In this webinar, Kenton Snyder, Product Manager at Intentwise, demonstrates how brands and agencies can use Microsoft Copilot AI to analyze Amazon data faster and uncover actionable insights without relying on pre-built reports or manually stitching together datasets.
The session explores how Intentwise AI Gateway connects Amazon data with AI tools such as Copilot, allowing users to ask questions in natural language and receive analysis based on live Amazon data. Kenton walks through practical use cases including performance reporting, keyword and campaign analysis, identifying optimization opportunities, diagnosing changes in ACOS, and combining advertising and retail data for a more complete view of Amazon performance.
Key takeaways
- Ask Amazon questions in natural language: Use Copilot to query Amazon advertising, sales, inventory, and other retail data without building complex reports or writing SQL.
- Analyze performance faster: Generate performance summaries, trends, and comparisons across campaigns, products, and time periods through simple prompts.
- Identify optimization opportunities: Use AI to surface high-performing search terms, products, and campaigns that may represent opportunities for further growth.
- Diagnose performance changes: Go beyond reporting to understand why metrics such as ACOS, spend, sales, or ROAS are changing and identify the campaigns, keywords, or products driving those changes.
- Combine fragmented Amazon data: Bring advertising and retail signals together to analyze performance across Sponsored Ads, DSP, Seller Central, Vendor Central, inventory, and other datasets.
- Build customized analyses: Copilot can help create dashboards, tables, charts, and recurring reports based on the questions and workflows specific to your business.
- Move from analysis toward action: AI-powered analytics can serve as a foundation for future campaign optimization and execution, reducing the need to switch between multiple tools.
- Maintain accuracy and security: Intentwise AI Gateway uses a semantic layer and domain-specific knowledge to provide more reliable answers while maintaining data-security controls when connecting Amazon data to AI clients.
The webinar also explores how AI-powered Amazon analytics can evolve from answering individual questions into repeatable workflows for reporting, auditing, optimization, and decision-making.
