relying on this case.

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