Responsible AI FAQs for Personalized Shopping Agent (preview)
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Personalized Shopping Agent is a starter solution in Microsoft Cloud Retail that lets you offer your customers a conversational and personalized shopping experience. In this article, you find answers to some frequently asked questions (FAQs) about Personalized Shopping Agent and how Microsoft uses your data responsibly.
What is Personalized Shopping Agent?
Personalized Shopping Agent is a chat-based solution that you can embed into your own shopping websites and apps. It helps you enrich customer interaction and increase sales. Your customers can chat with an AI-enabled assistant, ask for suggestions, and get guidance to make informed shopping decisions. The assistant converts these insights into sales in a seamless way.
What are the system’s capabilities?
Personalized Shopping Agent uses a machine learning model called GPT-4 Turbo. GPT-4 Turbo is trained on a large amount of text from the internet and can generate new text that looks and sounds like human-written text. The assistant takes a natural language statement from a customer through a chat interface and provides a response that is conversational and relevant to your data.
What can Personalized Shopping Agent do?
Personalized Shopping Agent provides a chat-based interface to the end customers. Customers can have a conversational shopping experience on this interface in a natural language format.
Customers can have natural language-based queries related to any event. For example, “I'm going backpacking in Yosemite National Park in March. This adventure is my first such experience. Can you help in buying the essentials.” Or they can have specific queries related to a product or product line. For example, “Show me some beginner-friendly ski boots with good insulation.”
The inherent idea about this conversational experience is to give an experience to customers where they can get informed, aware and can then make the right product decision, as they would do while talking to a shopping personnel in a regular retail store.
What languages does Personalized Shopping Agent support?
Personalized Shopping Agent is currently supported in English language only. We plan to localize the solution to other languages where Azure OpenAI is present and based on customer asks. Reach out to mcfrcommunity@microsoft.com for any such discussion.
What services does Personalized Shopping Agent use?
Personalized Shopping Agent uses the following services:
Microsoft Fabric
Azure services such as Azure OpenAI, Azure AI Search, Azure Bing Search API, Azure Blob storage, Azure SQL, Azure Webapp/Function
Where does Personalized Shopping Agent process data?
Personalized Shopping Agent processes data in your Azure tenant by using Azure services. You define the Azure resources and choose the country/region where the data is processed, as per the availability of the Azure resources.
What data does Microsoft store for Personalized Shopping Agent?
Microsoft doesn’t collect or store personal data or user data. Microsoft gathers aggregated telemetry (stored for 30 days) about usage that helps us improve the quality of the product.
All shopper data and usage information are stored in Azure Blob storage, which is present in your Azure tenants. Microsoft doesn’t have access to this information. For more information on data privacy and security for Azure OpenAI service, refer Data privacy.
How did Microsoft evaluate Personalized Shopping Agent?
Microsoft has an evaluation stage as part of our design and development process. Microsoft uses a set of evaluation methods that include a collection of sample questions, answers, and relevant documents to test the quality of the AI answers vs the human answers baseline.
We evaluate the solution by following Microsoft quality guidelines. It’s advisable for you to conduct an evaluation check for each new implementation, as the product is currently in public preview, and we warmly welcome feedback. It’s important to note that the evaluation is conducted thus far for English.
As part of the development process, the product is going through a Responsible AI assessment following Microsoft RAI guidelines.
Features in the product also go through multiple quality reviews such as privacy review, security review, and threat reviews before launching to customers.
What are the current limitations of Personalized Shopping Agent? How can customers minimize the impact of Personalized Shopping Agent?
Personalized Shopping Agent is built on GPT-4 Turbo models in Azure OpenAI. The underlying technologies are trained on a wide range of sources and some answers might not be perfect. It’s important for you to do thorough test with internal users and provide feedback. This testing can help in setting up the right prompt based on retailers needs and brand requirements.
Personalized Shopping Agent undergoes three step process of launch- private preview, public preview, and General Availability. Since Personalized Shopping Agent is in public preview, we recommend you to use the solution in test environments only.
You can minimize the impact in two ways:
- Define specific prompts based on your domain and nature of business.
- Optimize appropriate prompts to align with your brand guidelines.