Empathy AI

EMPATHY AI LABS #4

Conversational insights & setups

AI-driven conversational agents to talk to your analytics and insights

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Motive
Project #1Conversational AI Analytics
Productized
Inspired by: Original idea
Ready for: Motive

Conversational AI Analytics is an AI-powered, privacy‑first, interactive merchant assistant, available directly from the commerce store search bar. It lets merchants chat with analytics and insights to understand catalog performance, shopper behavior, and the impact of any merchandising actions in real time. Available now for shops using Motive Commerce Search, which includes Backroom functionality.

Based on the Model Context Protocol (MCP), the Conversational AI Analytics agent connects natural-language questions with live analytics data, transforming complex data queries into simple conversations. Data analysis becomes more accessible and explainable through natural dialogue and real-time visual graphs.

The Conversational AI Analytics agent is evolving to become an even more powerful ally for merchandisers. Soon, it will proactively suggest intelligent configurations for the commerce search and discovery, helping effortlessly elevate the store’s performance and create exceptional shopping experiences.

Key features
  • Natural language interface: Interact with your analytics and commerce store insights using conversational queries.
  • Real-time insights: Get instant answers to your data questions through AI-powered analysis.
  • Context-aware responses: The system understands context and provides relevant, actionable insights.
  • Multi-dimensional analysis: Explore data across different dimensions through simple conversations.
Use cases
  • Business intelligence analytics
  • Commerce store performance analytics
  • User behavior insights
  • Real-time data exploration
  • Merchandiser's configuration suggestions
Application scenarios
Originally built for commerce store performance analytics, Conversational AI Analytics can be applied across various business scenarios to make data more accessible and actionable, such as:
  • E-commerce analytics: Ask questions about sales performance, customer behavior, and product trends in natural language.
  • Marketing insights: Explore campaign performance, conversion rates, and customer engagement metrics through conversation.
  • Operational metrics: Get real-time answers about system performance, user activity, and operational efficiency.
  • Executive dashboards: Enable non-technical stakeholders to explore data without learning complex query languages.

Discover shops that already use it

Biciclasica

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