Tag Analysis
It provides a comprehensive analysis of the most commonly mentioned topics or themes (“tags”) in customer feedback. It helps you understand what customers are talking about and how they feel about those topics.
Key Components
These are themes or keywords extracted from open-text feedback (e.g., “Quick approval”, “High interest”, “Customer care”).
Sentiment Bar (Color-coded)
This bar visually shows how customers feel about each tag.
- Here, the green color indicates positive feedback, the orange indicates neutral feedback, and red indicates negative feedback.
Volume (%)
Indicates how many times a tag was mentioned, along with the percentage out of total feedback
Helps identify the most common issues.
Volume Change (%)
Compares the current tag frequency with the previous period (weekly/monthly).
Shows whether a topic is gaining or losing attention.
Reflects customer satisfaction level for each tag.
- Positive NPS = Happy customers (Promoters)
- Negative NPS = Dissatisfied customers (Detractors)

Green: Positive Feedback Orange: Neutral Feedback Red: Negative Feedback
Word Cloud
The frequently used words in the Word Cloud help generate automated summaries and tag suggestions for the overall feedback overview.
- Behind every Word Cloud is raw customer verbatim data.
NOTE: Word Cloud summaries are automatically refreshed with every sentiment change, ensuring your analysis stays current and actionable.
Summary
The Summary section provides an overview of the overall customer feedback based on the analyzed tags and sentiments.
It highlights the key takeaways from the feedback dataset, helping users quickly understand the overall customer experience without reviewing individual responses.
The summary typically includes:
Top Strengths
Highlights the most positively mentioned aspects of the product or service.
Example insights may include:
-
Fast delivery
-
High product quality
-
Good customer support
These strengths help identify areas where the business is performing well and creating positive customer experiences.
They are the most appreciated themes or topics customers talk about in a positive tone in their feedback.
- What did customers like the most about the product or service?
- Helps identify strengths and promoters in the customer journey.
Example: “Easy / Fast Process, Quick Approval”
- Volume: 195 mentions (33.39%)
- NPS: +43.28
- Customers praised the quick and hassle-free loan process, making it the top positive experience
represent issues or pain points mentioned by customers with negative sentiment.
- What customers are unhappy or frustrated about?
- Helps identify areas needing immediate improvement.
Example: “Extra Charges / Penalties”
- Volume: 25 mentions (4.28%)
- NPS: -12.43
- Customers were upset about unexpected or unclear charges, leading to dissatisfaction.
Tag Volume change
It shows the increase or decrease in the number of times a specific tag was mentioned compared to a previous period (week/month).
- Growing concerns or praises around a topic.
- Helps track if a particular issue is rising or falling over time.
Tag Net Sentiment Change
It reflects the change in customer sentiment (positive vs. negative) for a specific tag over time.
- Whether a tag is being viewed more positively or negatively now compared to before.
- Useful to see if changes (e.g., service fixes) are improving customer perception
Tag Trend
It shows the monthly trend of tag volumes, how frequently each feedback tag was mentioned over time.
- Tracks rising or falling discussions around each tag.
- Highlights which issues or positives are gaining or losing importance among customers.
- Helps in identifying recurring pain points or improved service areas.
Example Insights from the Chart
“Easy / Fast Process, Quick Approvals” (Light Blue Line):
- Consistently has the highest volume over months (e.g., peaks at 21 mentions in Jan 2024).
- Shows it's a strong positive experience for users.
“High Rate of Interest” (Yellow Line):
- Started with 8 mentions in Mar 2023 but gradually declined.
- Indicates that concerns about interest rates have reduced or become less frequent.
“Extra Charges / Penalties” (Red Line):
Has low but steady mentions throughout.
Suggests it's a minor but persistent concern
Verbatim Section
This section captures individual customer responses (verbatims) along with their star rating, the sentiment detected (Positive / Neutral / Negative), the option to tag the feedback.
Related Articles
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Sub-Tags
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Train Verbatim
Train Verbatim The Train Verbatim section allows users to review, categorize, and train AI models using actual customer feedback responses (verbatims). It enables you to assign tags, adjust sentiment, and refine text analysis results, ensuring that ...