Machine Learning Assisted Text Utterance Collection

How to improve the accuracy of your chatbot and give your customers the answers they’re really looking for.

In our increasingly on-demand society, it’s no secret that industry leaders are turning to chatbots to give the 24/7 service their customers expect. With 3x the engagement of emails, immediate response times and huge scalability, chatbots are the obvious customer service advantage. But how do you make your chatbot more accurate and ensure it gives the right answers to your customers?

If you’ve ever wondered, “why isn’t my chatbot giving the right answers?” chances are it hasn’t been trained enough. Chatbots are only as good as the training data they consume, and generating large amounts of high quality, varied text utterances for training can be difficult and time-consuming. Until now.

Figure Eight’s new Machine Learning Assisted (MLA) Text Utterance Collection optimizes utterance collection by using Machine Learning to filter out useless utterances using our three smart validators (duplicates, incoherence, different language) as soon as they’re collected.

With poor quality utterances out of the picture, your team can focus on generating high quality, usable chatbot data at scale, understanding the variety and nuances of how your customers ask questions – ensuring your chatbot is ready to give the right answer every time.

 

Here’s how it works

Every utterance submitted by contributors is checked for its accuracy and quality using the three smart validators. With poor quality utterances filtered out, your team can focus on only collecting high-quality, usable data at scale, ensuring your chatbot is trained to give a smooth and informative customer interaction every time.

 

Our smart validators leverage machine learning to improve the quality of collected data by using:

  • Duplicate Detection: Ensures only unique utterances are collected
  • Coherence Detection: Ensures coherent input
  • Language Detection: Ensures contributors are submitting using target language

Higher Quality

Validation ensure only high quality, usable data is collected, resulting in up to 35% reduction in rejected utterances

Greater Speed/Scale

Open your work to a larger crowd knowing every utterance is checked for quality on an enterprise-grade secure platform.

Reduced Cost

Eliminate peer reviews on utterances you can’t use, saving money and time

GET A 35% REDUCTION IN ERROR RATES FOR IMPROVED CHAT BOT RESULTS

READY TO BUILD YOUR MOST ACCURATE CHATBOT? SIGN UP FOR A FREE TRIAL TODAY.

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