Our latest Masterclass covered the importance of measuring customer sentiment. In this blog we summarise how AI can speed up the process of analysis and introduce our latest feature: Tag Analytics.
AI sentiment analysis processes thousands of customer reviews in seconds, categorising feedback into themes and revealing which issues impact your ratings most. Tag Analytics turns this data into a prioritised action plan, showing you exactly where to focus resources for maximum impact.
AI sentiment analysis uses natural language processing to read customer reviews, identify themes, and assess emotional tone. Unlike manual reading, AI evaluates every review with the same rigour without bias or bad days.
When a customer writes "The boots are beautiful, but delivery took two weeks," a human sees a 3-star review and moves on. AI breaks this into Product (positive) and Delivery (negative). This precision reveals your product performs excellently, but your logistics partner damages overall scores. You now know exactly where to intervene.
Tag Analytics goes beyond counting mentions. It quantifies how each theme impacts your rating and conversion rate. You can see that delivery speed has a 0.8 correlation with overall rating whilst packaging has only 0.3 correlation, helping you prioritise fixing delivery over packaging redesign.
The action matrix provides a visual dashboard showing:
Real-time pattern detection spots emerging issues before they scale.
Many legacy review platforms simply bolt AI onto outdated analytics tools, resulting in generic categories that don't match your business operations. Tools developed on AI from the ground up structure data intelligently from day one, align sentiment categories with your teams and products, and provide insights that fit your actual workflow.
AI handles reading every review, consistent categorisation, pattern detection across time and segments, and multi-language analysis at scale. Humans handle context and nuance like sarcasm or regional slang, strategic decisions about budget and timelines, customer responses requiring empathy, and implementing operational changes. AI is your radar scanning the horizon for storms. You're still steering the ship.
Feefo's Tag Analytics operationalises your tags by transforming existing categories into actionable Topics with auto-generated summaries. The action matrix provides a visual dashboard showing where to focus today, whilst impact analysis explains how sentiment affects ratings and what that means for conversion.
Boosting your average rating by 0.1 stars can increase conversion by 25%.
A retail client discovered through Tag Analytics that delivery speed drove 40% of rating variance, whilst packaging drove only 8% despite receiving more mentions. They redirected resources from packaging redesign to logistics optimisation, improving their rating by 0.3 stars in three months.
Audit your current approach to see whether you're manually reading reviews or using basic keyword counts. Choose a platform built on AI rather than one with AI added afterwards, and map your existing tags to ensure they align with business goals and team ownership.
Within your first 30 days, let AI categorise your last 500 reviews, review the action matrix with your team, and identify your top three priority themes with clear ownership. Within 90 days, track how sentiment changes as you implement fixes, share progress with teams and customers through "You Said, We Did" updates, and refine tags based on what you've learned.
AI sentiment analysis doesn't replace human judgment – it amplifies it. You stop guessing what matters and start knowing, backed by data from every customer who took the time to tell you.
Read the complete guide, watch the whole masterclass, or to understand how Feefo could help you effectively measure customer sentiment, speak to a consultant.