Can I import my own survey or support ticket data?
Yes. You can import CSV files of survey responses, NPS comments, CSAT feedback, or support ticket exports. BigSentiment's AI will analyze and theme-cluster them alongside your review data.
Customer Sentiment Analysis
Customer sentiment analysis from reviews, surveys, and support tickets. Identify recurring themes, track tone over time, and connect customer feedback to product and service decisions.
Turn scattered customer feedback — reviews, surveys, support tickets — into clear sentiment insights with theme analysis, tone scoring, and actionable recommendations.
What is customer sentiment analysis?
Customer sentiment analysis uses AI to automatically extract emotional tone and recurring themes from the feedback your customers leave across review platforms, surveys, and support channels. BigSentiment collects this feedback, scores each piece for sentiment, groups mentions by theme, and shows you exactly what customers love, what they complain about, and how those patterns change over time.
The value isn't just knowing that sentiment is 'positive' or 'negative' — it's knowing which specific themes drive each. A 4.2-star average rating tells you almost nothing. But knowing that 'wait times' drove 40% of negative mentions this month while 'product quality' drove 60% of positive ones — that tells you exactly where to focus.
Who it helps
- Product managers - Prioritize roadmap items based on what customers actually complain about and praise
- Customer experience leaders - Quantify CX improvements with sentiment tracking, not just CSAT scores
- Operations teams - Identify location-specific or service-specific sentiment issues before they spread
- Customer support leaders - Connect support ticket themes to broader review sentiment patterns
How it works
- Connect your feedback channels - BigSentiment monitors Google Reviews, Yelp, and other review platforms. You can also import survey responses and support ticket data.
- AI analyzes each piece of feedback - Every review, survey response, and ticket is scored for tone, classified by theme, and tagged with urgency if needed.
- Themes are clustered and quantified - BigSentiment groups feedback into themes with counts, tone averages, and representative quotes for each.
- Trends emerge over time - Weekly and monthly reports show which themes are growing or shrinking, so you can track whether improvements are working.
- Reports connect sentiment to action - Each report includes recommended actions tied to the specific themes driving negative or positive sentiment.
Data sources and signals
BigSentiment analyzes Google Reviews, Yelp reviews, and other major review platforms. You can also import CSV data from customer surveys (NPS, CSAT, open-ended responses) and support ticket exports. All feedback is categorized as direct voice — first-person customer experiences.
Theme extraction is powered by AI, which means themes emerge from the data organically rather than from a predefined list. This ensures you catch unexpected issues — like a new complaint theme that didn't exist last month.
Decisions it supports
- Which product or service improvements will have the biggest sentiment impact
- Whether a recent change (new menu, updated app, staff training) improved customer sentiment
- Which locations or segments have sentiment issues that need targeted intervention
- How to prioritize the product roadmap based on complaint frequency and severity
- Whether customer service investments are paying off in improved review sentiment
What makes BigSentiment different
- Organic theme clustering - Themes emerge from the data, not a predefined list — so you catch unexpected issues
- Feedback import - Bring your own survey and support ticket data alongside review monitoring
- Trend tracking by theme - See which themes are growing or shrinking over time, not just a single snapshot
- Representative quotes - Every theme includes real customer quotes so you hear the voice behind the score
Frequently asked questions
How are themes identified?
Themes emerge organically from the data using AI clustering. BigSentiment doesn't use a predefined category list — it reads every piece of feedback and groups them by the actual topics customers are talking about.
Can I track sentiment by location or segment?
If your feedback data includes location or segment metadata, BigSentiment can break down sentiment by those dimensions so you can identify location-specific or segment-specific issues.
Related BigSentiment pages
- Brand Sentiment Analysis - Use Case
- Sentiment Analysis Dashboard - Use Case
- Social Media Sentiment Analysis - Use Case