Evaluate the customer journey with InMoment's

Text Analytics

Overview

At InMoment, we collect over 275,000 customer experiences every day. This massive amount of data can be daunting, but through the use of text analytics, invaluable insights can be uncovered. Text analytics come into play at all stages of the process: During the feedback process, follow-up questions are asked based on previous customer comments. Comments are then analyzed to surface the most insights from your customer analytics data as possible.

We integrate our text analytics across our entire platform – from improving the customer feedback process, to surfacing insights, to powering real-time alerts and reports.

Our text analytics are:

  • Built on the IBM Watson Natural Language Processing engine
  • Highly-tuned to industry vocabularies
  • Calibrated to individual brand needs
  • Integrated across the Experience Hub
  • Precise, offering 90% accuracy

Why It Matters

As consumer expectations continue to rise, it is even more vital to tune in to what your customers are saying. A recent study shows that companies with just an average customer experience will see a decrease in customer recommendations and returning customers. On the other hand, a company providing “wow” level customer experiences can see a 30-50 percent increase in recommendations and returning customers.

Text analytics is a key component to monitoring your customers’ experiences and behavior. Smarter data allows you to make more informed decisions. Analytics software also provides a deeper understanding of WHY customers feel the way they do about your brand – in their own words.

InMoment text analytics helps to improve the act of receiving feedback as it ensures your customer’s voice is heard—making this an important part of the customer experience. Personalized questions give them the chance to share stories most relevant to them which will help you understand customer behavior better.

How We Apply Text Analytics

Other vendors only apply text analytics to the data they’ve already collected. InMoment takes a completely unique approach by also applying them during the customer feedback process itself through Active Listening.

Improving the Feedback Experience

Our use of text analytics in conjunction with branching logic gives access to previously untapped insights. Branching logic serves up questions based on the answer to the previous question. For example, if a customer rated their experience a 1 out of 10, the next question might be: "We’re sorry your experience did not live up to your expectations. Would you like a manager to contact you to help resolve your concern?"

In an open-ended question, a customer may mention your new product favorably. Text analysis tools will pick up on the name of product, while branching logic will lead to a question such as “Where did you hear about XYZ product?” This ensures that customers are being asked questions that are relevant to their customer journey.

Analyzing the Data

We apply text analytics to customer stories to surface important insights from the words of your customers. Through the use of linguistic-based text analytics we are able to offer greater insight and accuracy. We then channel these insights to the right people at the right time, via real-time alerts, reports, and dashboards.