Topic Modeling and Sentiment Analysis of Customer Reviews, VoC, and Survey Responses

InfraNodus will reveal the main topics in your text data, identify the sentiment, discover the structural gaps and use the AI to generate new product ideas.



 
Watch an Introduction
 

 

Text mining and topic modeling using network analysis

InfraNodus Features

You can perform sentiment analysis of product review data or survey responses, revealing the main topics in positive / negative reviews. You can also identify the structural gaps in the customers' discourse and use the built-in AI to generate new product ideas.

Survey Responses and Product Reviews

You can upload your survey responses and product / customer reviews as well use the Amazon import.

Sentiment Analysis of Customer Reviews

Use the built-in BERT AI model to identify the sentiment for each customer review (positive, negative, neutral).

Reveal the Main Topics and their Relations

Reveal the main topics in the positive / negative reviews and the context where they appear using the network graph.

Use the GPT-3 AI to Generate New Ideas

Detect the structural gap in the customers' discourse and use the built-in AI to generate new product ideas.



Multilingual

Study the markets in multiple countries and languages: English, German, French, Spanish, and Italian.

Fully Shareable

You can download hi-res copies of the graphs to add to a presentation. You can also export a URL or an embed code to add it to your website.

Market Comparison

You can compare the different graphs together to see how they overlap or how they differ. Use the filters to reveal the missing parts.

Advanced Analytics

Our text network analysis algorithms will reveal the main topics, the most influential terms, and latent ideas in any discourse.



Review & Survey Responses Analysis Workflow:

 

Import the customer reviews, survey responses, VoC data, and detect the clusters of main topics inside. Unlike other tools, InfraNodus shows you the results in context (e.g. "battery" connected to "life").

Topic modeling of customer review data

Use the advanced BERT AI model to reveal the sentiment in your responses / reviews. Filter the results by sentiment to see what the negative reviewers are talking about (or the positive ones).

Sentiment analysis of customer reviews

Use the integractive graph to find the parts of the customers' discourse that seems interesting to you. Zoom in and find the reviews that contain a certain term.

Get the relevant excerpts using the graph

Identify the structural gap (the ideas that are not yet connected) and use the AI to generate ideas that would fulfil this gap.

Identify the structural gap - what ideas are not connected yet


Sentiment Analysis Workflow





Other Marketing Workflow Demos:

Check out those help articles from our support center below, which demonstrate a workflow for finding a market niche and for performing sentiment analysis of customer review data:


Market Niche Finder     Sentiment Analysis

 



Try it With the Real Graphs:

The graph below is a visualization of Tesla customer reviews from 2018, filtered by the low rating, so you can see what the customers who give the car a lower rating don't like about it:

  Tesla Reviews (2018, 1 & 2 stars)
 

The advantage of InfraNodus is that it doesn't just show you the keywords, but also the interactive relations between them, so you can click on those terms and better understand the context of the customers' sentiment or of a market discourse.

You can also import and analyze customer product reviews from any Amazon site, so you can study your competition or simply use it to make a more informed decision.

Sign Up to Try with Your Data


 
 
 
 

Start Using InfraNodus

Sign up for an account now, so you can get insight using this tool for your own data and texts.