AI for Market Research

Categorize thousands of comments in minutes

Qualitative data is arguably the most insightful data. It is when people express themselves in their own words that analysts can get a true understanding of people’s opinions. Unfortunately, qualitative data is time-consuming to analyze at scale, and it is expensive when commissioning a research study.

Solution

This is why we are developing technology that can help analysts harvest insight from text. We combine natural language processing, sentiment analysis, threats and abuse analysis and other data mining algorithms to categorize unstructured text. Whether you are analyzing social media content, answers to open-ended survey questions, or focus group transcripts, our AI can help you categorize thousands of comments in minutes.

BEnefits

We provide a ready-to-use application packed with the following functionality. You do not need to be a technical person to get these benefits:

  • Analyze tweets, open-ended responses, and more
  • Categorize content into different themes
  • Extract relevant keywords
  • Generate topic summaries
  • Determine the sentiment of each response
  • Detect inappropriate or abusive language
  • Visualize the categorized data
  • Export data in CSV format for further processing
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Case Studies

See how these organizations used AI to improve their operations

Insight Automation

Automating Customer Feedback Analysis

A national training organization uses AI to harvest customer sentiment

The organization was able to:

  • Extract comments from thousands of print forms in minutes
  • Automatically categorize comments by sentiment
  • Visualize service strengths and weaknesses
records classification automation

Automating the Verification of Database Records

A market research firm uses AI to reduce the workload of their data verification team

The company was able to:

  • Categorize thousands of records in minutes
  • Automate the processing of newly acquired records
  • Integrate the AI into their existing data pipeline