Amazon Ads Launches Natural-Language AI Advertising Analytics Tool
Amazon Ads launched an AI-powered conversational advertising analytics tool that lets advertisers use natural language to query new-to-brand customers, ROAS, and long-term sales performance.
What are the key facts?
- 1Amazon Ads launched an AI-powered conversational advertising analytics experience on September 28, 2026
- 2Advertisers can use natural language to query new-to-brand customers, ROAS, and long-term sales performance
- 3The tool is for brand sellers, agencies, and advertising operations teams using Amazon Ads
- 4The tool integrates reports, spreadsheets, and manual analysis into an interactive visual workspace
What happened?
On September 28, 2026, Amazon Ads launched an AI-powered conversational advertising analytics experience for brand sellers, agencies, and advertising operations teams using Amazon Ads. Advertisers can ask questions in natural language to identify which campaigns brought in the most new-to-brand customers, compare ROAS across different advertising products, and review advertising’s impact on long-term sales and New-to-Brand purchases. The tool also supports follow-up questions and trend views by advertising product, time period, campaign, or customer type.
The core change is not the addition of fees, but the integration of tasks that previously required report exports, spreadsheet preparation, and manual analysis into an interactive visual workspace. For brand sellers with larger advertising budgets, the feature may increase the frequency of budget adjustments. In analysis, sellers should consider new-to-brand customer acquisition costs, long-term conversion, and marginal ROAS in addition to sales and ad-attributed orders. The original source also notes that sellers should first standardize advertising names, product groupings, and profit definitions; otherwise, the AI may produce conclusions that are not suitable for direct execution based on incomplete cost data.
What does this mean for cross-border sellers?
Brand sellers, agencies, and advertising operations teams using Amazon Ads can use natural language to query new-to-brand customers, ROAS, long-term sales, and New-to-Brand purchase performance, reducing report exports and manual preparation. Budget adjustments may become more frequent, but sellers should assess performance using new-to-brand customer acquisition costs, long-term conversion, marginal ROAS, and complete profit definitions—not only sales and ad-attributed orders.
What should sellers do now?
- 1This week, organize query definitions by advertising product, campaign, and customer type for brand stores using Amazon Ads; record new-to-brand customers, ROAS, and long-term sales performance; and produce a reviewable analysis table with abnormal trends flagged.ACoS / ROAS calculator
- 2This week, standardize advertising names, product groupings, and profit definitions for brand stores. Then use natural-language queries to separately examine new-to-brand customer acquisition costs, marginal ROAS, and New-to-Brand purchases, checking whether each result is supported by corresponding cost data.
- 3This week, for stores with larger advertising budgets, compare ROAS, long-term sales, and new-to-brand performance across advertising products and product categories. Create a shortlist of budget-adjustment candidates and retain the query conditions and supporting basis for each conclusion.