Case: Launching a Retailer-Facing Chatbot for End-Customer Support

Context (completed)

You are evaluating whether to launch a chatbot that retailers can embed to automatically answer their end-customers’ questions (B2B2C setting). The goal is to reduce support costs, improve CX, and potentially drive conversion for sales-related queries. Assume you have historical support logs, site analytics, and limited pilot telemetry, but no randomized A/B test. A visualization was referenced but not provided; see assumptions in the last section.

Prompt

1. Should we launch this chatbot? Outline the product’s value, risks, and expected business impact.
2. Without running an A/B test, how would you size the opportunity and define success metrics for:
   • Users (end-customers and retailers)
   • The business
   • Model performance
3. Review the provided visualization and explain its strengths and weaknesses.

Hints

• Frame goals, metrics, opportunity sizing, and qualitative/quantitative evaluation.
• Consider cost savings (deflection), revenue impact, safety/brand risk, and operational guardrails.