Sentiment analysis is a popular and telling research method. This is especially true in the age of digital media where consumer opinions are everywhere, but not organized.
As a quick review, sentiment analysis is the process of using AI automation technology to understand the overall emotional tone behind a group of words.
For example, you may want to know the overall opinions, attitudes, and emotions expressed by a large group of consumers. Accomplishing this successfully, using sentiment analysis, involves three major parts:
- Understanding where customers go to express their opinions (e.g. social media, online reviews, online communities, direct feedback, etc.).
- Using AI technology to conduct a data pull for large amounts of consumer opinion data, instead of trying to make inferences from only a few batches of text data.
- Analysing data to assign an overall positive or negative value to consumer expressions.
When can researchers use sentiment analysis?
There are several uses for sentiment analysis in the research process. You can use sentiment analysis to understand customer satisfaction levels to see whether or not you need to make adjustments to your customer service practices.
You can use it to understand product feedback. This helps you identify what products are well-received and which are not.
And, you can employ sentiment analysis to get an idea of how customers perceive your brand to improve your marketing efforts.
A closer look at sentiment analysis in practice
To get a better understanding of how to use sentiment analysis, let’s take a deeper look at a successful study published on researchgate.
Researchers used sentiment analysis as a social media monitoring tool to gain an overview of the wider public opinion of top automotive brands. The purpose was to determine which automotive brands held the highest, and lowest, public opinions, based on Twitter feedback.
The researchers chose Twitter as the best place to aggregate customer opinions based on high engagement rates. According to the 2014 CMO council report, 23% of car buyers have discussed other users’ experiences and reviews before purchasing. And, 38% of car buyers said that they will use social media in the next purchase.
After collecting 3,000 Tweets, researchers employed sentiment analysis to understand the polarity of consumer emotion from brand-to-brand.
What were the results? Researchers found the following:
- Audi had the most positive tweets at 83%, followed by Mercedes at 79%, and BMW at 72%.
- BMW had 8% negative polarity compared to 18% for Mercedes and 16% for Audi.
What does this mean? Audi customers were reporting the highest customer satisfaction levels.
How to get started with sentiment analysis
Sentiment analysis is technical, but it also can be an easy solution to understand customer opinions. That is, it can be easy if your market research team uses a smart technology that automates most of the process.
The best place to start is to try a market research tool that will allow you to experiment with an online demo of the tool. Many tools will allow you to type in a message and test the results of the analysis. This will give you a good idea of how the tool works and how it will fit in with your current market research practices.
Remember, when you’re looking to truly understand the overall sentiment of your customers, sentiment analysis is the perfect tool. Select a digital platform with high engagement for your industry, and you can rest assured you have a strong sample.
The results of your analysis will tell you what you need to change in regards to your customer service practices, marketing efforts, or products.