The picture above depicts Paul McCartney wearing a mullet. This article criticizes word clouds, the mullets of the Internet. :-)
“Every time I see a word cloud presented as insight,
I die a little inside”
J. Harris, data journalist
If you are a manager, there is a high chance that you’ve encountered word
When it comes to making sense of data, getting actionable insights is the holy grail. But what does this even mean? When is a finding an insight? When is an insight actionable? Can data analysis deliver them? Let's get to the bottom of this by looking at some examples.
What is Natural Language Processing, or NLP in short? If you're unsure, you're not alone. Many people don’t know much about this fascinating technology, and yet we all use it daily. In fact, if you are reading this, you have used NLP today without realizing it.
Understanding customer comments, on a large scale, needs to be automated. So, it requires Natural Language Processing (NLP) or Text Analytics. Unfortunately, most open-source NLP tools were developed on text researchers have easy access to. These are typically news articles, research papers and movie reviews. I learned that the analysis
Have you thought of using text analytics for surveys? If you ever had to read hundreds of customer responses to open-ended questions, you probably did! We get it! Coding open-ended questions is a tedious task. Word clouds are an easy but poor alternative.
There were many reasons why I was looking forward to the Customer Experience Asia Summit in Singapore. And I won't lie, one of them was the fact that it took place at the famous Marina Bay Sands!
Recently I had an interesting discussion with Ron Stroeven, one the founders of Infotools, about open-enders, short for open-ended questions. In 1990 Infotools was established, but Ron has worked in market research far longer than that. He has a wealth of experience in survey design and data analysis, so it
Four people and several automated solutions were tested on a task of coding open-ended questions in a Net Promoter Score (NPS) survey. Their task: figure out the five key reasons behind an NPS survey and the five areas that could be improved. Here, we compare their performance using an academic metric of
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.
They collect scores into pretty dashboards, but don’t actually tell what the feedback is or how to achieve customer loyalty. Customer feedback analysis tools are all the rage, but most of them suck.
If you ever left a review yourself, you will know that your score is not nearly as valuable