n8n, Apify
Brand Reputation Agent
Built for Mesa School of Business to teach students how automation can turn user feedback into brand intelligence.
Turning product reviews into insight, instantly
This agent analyses Amazon product reviews to understand how customers truly feel about a brand. It summarises sentiment, identifies recurring criticism, and recommends areas for improvement, helping brands make faster, data-backed decisions.
Results at a glance
80% reduction in manual review time
3 days from concept to pilot
1-click report delivered directly in Slack
The problem
Brands and product teams were spending hours reading through hundreds of Amazon reviews to understand customer sentiment. Manual analysis was slow, inconsistent, and often missed subtle patterns in feedback.
The solution
We built an on-demand agent that takes a single Amazon product link and returns a full sentiment analysis report. It scrapes all reviews, categorises them by tone, extracts recurring pain points, and summarises key recommendations for product improvement. The final report is shared directly in Slack for easy team access.
How it works
Input: User submits an Amazon product link through Slack.
Scraping: Apify gathers all reviews and ratings from the listing.
Analysis: GPT-5 processes the data to extract sentiment, identify major complaints, and highlight praise.
Report generation: A concise summary is compiled with a sentiment breakdown and improvement recommendations.
Delivery: The report is automatically sent back to Slack as a formatted message.
Impact
80 percent reduction in time spent analysing customer reviews
Faster, clearer decision-making for brand and product teams
On-demand access to real user sentiment across multiple SKUs
Designed as a teaching case for automation at Mesa School of Business
Build overview
Duration: 3 days (concept, build, and pilot)
Stack: N8N, Apify, GPT-5, Slack API
Client: Mesa School of Business (educational workshop)
Challenge: Building a reliable review scraper with dynamic page structures
In summary
The Brand Rep Agent turned review analysis into a fast, structured process. By combining intelligent scraping and sentiment reasoning, it enabled business students to see how automation can transform scattered user feedback into actionable brand insights, all inside Slack.
Next work
