AI-Agents for Customer Insights Analysts in Retail
Agents help retailers stay responsive to shoppers as demand changes in stores and online.
Share specific customer feedback from reviews of competing products.
Your team gets competitor review alerts in its discussion channel. Each alert shows a rating and useful customer feedback, with a link to the review.
17 toolsDraft SQL counts of customers matching the requested criteria.
Get a SQL count query in the chat thread, with a clear note on what it counts and which conditions it uses.
15 toolsDraft SQL for questions about customer behavior.
Get a SQL query and a clear explanation in the same chat thread as your question, with results when you allow them.
14 toolsDraft joins across customer and feedback tables for insight questions.
Get a SQL query with the joins and filters your question needs, plus a short explanation in the same help thread.
8 toolsGroup recurring needs and flag thin survey evidence.
Get a market research brief on your study page. See customer wording and response examples alongside messages to test.
15 toolsCollect new and edited review text for customer analysis.
See new and edited customer reviews in one table, with ratings and links back to the source page.
4 toolsCollect dated review changes with links for customer analysis.
See new and changed map reviews across your locations in a dated table, with links back to the reviews and notes on scans that need attention.
Save public buyer feedback with its source for each new product.
See buyer reviews for new research products in your log, with clear flags when a product needs another check.
Keep the review log current and surface negative customer feedback.
Your team gets a weekly log of new public reviews, with sentiment labels that make unhappy customers easier to spot.
