How to Analyze Buyers’ Sentiments of Amazon Products Using Customer Review Insights?

how-to-analyze-buyers-sentiments-of-amazon-products-using-customer-review-insights
Actionable perceptions from Amazon reviews to make better decisions
In the past two decades, the internet has got a revolution in shopping experiences. Having nearly everything accessible online, the customers can just open the app, do some tapping and that’s it, the product will be delivered at the doorsteps!

Though, with hundreds of available options in different categories, this can be an intimidating task to search for every option as well as choose the finest one. Mostly, product reviews are differential when the time comes to make an important decision.

On the opposite, user reviews data is similarly important for businesses to predict and monitor trends, study consumer attitudes as well as create directed action plans.

With more than 10 years of experience in gathering product reviews across an extensive range of e-commerce websites & product categories, X-Byte Enterprise Crawling is the go-to solution for all the data acquisition requirements.

Motivation
Due to their larger inventory, better customer service, and user experience, Amazon is always the leading retailer in a lot of countries. The majority of their products are reviewed well, with several in tens of thousands.

Using Machine Learning as well as Language Processing methods, we’ve studied lots of Amazon reviews. Our objective is to know consumer sentiments and assist in better decision-making.

Data Collection
data-collection
For use cases, we have collected different reviews of exterior monitors from three top brands — Dell, HP as well as LG — in Amazon’s UK and US web stores.

Our dataset has incorporated 12 products from those three brands as well as the given data fields:

Product Details

ASIN
Brand
Price
Product’s Name
Seller
Reviews Details

Review Title
Complete Review Text
Helpful
Ratings
Review Date
Reviewer’s Name
Verified Purchase
After some rounds of QA (deduplication, removing null records, etc.), our last dataset included 10,786 records from which the first review was displayed in December 2014.

review-over-time
Top Brand Sharing with Similar Insights
top-brand-sharing-with-similar-insights
Dell, HP as well as LG are the three most reliable brands in computers as well as the electronic accessory industry. As anticipated with the leading makes, the highest ratings of 5.0 had maximum reviews with 7,168.

By breaking down the given chart, we can observe that these brands have received nearly similar reviews in numbers overall as well as for every rating.

review-by-brands
total-review-by-rating
These three brands had parallel average ratings also for monitoring on Amazon.

average-rating-by-brands
Depending purely on numbers, one could gather that all the three brands have roughly similar market share in Amazon as well as is also as trendy as the other two. Future buyers would need more drills on review content to make the last decision.

Analysis of Top Reviewed Products
analysis-of-top-reviewed-products
HP 23.8-Inch VH240a Full HD Monitor was the maximum-reviewed product in the dataset having 3,559 reviews. So, we’ve chosen that to do individual analysis. This monitor also had average ratings of 4.27.

top-review-by-product
100% Authenticated Purchases
For this selected monitor, nearly all the collected reviews were from authenticated purchases, imposing the quality of the dataset for more analysis.

verify-purchase-ratio
Average Quarterly Ratings over Time
The initial review for the HP VH240a monitor was given way back in July 2017. This achieved the maximum quarterly average ratings of 4.40 in the Q4 of 2019.

avg-ratio-over-time
The average ratings have been dropping since the all-time high that might be down to some factors like:

Better options either within the similar brand or the competitor

New technologies in the display panel hardware as well as power management, picture quality, etc.

Happy Customers’ Ratio of 87%
With nearly two-thirds of reviewers (2,352) providing 5 stars, it’s quite fair to indicate that overall, the customers were pleased with the purchase. Opposed to it, merely 12% of the clients rated a monitor unwell with ratings either 1-2 stars.

review-by-ratings
Reviews at Contrasting Ends of Scale More Useful
On Amazon, all the registered users can “like” the reviews to indicate that they got the details helpful. The “likes” count is a very good indicator about the type of data, which resonates with future customers as well as helps them to go with products in question or unrestraint it.

helpful-review-per
Depending on the review percentage, which was supposed to be “helpful”, as given in the above chart, it is quite clear that with any higher percentage of users available, the negative reviews prove to be the most useful during the buying procedure. The percentage got calculated as:

Total reviews, which were marked useful * 100 / Total number of reviews for the rating

Although, while thinking about the real number of “likes”, total reviews of two excesses (ratings of 5.0 as well as 1.0) look to be most useful.

helpful-review-by-ratings
Review Lengths
Depending on the analysis, we have found that the users have provided reviews of comparable lengths for every rating — about 350 to 400 words on an average. It suggests that, despite the observed product sentiment, the customers look to be equally descriptive about the experiences on reviews. It might be due to a fact that these monitors are a “well-versed buying product”, for which detailed data could be shared on the review.

Having seen that, there is a small increase in average lengths of reviews with every rating.

review-lenght-rating
Speakers, as well as audio quality, govern the customer opinions

common-mention
Depending on a word cloud produced for good reviews, the customers are usually “happy” with the “quality” of the purchase, having “speakers”, “screen”, “sound”, as well as “picture” regularly mentioned. Customers also look to like monitors for “office”, “home”, and “gaming” objectives, as well as are ready to “suggest” that to the contacts.

bad-review
Instead, dissatisfied customers look to be getting “problems” with “power”, “sound”, “cable”, as well as might “return” that.

As “speakers” featuring conspicuously in both the review groups, we could conclude that it is the feature, which is separating customers.

It was only a hint into the type of actionable analysis, which is possible with quality data, which X-Byte Enterprise Crawling offers. Analysts can do more thorough sentimental analysis for scraping extra insights from in-house or competitive review data that can be essential in driving well-versed product development decisions.

About X-Byte Enterprise Crawling
X-Byte Enterprise Crawling is the Web Data Scraping platform specialized in the withdrawal of web data from nearly all industry divisions. Contact us with all your requirements, and we provide a solution just for you.