Overview

I analyzed 1,906 raw customer reviews to identify what customers complain about and which areas the business should improve first.

Key Deliverables:

Theme & Sentiment Classification: Grouped text reviews into 13 key business themes and calculated the number of negative, neutral, and positive mentions for each category.

Data Visualization: Created charts showing the exact distribution of sentiment and a breakdown of negative reviews by volume to highlight the main operational priorities.

Priority Action Plan: Provided a structured table with recommended fixes and estimated business impact for every analyzed theme.

Business Value This report simplifies large amounts of text into clear charts and tables, allowing management to see their top operational risks and immediately prioritize maintenance and cleanliness updates.

Great job done

Peer Competition Analysis Problem: Client struggled to keep track of competitors' websites, marketing strategies, content updates, and market positioning. Manual competitor research is time-consuming, inconsistent, and quickly becomes outdated. Solution: I built an automated N8n workflow that accepts competitor website URLs, scrapes and analyses website content using AI, identifies weaknesses and opportunities, generates actionable business strategies, and stores insights in Google Sheets. The system runs automatically every morning to monitor all competitors and keep intelligence reports up to date. Results: Reduced competitor research time by up to 90%. Saved approximately 10–15 hours per week of manual analysis. Delivered daily competitor intelligence without human intervention. Identified market opportunities and competitive gaps faster. Created a centralised dashboard of competitor insights in Google Sheets