Theme and Sentiment Analysis

Many organizations are focused more and more on the experience of customers, employees, and partners recognizing that behind every person is a story. These stories can help organizations illuminate and improve moments that matter most to individuals. Often these stories are gathered through open-ended questions in surveys and questionnaires.

As more and more qualitative feedback/stories are collected, the problem lies within how to leverage the insights, positive or negative, for continuous improvement in organizations. These stories can serve to assist organizations in recognizing the behavior, preferences, wants, and needs of those they serve—not as point-in-time insights, but as an ongoing relationship. “Businesses know there is a richness in the qualitative feedback they have collected, yet many struggle with the best way to utilize it in a systematic way to help make better business decisions, quicker,” states NLP Logix Modeling and Analytics Lead, Mary Sheridan.

To bring an understanding to this mass of open-ended feedback NLP Logix has developed a theme and sentiment analysis solutions to gather, collect, categorize and inform organizations of insights. Theme and sentiment analysis was built utilizing Natural Language Processing (NLP) to do the following:

  • To organize and tag comments with appropriate themes.
  • To understand the sentiment (positive or negative feelings) expressed in the comment.
  • To alert management teams to situations and issues in comments which are most likely to require a response or action.

Sheridan states, “While many companies rely on more rules-based logic to classify feedback, NLP Logix uses several layers of NLP technology to dissect comments into meaningful units, extract relationships between words and phrases, and identify similar concepts that should belong to the same theme. This cutting-edge technology allows the model to grow and adapt to new concepts and without the need to manage large and complex rule sets.”

Utilizing comment themes and sentiment to identify opportunities to improve experiences, organizations can additionally track improvement progress after interventions have been put in place. For example, a key initiative for many industries is to ensure that organization leaders are providing all the information and education needed for customers to continue the proper course for success. Utilizing NLP Logix’s custom solutions, organizations can track the percent of negative comments about the information and education they are receiving, and work to turn those into positive comments over time.

“The NLP Logix solution allow businesses to uncover growing trends in real-time before they become a larger issue,” states Sheridan. “Hearing multiple customers or employees discuss a similar topic in a negative light can help draw attention to issue before it has wider impact.” As organizations have become more astute at utilizing feedback/stories, expectations have evolved. NLP Logix enriched the current NLP comment analysis to enhance the following features:

  • Flexibility – NLP was geared to analyze feedback from a single type of story. Organizations want to learn from stories regardless of the context of how it is gathered.
  • Accuracy – Sentiment analysis and alerts can be trained for accuracy to avoid themes expected over time.
  • Relevancy – Some themes can become redundant while others may not appear granular enough to be actionable.
  • Agility – Making routine additions, and updates can be done with greater agility with model restructure.

To solve these challenges NLP Logix has created a specific model update driven by NLP techniques enabling:

  • Feedback to come from any customer, employee, and partner story
  • Enhanced accuracy of theme and sentiment assignment
  • Theme pairs to improve the relevancy
  • AI-guided themes to increase agility

To learn more about Natural Language Processing and how to enhance your customer’s experience,  contact our team today.