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Prototype

Sentiment Analysis for Customer Feedback

In partnership with the SAP ConcurĀ® UX team, we built a sentiment analysis tool to assess and analyze large volumes of customer feedback, and help prioritize areas for improvement.

The prototype was created using a natural language processing technique called tf-idft (term frequency-inverse document frequency), which involves term-weighting and linguistic algorithms that assign values to positive, negative or neutral responses from users. Machine learning processes the multiple datasets to reveal trends and notable indicators over time.

See additional details in the blog article.