Net Promoter Score (NPS) surveys are one of the most common ways of knowing how customers perceive a product or service. Basically, they consist of two stages: first, you ask a customer to score a business from 0 to 10, then you ask them to give reasons for the score they leave with open-ended question.
When it comes to processing the results, the first stage is easy: you just have to calculate the average score. But when it comes to analyzing tons of open-ended NPS responses, the analysis becomes more complicated. Imagine if your team had to tag hundreds of responses manually. Not only it would be a tedious and time-consuming task, it may also lead to inconsistent results derived from different criteria during the tagging process.
Fortunately, sentiment analysis enables you to process large volumes of NPS responses and obtain consistent results in a very fast and simple way.
It might just be the industry I’m in, but I don’t really get excited about sentiment analysis. Still, don’t let my biases influence your thought process too much.