What is Sentiment Analysis Using Product Review Data
There is no doubt product reviews contain a whole lot of information – from what consumers liked (or didn’t like) about the product, to favorite features, and even how it compares to the competition. Containing valuable consumer insights, this feedback data gold mine is all you need to elevate your Sentiment Analysis to the next level.
In this article we’ll explain what Product Reviews Sentiment Analysis is, how to collect reviews, and how to analyze them so you get quality actionable insights that’ll push your brand forward.
Tapping into product review data enables brands to make data-driven strategic decisions, basing their goals and objectives on an accurate understanding of consumer wants needs, and experiences.
In order to extract those valuable consumer insights, most brands use sentiment analysis. Applying this text analysis tool to product reviews is the best way to learn what customers like and dislike about your product. In addition, you’ll be able to compare your product to the competitors and extract valuable actionable insights. All this information will help you to improve customer experience and product development, boosting sales and earnings.
How To Collect Product Reviews
Product reviews are absolutely everywhere! From Shopify and Yelp to Amazon, Walmart, and Google Play. So, collecting all that data manually is virtually impossible. Especially if you have new customer reviews appearing every minute.
Luckily, we’ve got Web Scraping. Also known as Data scraping, Web scraping is an automated data extraction and gathering from multiple sources into one place. This automated simultaneous process makes collecting product reviews a lot more effective, efficient, and affordable.
How To Analyze Product Reviews
Now that you know how to collect product reviews, let’s talk about how to analyze them.
First and foremost, use a sentiment analysis tool that will allow you to automatically analyze product reviews and separate them into categories – Positive, Neutral, or Negative.
After categorizing the feedback, make sure to identify trending topics discussed and mentioned in product reviews. Moreover, you should pay attention to the sentiment associated with the topics, be it positive or negative. It’ll help you identify trends, consumer pain points, and even market gaps you can leverage to your advantage.
Additionally, pay attention to Volume. The amount of reviews posted tells you a lot about the success of a new marketing campaign or dissatisfaction with a newly added feature. It’s also a good indication of the popularity of certain products, allowing you to detect trends and shifts in the market.
Last but not least, think about repetition. If a topic, either with positive or negative sentiment, keeps coming up in product reviews, it requires your attention. A repeating issue is a strong indicator of product bugs that need to be prioritized, or you risk consumers ditching your product.
How To Extract The Sentiment Analysis From Your Product
But how exactly do you extract sentiment from product reviews? We’ll that is where our dashboard can help!
Here is how you can use the Revuze dashboard to extract product sentiment:
- Login to dashboard → Products → Choose desired products → Apply Filter
- Go to “Topics” and extract the top liked, disliked, most trending topics with negative sentiment and positive sentiment.
- Select a topic and extract the keywords with the strongest positive / negative sentiment.
- Go to comparison and see how your product compares to the competition
You are able to compare products by source review volume, positive sentiment rates, or even by topics and star ratings.
Sentiment analysis using product review data is a great way to get to know your customers. Collecting and analyzing consumer feedback enables you to understand what people like and dislike about your product, what they are missing, and how your brand is measuring up to the competition.
Revuze provides you with the tool you need to collect, analyze, and understand consumer product reviews.
Revuze’s innovative AI technology collects real-time product reviews, providing accurate and relevant data for analysis. Our self-learning algorithms scan and analyze the data, identifying customer sentiment, detecting trending topics, and flagging consumer pain points.
The end result is a highly granular product review sentiment analysis, ready to help you make data-driven decisions that will elevate your brand to a whole new level.
Simone Somekh is a New York-based writer and editor who specializes in marketing and communications for B2B SaaS companies. He teaches Communications at Touro College and he is the author of an award-winning novel published in four languages.