Our latest Masterclass covered the importance of measuring customer sentiment. In this blog we summarise how you can use tagging to accurately track trends and sentiment from your feedback.
Review tagging categorises customer feedback into themes like delivery, quality, or customer service, allowing you to track sentiment patterns over time. Without tags, thousands of reviews become noise. With them, you gain a clear roadmap for improvement.
Key Takeaways
- Tags turn unstructured feedback into trackable themes
- 5-10 core topics aligned to business goals allow greatest focus
- Weekly monitoring catches emerging issues early
- AI-powered tagging scales analysis across thousands of reviews
Why review tagging matters
When you collect hundreds of reviews, manually reading every comment becomes impossible. Review tags solve this by categorising feedback into themes, turning subjective text into quantifiable data. Tags reveal which issues appear most frequently, how sentiment changes over time, and where to prioritise resources.
Choosing your tags
Start with 5-10 themes aligned to business priorities. Think about what could cause customers to leave, and what would help future buyers decide. Retail businesses might track delivery speed, product quality, and sizing accuracy. Travel companies focus on room accuracy, cleanliness, and staff responsiveness. Finance brands monitor claims processes, fee transparency, and support accessibility.
Don't try to tag everything. Focus on what matters most to your business right now.
Making tags actionable
Each tag should connect to a business outcome. "Delivery issues" points to your operations team investigating courier performance. "Sizing inaccurate" signals your buying team needs to audit product descriptions. "Can't reach support" means customer service should review staffing levels.
Track how each theme trends week-to-week. Is delivery sentiment improving after switching couriers? Are customer service scores declining on Mondays? Define action thresholds before you're in crisis: any theme below 70% positive sentiment warrants investigation, whilst a 10% week-on-week decline requires urgent action.
How AI scales tagging
Manual tagging works for dozens of reviews. For thousands, you need automation. AI analyses every review consistently, detects emerging patterns humans miss, and categorises multi-language feedback.
For example, if a review of a coffee machine mentions ‘temperature’, it might be too cold or too hot. Tagging allows all these reviews to be easily assessed – and appropriate action taken (such as providing more detailed instructions on how to change the temperature!)
Discount Coffee reviews all feedback rated 3 stars or below weekly. When delivery complaints spiked, they tracked the sentiment pattern, identified the courier as the root cause, and switched providers. Delivery complaints dropped immediately.
Getting started with tagging
Read your last 20 reviews and manually tag them. Note which themes appear most often. Within a month, set up automated tagging through your review platform, create a weekly review meeting to discuss trends, and define action thresholds for each theme. Within a quarter, assign clear ownership per theme and share a "You Said, We Did" update showing customer impact.
Quick wins from sentiment tags
Not every insight requires months of development. If tagged feedback shows customers struggle with coffee temperature settings, create a simple guide, add it to your FAQ and product page, and include it in post-purchase emails. This addresses the issue immediately whilst creating helpful content for search engines and AI systems.
Read the complete guide to measuring customer sentiment, watch the whole masterclass, or book a demo to understand how Feefo could help you measure customer sentiment.
