Transforming Sales Intelligence:
How an AI Chat Platform Empowered
8,000 Global Field Sellers

In this project, I designed an internal AI chat platform from the ground up to streamline user inquiries about the Marketplace.

Due to NDA restrictions, I am unable to disclose all the details.

Overview:
Field Sellers on the Microsoft commercial marketplace were struggling with fragmented information across multiple platforms, leading to inefficient searches and delayed sales processes. As Lead Product Designer, I spearheaded the development of Knowledge Base Chat (KBC), an AI-powered solution that revolutionized how our global sales force accesses critical marketplace information.

Problem
Field sellers faced three key obstacles in their daily operations:

  • Scattered Resources: Information was spread across multiple platforms.

  • Time-Intensive Searches: Inefficiencies from a lack of a streamlined tool.

  • No Real-Time Support: Delays in obtaining information disrupted sales processes.

My Role
As Lead Product Designer, I owned the end-to-end design process, including:

  • Product strategy development

  • User research and synthesis

  • Interaction design

  • Prototyping and usability testing

  • Cross-functional collaboration with development teams

The Opportunity
Despite having extensive marketplace resources, field sellers struggled to quickly find the information they needed to drive sales. With content scattered across multiple platforms and no real-time support system, valuable selling time was lost searching through documents. We identified an opportunity to develop an AI-powered chat platform that would not only centralize information access but transform how sellers engage with marketplace resources.

Impact

This tool has been rolled out to 
8,000 Field Sellers globally

  • Successfully deployed to 8,000 field sellers globally

  • Increased seller confidence through reliable, instant information access

  • Accelerated revenue growth through improved sales efficiency

  • High user satisfaction rates driven by features like re-ask capability and content indexing

  • Platform scalability demonstrated through successful integration with key tools like Seismic

Team/Collaboration

  • Lead Product Manager: Overseeing the project and ensuring alignment with business goals.

  • Sr.Director: Providing strategic direction and decision-making.

  • Engineers: Responsible for developing and implementing the AI chatbot.

  • Data Scientists: Ensuring the chatbot is trained on high-quality data and information.

Next

Marketplace Customers Dashboard (Microsoft)