What is Amazon Review Analytics? Amazon Review Analytics Review

What are Amazon reviews?

Amazon reviews refer to the written comments given by buyers on products. They are displayed on the Amazon listing page.

Amazon revamped the review section of Listings in 2019, changing it from reviews to ratings.

Amazon buyers are allowed to give corresponding star ratings directly without writing reviews. This adjustment can reduce the time buyers need to spend on leaving reviews and increase the chances of buyers leaving reviews to a certain extent.

However, ratings without text content will not be displayed on the listing details page. In addition to the overall rating of the listing, the only thing that consumers can see directly is the specific reviews, which will greatly affect the conversion rate of the listing. Therefore, review analysis is one of the essential research tasks for Amazon sellers in product selection and operation.

What is the role of review analysis?

1. Improve conversion rate

When buyers are looking at products, they usually look at the comments on the listing, just like when we buy things on Taobao, they read the reviews and the buyers’ posts. If their products have a lot of negative reviews, it will naturally be difficult to convert them. Then, they can compare their products with the reviews of competitors to see where the problems with their products are, and improve the direction of the reviews.

Track your own reviews and those of your competitors to see where the focus of user feedback is. Show the good side of your product as much as possible. When appropriate, you can add more reviews. When buyers see that the positive reviews are what they need, the chances of buying will increase greatly.

2. Product selection

The comments on the listing can provide a substantial reference for sellers to select products. Through the comments of buyers, sellers can know what buyers like and need, and know the advantages and disadvantages of the products, so that they can cater to the buyers' preferences when selecting products and develop potential hot-selling products that better meet market demand based on the needs and preferences of buyers.

The number of comments on the listing and the proportion of comments on each variant can also be used to estimate the sales volume of the listing and the sales volume of different variants. This can indirectly tell sellers which colors and models of the product are in high demand, and can help sellers select products and prepare stocks more specifically. Of course, because Amazon has the problem of brushing and cleaning reviews, this can only be used as a reference.

3. Optimize your listings

Buyers’ comments on products allow sellers to learn from these comments what buyers need and care about for the product. Sellers can use this information to optimize listings, focus on the parts that users like and care about, optimize product descriptions, five features, and product images, so that buyers can quickly understand the product and increase the listing keyword volume and ranking.

So how do you do review analysis? Next, let’s use a product as an example to demonstrate the analysis.

How to analyze?

Below we take B07MYWM2C6 as an example for analysis and explanation.

This is one of 344 variations of a creek shoe.

Click the [Comment Analysis] button on the product listing page to generate a comment analysis report with one click.

You can see that this product has a total of 3791 rantings, but there are only 641 reviews with actual content.

Click to enter the review analysis report to see the number of reviews for each variant and the percentage of reviews. Variants without reviews will not be displayed.

Generally speaking, the variants with higher sales have more reviews.

The product variant Size: 10 Women/9 Men | Color: Water Shoes-927grey has a high share of 52.8% of reviews.

This means that more than half of the sales of this listing come from this variant.

Rating star ratio:

This refers to the number of star ratings in the listing and its proportion in the total number of ratings.

The product has an average star rating of 4.5 points, of which 2,743 have 5-star ratings, accounting for 72.3%. The high rate of favorable comments indicates that the product itself is relatively mature and has fewer after-sales problems, but on the other hand, it also indicates that there is little room for improvement in the product itself.

If you have an independent supply chain and strong product development capabilities, then a high rate of negative reviews may actually be a good thing, as you can improve and upgrade your products and seize the market.

Review star statistics:

This refers to the number of reviews of each star in the listing and its proportion in the total number of reviews.

It can be seen that the number of 1-star negative reviews accounts for 6%, which is higher than the proportion of 1-star ratings (2.7%).

The comments will be displayed on the front page and seen by buyers, which directly affects the conversion rate of the listing. If the negative review rate is high, we can check the specific negative review content in the comment list to make targeted improvements.

Feature Rating:

The data comes from the By feature section of the Listing page. Check "Translate" to translate the feature words into Chinese.

When buyers rate products, the Amazon system will automatically give characteristic words based on the product category and invite buyers to give star ratings based on the product features.

Through this indicator, you can quickly understand the product characteristics and the score of each characteristic, and improve the product in a targeted manner.

For example, the lightness of this product is rated a full 5.0 points, but the comfort level is only 4.2 points, so there is still room for improvement in this aspect.

Comment type statistics:

Among the 641 reviews of this listing, 571 are VP reviews, 19 reviews have pictures, and there are no reviews with videos.

If you consider this product as a competitor, your conversion rate may be higher if you have a video review on your listing.

Comment model statistics:

Based on the number of reviews and the proportion of reviews for the variants, we can estimate the sales of different variants and help sellers select products and prepare stocks more specifically.

You can also switch the time dimension and model to view the recent distribution of reviews and adjust stocking requirements in a timely manner.

Variant review trend:

By choosing different variant models, you can determine the peak and off-peak seasons of the product by looking at the changing trends of the variant reviews.

Here we have chosen the variant with the most reviews, which generally means the corresponding sales volume will be the highest. It can be seen that there is a peak period for reviews in July every year, but reviews generally have a certain delay. It takes time for buyers to place an order, receive the goods, and then leave a review after trying the product.

Therefore, we infer that the annual sales peak of this product may start in June, so we will have a clear idea of ​​when to increase inventory and when to start promotions.

Comment list:

All comments on the listing will be translated into Chinese in real time, greatly reducing the reading cost. It supports filtering by star rating, comment type and other conditions, so you can quickly understand the product's selling points, shortcomings and usage scenarios.

Analyzing competitors' reviews helps to discover the quality of the product itself and the buyers' demands.

For example, if we filter out 1-star reviews, we can find that the main quality problem of the product may be caused by the upper material. If this is a product you want to make, you need to focus on this issue when selecting products.

Or filter out reviews from the last month. Because the product may be constantly improving, new reviews are more valuable for reference.

You can also analyze based on the high-frequency words in the comment tags. Click on a word to see all the comments containing that word.

For example, if we click on the keyword arch support, we can see that although the corresponding comments are all positive, there is actually a demand for the product to have more arch support. If this pain point can be solved, perhaps the sales of this type of product can be taken to a higher level.

Amazon reviews can provide a lot of value to sellers. Sellers can view these review information one by one on the Amazon front desk or copy and paste them into a table for manual statistics. However, the significance of the tool is to improve operational efficiency and help sellers achieve twice the result with half the effort.