Imagine you’re a consumer goods manufacturer with hundreds of appliances on the market. Every day, customers around the world come to your sites and use the search bar to look for answers, solutions, and information.

Unbeknownst to you, a search trend is emerging around one of your flagship products, indicating that a high volume of customers are running into problems with this product at the very same point in the customer journey. Good to know!

The question is, how were you supposed to know? Herein lies the considerable potential of user sentiment analysis.
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How user sentiment analysis helps you connect the dots

Though user sentiment analysis is not a new concept, it is today more beneficial than ever in the so-called age of customer experience. The combination of modern site search experiences, machine learning and artificial intelligence, and analytics has enabled new and powerful insights around why customers use your site search.

What is their intent behind a given search? What do they need? Where are they struggling?

Are the search terms entered positive in nature, negative or neutral?

This kind of user sentiment data can now be gathered, organized, and parsed into reports to help organizations reveal actionable conclusions about deficiencies in their customer experience. These organizations then have data-backed improvements they can make with the potential to impact customer lifetime value tremendously. 

For example, these organizations can:

  • Identify common themes across different audiences or products. For example, the consumer goods manufacturers mentioned above might discover that negative searches are clustering around the setup process for one of their flagship consumer models within the European market.
  • Quantify the areas along the journey where customers are struggling the most and prioritize improvements based on the sources of most friction. A high volume of negative searches around the warranty claims process, for example, might indicate that this “touchpoint” is worthy of closer review.
  • Use data to guide strategic plans for content improvement based on any gaps, deficiencies, or inaccuracies that are revealed through sentiment analysis.

Tap into user sentiment with MindTouch Intelligent Search

User sentiment analytics are part of the MindTouch Search Insights report for all customers running the latest version of MindTouch. Through the application of machine learning models influenced by billions of human interactions applied to online search queries and reviews, MindTouch can provide powerful insights around user sentiment

  • What are people searching for and why?
  • What is the intent behind a given grouping of searches?
  • Based on user sentiment data, where along the journey are people struggling most?

These are the kinds of insights that MindTouch Intelligent Search can help unlock.