Build a Custom Sentiment Analysis Dashboard Using AI in Minutes
Describe your Sentiment Analysis Dashboard in plain English and Emergent delivers a build that's ready to launch. Design, development, and deployment in minutes. No code needed.
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Emergent Key Features for Building a Sentiment Analysis Dashboard
Every source classified into themes with accuracy measured rather than assumed.
Every Source Classified Together
Reviews, tickets, survey comments and social mentions are analysed on one scheme, so themes can be compared across channels.
Themes Rather Than Keywords
Text is grouped by meaning rather than by word matching, which is what makes the resulting categories genuinely actionable.
Drivers Separated from Volume
Themes that most influence sentiment are distinguished from those merely mentioned often, which changes what you fix first.
Accuracy Measured, Not Assumed
A sample is compared against human assessment, so classification quality is a known figure rather than a hope.
Low Confidence Surfaced
Items the classifier could not confidently categorise are flagged for review instead of being silently misfiled.
Classification Stored with the Record
Each item keeps its classification alongside the original text, so a theme can always be traced back to what people actually wrote.
Sentiment Analysis Dashboard Use Cases You Can Build in Minutes
Measure What People Say, Not a Sample
Volume and sentiment split across positive, neutral and negative by source and period, twelve month trend, sentiment by product, region and customer segment, the sources with the most negative sentiment and the periods where sentiment shifted.
window.awbMockup = { sentimentOverview: "Build a sentiment analysis dashboard showing volume and sentiment split across positive, neutral and negative by source and period, sentiment trend over 12 months, sentiment by product, region and customer segment, the sources with the most negative sentiment, and periods where sentiment shifted materially with the events around them.", themeExtraction: "Build a theme analysis dashboard grouping text into recurring topics, showing volume and sentiment per theme, themes growing fastest this quarter, themes strongly associated with negative sentiment, representative examples per theme, themes appearing in one source but not others, and new themes emerging in the last 30 days.", driverAnalysis: "Build a sentiment driver dashboard identifying which themes most influence overall sentiment rather than simply appearing most often, themes mentioned by dissatisfied customers specifically, the combination of themes that appears before a customer leaves, sentiment by customer value, and the single theme whose improvement would move overall sentiment most.", classificationQuality: "Build a classification quality dashboard showing a sampled set of items with the automatic classification against a human assessment, agreement rate by sentiment and theme, categories where the classifier performs worst, items the classifier could not confidently categorise, classifications corrected by a reviewer, and accuracy trend since the last adjustment."};
Group by Meaning, Not by Keyword
Text grouped into recurring topics with volume and sentiment per theme, themes growing fastest this quarter, themes strongly associated with negative sentiment, representative examples, themes appearing in one source only and new themes this month.
window.awbMockup = { sentimentOverview: "Build a sentiment analysis dashboard showing volume and sentiment split across positive, neutral and negative by source and period, sentiment trend over 12 months, sentiment by product, region and customer segment, the sources with the most negative sentiment, and periods where sentiment shifted materially with the events around them.", themeExtraction: "Build a theme analysis dashboard grouping text into recurring topics, showing volume and sentiment per theme, themes growing fastest this quarter, themes strongly associated with negative sentiment, representative examples per theme, themes appearing in one source but not others, and new themes emerging in the last 30 days.", driverAnalysis: "Build a sentiment driver dashboard identifying which themes most influence overall sentiment rather than simply appearing most often, themes mentioned by dissatisfied customers specifically, the combination of themes that appears before a customer leaves, sentiment by customer value, and the single theme whose improvement would move overall sentiment most.", classificationQuality: "Build a classification quality dashboard showing a sampled set of items with the automatic classification against a human assessment, agreement rate by sentiment and theme, categories where the classifier performs worst, items the classifier could not confidently categorise, classifications corrected by a reviewer, and accuracy trend since the last adjustment."};
Fix the Theme That Moves the Score
Which themes most influence overall sentiment rather than simply appearing most often, themes mentioned by dissatisfied customers specifically, the combination appearing before a customer leaves, sentiment by customer value and the highest impact theme.
window.awbMockup = { sentimentOverview: "Build a sentiment analysis dashboard showing volume and sentiment split across positive, neutral and negative by source and period, sentiment trend over 12 months, sentiment by product, region and customer segment, the sources with the most negative sentiment, and periods where sentiment shifted materially with the events around them.", themeExtraction: "Build a theme analysis dashboard grouping text into recurring topics, showing volume and sentiment per theme, themes growing fastest this quarter, themes strongly associated with negative sentiment, representative examples per theme, themes appearing in one source but not others, and new themes emerging in the last 30 days.", driverAnalysis: "Build a sentiment driver dashboard identifying which themes most influence overall sentiment rather than simply appearing most often, themes mentioned by dissatisfied customers specifically, the combination of themes that appears before a customer leaves, sentiment by customer value, and the single theme whose improvement would move overall sentiment most.", classificationQuality: "Build a classification quality dashboard showing a sampled set of items with the automatic classification against a human assessment, agreement rate by sentiment and theme, categories where the classifier performs worst, items the classifier could not confidently categorise, classifications corrected by a reviewer, and accuracy trend since the last adjustment."};
Know How Accurate the Classification Is
A sampled set of items with the automatic classification against a human assessment, agreement rate by sentiment and theme, categories where the classifier performs worst, items it could not confidently categorise and accuracy trend since adjustment.
Know How Accurate the Classification Is
A sampled set of items with the automatic classification against a human assessment, agreement rate by sentiment and theme, categories where the classifier performs worst, items it could not confidently categorise and accuracy trend since adjustment.
Build a custom sentiment analysis dashboard in 4 simple steps
Classify text from every channel into themes and sentiment, so what people say is measurable rather than something you read a sample of.
Start with the sources you receive open text from, such as reviews, support messages, survey comments, social mentions and sales notes, and the themes that would be actionable if you could count them. Emergent builds classification around your own domain.
Link the systems holding that text. Emergent classifies each item by sentiment and theme, stores the classification alongside the source record, and keeps a sample for human review so accuracy can be checked rather than assumed.
Ask to add a theme, merge two categories, change how sentiment is scored or include another text source, and every item is reclassified with accuracy measured again.
Deploy one build where each team sees the themes relevant to them and leadership sees overall sentiment and what is driving it. Comments become a ranked list rather than an unread archive.
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Most tools give you a demo you have to rebuild. Emergent gives you a product that is ready to run.
| Comparison | Other Tools |  |
|---|---|---|
| Built for | Demos and MVPs | Products you keep growing |
| What you get | Front end shell only | Full stack, wired end to end |
| Backend and database | Set it up yourself | Built and connected for you |
| Customization | Surface level styling | Deep workflow control |
| Integrations and APIs | Manual glue work | Connected from a prompt |
| Code ownership | Locked to the platform | Clean code you can export |
| Time to launch | Weeks of patching and setup | Live the same day |
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