Text Analytics

Unleash the Power of Your Customers’ Voice


Text Analytics

Emotion, sarcasm, and slang. These are just a few of the complexities of language that make text analytics so complicated. So when you ask a computer to understand and analyse speech—across multiple languages—it’s difficult to capture every nuance.

Identify Critical Issues in Real Time

From real-time anomaly detection and root cause analysis to data exploration and understanding trends, text analytics are at the core of everything we do—so you’re empowered to take the right action at the right time.

Finding the Perfect Balance

With text analytics, there is a balance between time, expense, and accuracy. Different models and methodologies will have varying impacts on your business, so it’s important to determine which approach best fits your priorities. We’ve built our text analytics engine to simply work from the day you turn it on—with intelligence that gets smarter over time—so you can feel confident when you take action.


Custom Models Without the Time or Expense

Accurately assigning tags and themes helps you understand emerging trends in written text, whether it’s reviews, feedback, or call transcripts. When it comes to tagging models, you typically have two choices:

  • Industry Models work well if your business fits neatly into a single industry or category; but they tend to miss brand-specific insights
  • Custom Models are more accurate, but are expensive and time-consuming to build and maintain because they require constant re-tuning

That’s why we offer the best of both worlds. Our Custom Layered Models allow you to choose and run multiple highly tuned industry models simultaneously. This means you get a custom and accurate model out-of-the-box which can be tweaked over time to align with your company’s specific lexicon.

Machine Learning Sentiment

Decipher and Decode Emotion, Sentiment, and Intent

When you understand the difference between a minor nuisance and a major issue that puts customer loyalty and revenue at risk, you can identify—and replicate—the types of experiences that elicit unbridled joy and increase customer retention and spend. Enter InMoment’s Adaptive Sentiment Engine.

Rules-Based Sentiment

  • Based on rigid rules
  • Requires manual intervention
  • Accuracy never improves without continuous manual updates

Adaptive Sentiment Engine

  • AI-driven—gets smarter over time
  • Accuracy continually improves
  • Ability to recognise new terms and phrases

Since switching from a rules-based model to InMoment’s Adaptive Sentiment Engine, we’ve seen a significant uptick in sentiment tagging accuracy.

Tyler Saxey, Director of Customer Experience, Footlocker

Our AI-driven Adaptive Sentiment Engine gets smarter and therefore more accurate over time, boasting the ability to correctly determine the sentiment of new terms and phrases as they enter the customer vocabulary—so you never miss a trend.

Native Language Text Analytics

Native Language When You Need It

In 99.9% of cases, machine translation for text analytics will get you the accuracy you need. However, some programmes may benefit from using native language libraries that help capture the sometimes critical cultural nuances that can be lost in translation. Fully featured native language text analytics help you accurately identify trends and opportunities in large amounts of data.

Active Listening™

Drive Intelligent Conversations

Without additional encouragement, qualitative feedback can be short and incomplete. Active Listening™ is the only AI-powered conversational feedback bot that uses text analytics to listen, understand, and respond to customers in real time, eliciting not only more, but more valuable responses.

Change Region

North America
United States/Canada (English)
DACH (Deutsch) United Kingdom (English) France (français) Italy (Italian)
Asia Pacific
Australia (English) New Zealand (English) Singapore (English)