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Amazon Review Sentiment Analysis: A Comprehensive Guide

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Reviews are important for every business. Multiple verified and high-quality reviews improve consumer trust and conversions. 

But, the true value of reviews for sellers is the content: are buyers happy with your products? Do they prefer a competitor’s products? How can that change?

Amazon review sentiment analysis uncovers the emotions and trends behind your reviews–and competitors’ reviews. 

This article covers what Amazon review sentiment analysis is, how to conduct it, and how to turn those findings into the ultimate customer success.

What is Sentiment Analysis for Amazon Reviews?

Sentiment analysis uses natural language processing (NLP) to understand the feelings and opinions of customers leaving Amazon reviews. It automatically tags the unstructured data (customer words within reviews) so it can be processed quickly and efficiently. 

Sentiment analysis primarily focuses on polarity (the distribution of negative and positive reviews) and subjectivity (whether sentences are an opinion or facts). 

This can help organizations understand where and when customers are having a negative experience while using their product or service.  Businesses can see how their brand or specific products are trending over time. They can see if overall customer sentiment is becoming more positive, more negative, or staying steady. 

Sellers can also conduct sentiment analysis on competitor reviews for insight into what their competitors are doing right–or where they can beat them out. 

Why Do We Need AI for Amazon Review Analysis?

According to IBM, Artificial intelligence (AI) is: 

“A field which combines computer science and robust datasets, to enable problem-solving. It also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence. These disciplines are comprised of AI algorithms which seek to create expert systems which make predictions or classifications based on input data.”

Because user-generated content can come in at such large quantities (i.e. millions of different data points), it’s necessary to use artificial intelligence and machine learning (ML) to quickly analyze and pull insights. While marketing teams can manually look at a few reviews, analyzing multiple products with hundreds or thousands of reviews is only possible using AI and ML. 

Benefits of Conducting Sentiment Analysis on Amazon Reviews

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Sentiment analysis predicts and identifies customer trends in a fraction of the time that it takes humans. This can help sellers optimize listings, manage product issues, and get ahead of brand reputation–all before seeing a dip in sales. Let’s get more specific.

Better Understanding of Customers 

To save your business and the potential for ratings to affect the sales of your product, understanding your customers’ needs to happen quickly and accurately. This is only possible through sentiment analysis software that uses AI and ML technologies. 

More Complexity Than Star Ratings

While star ratings are helpful, they’re not very detailed. Your product could have an average of 4.3 stars, but that information only tells you that it can improve – not how it can improve. Sentiment analysis can determine specific customer pain points or product deficiencies. 

Competitive Insights

Amazon seller competitive analysis identifies and evaluates brands that sell comparable products and compete for a similar audience. You can conduct a general Amazon seller competitor analysis or tailor the method to look into specific aspects of your competitors’ business. 

Negative reviews can show you how to beat out your competition–but so can positive reviews. Uncover what customers love about your competitors’ products and see how you can update your product or product listings so you can match up.

However, this can be very time consuming. Luckily, Sellesta does this automatically. You can filter reviews by aspect and sentiment to see what customers are saying about any product on Amazon. The AI analyzes key tags and the emotional tone of key tags to break down what customers really think about your competitors’ products. 

Improved Customer Support

Review sentiment analysis helps teams customize their customer service and identify which customers need additional support. 

A customer might give a 3.5-star review not because they didn’t love the product, but because it arrived late. Sentiment analysis helps determine the real issues behind the customer experience–is it a product issue, a service issue, or something else? 

Solving customer issues quickly and effectively improves customer satisfaction and loyalty. 

Optimized Product Listings

This may seem obvious, but updating your listings based on the data from the ratings you receive can be essential to growing sales exponentially. 

Review analysis can also be used to uncover what your competitors are doing well–or where they’re falling short. Then you can use this data to improve your products or product listings. 

Brand Reputation Management 

Brand reputation is tied directly to customer loyalty. Understanding specific issues customers have either with your brand or product helps you drive improvements for increased profitability. 

There may also be overall market or societal shifts that impact how customers use or view your product. Review analysis can immediately uncover a change in customer sentiment, allowing you to react timely to customers’ changing needs. 

Product Enhancements

What are your customers looking for? Often, customer reviews mention what customers wish a product had or what could make it better. Use these valuable insights to improve your products and offerings. 

Or, if you have another product that solves these issues, try offering product bundles as an upsell opportunity. 

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How to Perform Sentiment Analysis on Amazon Reviews

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1. Use an Review Sentiment Analysis Tool

While sellers can manually analyze some reviews, true sentiment analysis will require AI-powered software. 

Rather than having to comb through reviews yourself, Sellesta uses sentiment analysis to uncover what customers really think about your products. By evaluating key tags and their emotional tone, you’ll gain a better understanding of what your customers love or dislike about your products. This feature also works on competitor products so you can see how you compare.

Additional Sellesta features include: 

  • List scoring: Our AI provides estimations of the performance of each of the main aspects of your listing. It will return a score on your product title, description, images, and review count so that you can present the best possible listing to shoppers on the Amazon marketplace.
  • Keyword search integrated with listing optimization: Sellesta’s all-in-one approach of combining keyword search with listing optimization allows sellers to maximize organic traffic to listings without having to switch between keyword and list optimization tools. With its help, you’ll be able to improve the listing title, bullets, and keywords to bring more shoppers to your product.
  • Competitive analysis: Sellesta automatically identifies direct and indirect competitors. Our interface also allows for easy tracking of their Best Sellers Rank, prices, ranking, and listing optimization score.
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2. Enter Your Product Listing 

Once you have chosen your seller tool, review analysis is easy. Simply enter your product listing in the data input section. This will typically be the URL for your listing as seen on the Amazon platform.

Once you provide the input, you’ll get the results of the analysis within minutes.

3. Review the Results 

Sentiment analysis tools make it easy to review your results. They’ll provide the analysis in easy-to-read charts and graphs. 

4. Implement the Findings

This is one of the most important steps of sentiment analysis. All this data is only helpful if you use it! 

Once you’ve sorted through your results, you can begin implementing the findings. This could include changing the language of your posts, getting ahead of customer service requests, and enhancing your products. 

5. Optimize Your Amazon Listing

It’s important to consistently optimize your Amazon listings to improve rankings. New products, shifting markets, and societal changes can all impact the success of your product listing. 

In addition to using the findings from your sentiment review analysis, take advantage of keyword research tools, listing optimizers, and other Amazon SEO best practices.

Conduct Amazon Review Sentiment Analysis with Sellesta

There are over three hundred million customers shopping on Amazon’s platform worldwide which makes navigating the space as a seller can be challenging. 

Fortunately, using Amazon seller tools like Sellesta makes it that much easier to conduct a sentiment analysis of your products and listings. Amazon review analysis helps you connect with your customers, improve your listings instantly with data-driven insights, and identify your competitors and their strategies–all the while maintaining your company’s brand reputation. 

Use Sellesta for your review sentiment analysis to learn how to scale your customer’s experience and get ahead of your competitors in a fraction of the time.

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