When we conduct research, need to explain changes in metrics or understand people's opinions, we always turn to qualitative data. Qualitative data is typically generated through: * Interview transcripts * Surveys with open-ended questions * Contact center transcripts * Texts and documents * Audio and video recordings * Observational notes Compared to quantitative data, which captures
Become a qualitative theming pro! Creating a perfect code frame is hard, but thematic analysis software makes the process much easier.
At Thematic, we have a dedicated research team that is always innovating to bring you the most accurate sentiment and thematic analysis. Solving this difficult task requires in-depth understanding of both the problem of customer feedback analysis and the relevant advances in technology. This article is a glimpse into one
Most likely, you landed in this blog because you have too much feedback to analyze. You sent out a survey or collected reviews or other form of free-text feedback. Now that you have this feedback in-hand, what do you do with it? How can you identify common themes in responses?
What is sentiment analysis? If we take your customer feedback as an example, sentiment analysis (a form of text analytics) measures the attitude of the customer towards the aspects of a service or product which they describe in text. This typically involves taking a piece of text, whether it’s
I wanted to share with you my learnings from when our team at Thematic organized and sponsored a free 3-hour workshop on Deep Learning for Sentiment Analysis, run byDr. Felipe Bravo-Marquez [https://www.cs.waikato.ac.nz/~fbravoma/]. The workshop booked out within 24hrs of announcing it and more than
Have you wondered what customer sentiment analysis really is? Let’s get to the bottom of it. But first, let’s set some context. Customers are looking for positive experiences. Brands do too! “People will forget what you said, people will forget what you did, but people will never forget
Most people believe that text analytics solutions fail because sarcasm in customer feedback is very common. Somebody writes “Great service, yeah right!” and the dumb algorithm tags it as positive. So, whenever I speak on text analytics, someone in the audience will always ask: But how do you deal with
According to Bruce Temkin’s 2016 study, after a positive emotional experience, customers are 15 times more likely to recommend a company. 15 times more likely! That’s a huge difference. Not surprisingly, emotion analysis is receiving a lot of buzz. But do the current solutions deliver on the key
In July 2016, I was fortunate enough to speak at the Sentiment Analysis Symposium in New York. It is one of the most important events for those who invent text analytics solutions and for those who use them. I also attended the co-located sentiment analysis tutorial run by Jason Baldridge.