Lumoa
JANUARY 23, 2018
This situation is where automated text analytics is brought in: it can help in sorting out the key topics talked about and reveal the general sentiment per topic. Text analytics helps in understanding the feedback. Careful and well implemented text analytics can easily reveal dozens of improvement ideas.
PeopleMetrics
JULY 31, 2018
The true “voice” of your customer is the unique words they share with you each time you ask them “Why” or “Please tell me more about that” in your survey. There is gold in each comment that customers share with you. Enter text analytics. Machines (Text Analytics). But first, let’s take a step back.
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Lumoa
JANUARY 8, 2024
And, if you’re nodding along, I’m also betting you’re savvy enough to know that the future of business success is tightly intertwined with embracing Machine Learning (ML) and Artificial Intelligence (AI). AI tools are changing the way we analyze customer feedback. .’ It’s a common goal, after all.
Lumoa
FEBRUARY 9, 2023
Actionability is also, as we believe, one of the essential aspects of customer experience management. The most important AI technologies, that are relevant for analyzing customer feedback, fall in the area of natural language processing (NLP) and machine learning. Why is NPS ® going up or down?
SurveySensum
NOVEMBER 11, 2021
SurveySensum is an AI-powered end-to-end customer experience management platform that facilitates SMEs and growth-stage businesses to act effectively on your feedback. . When you have too many customer personas and a huge audience pool, you need to manage it. Text Analytics. Text Analytics.
PeopleMetrics
JUNE 4, 2019
Those in B2C need to embrace the fact that they probably have more customer feedback than they know what to do with. However, the seemingly overwhelming volume of feedback allows B2C companies to learn more about customers and their experiences than ever before. TEXT ANALYTICS: N/A. VOLUME: Small.
Lumoa
APRIL 13, 2020
When you want to generate insights from voice data the first thing you need to do is to transcribe the audio into text. This can be done using voice-to-text analytics, also known as speech-to-text analytics. When the audio is transcribed you can treat the transcribed text as normal text feedback.
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