In the past, e-commerce operators and product managers always needed to analyze tens of thousands of Amazon reviews one by one to understand consumer thoughts, innovate, and iterate products. Analyzing a single product would take months. Now, VOC.AI VOC is born to solve this complex scenario.

You only need to search, select, enter the product you want to know about, and you can analyze tens of thousands of Amazon customer original reviews with one click. In just a few minutes , a professional insight report with 14 modules including consumer profiles, product strengths and weaknesses analysis, competitive analysis, star rating impact analysis, AI topic analysis, and more will be presented before your eyes. The report comes with AI comprehensive recommendations, providing you with more efficient, comprehensive product selection and optimization suggestions, helping your business enhance market competitiveness.

🥳 Follow the guide to start creating your report~

1.How to create a report?

VOC supports creating consumer insight reports in various forms.

1. Create reports through plugins.

Before creating the report, you need to install the VOC.AI plugin, see ➡️ VOC.AI plugin installation and usage instructions.

On Amazon’s search results page, ranking page, and product details page, you can quickly find the VOC.AI plugin’s “Add” button to quickly create reports to the web version. -> Search results page

-> Amazon ranking page

-> Product details page

2. Create a report through the web version

You can access ➡️ VOC web versionfor creation.

【Method 1】Search box search to create a report Support searching category words, brand words, single Asin to quickly create reports on the web version (for multiple Asins, please refer to method 2. Add by creating a button)

VOC.AI supports you to customize sorting and filtering when selecting products.

【Method 2】Creating a button to create a report Enter the report name (not the Asin you want to see), select the corresponding site; enter or upload the Asin file (when entering multiple Asins, pay attention to the format).

➡️ Tips:

Currently creating reports using nearly two years of full comment data (more than 100 displayed by Amazon). When building a report, you need to select the corresponding site, which defaults to the site selected last time. Non-English report content output needs to be translated. Please wait patiently as it may take a little longer.

2. How to view and analyze

➡️ Little tip:

If you’re entering the market now, but I don’t understand the users; let alone what they’re thinking.

If you want to create explosive products, but I don’t know the pain points; you can’t compete with differentiation. I’m happy to help with the translation! Here it is: “

If you want to start production for the market, but I dare not stock up, let alone know which one will sell well.

Using VOC.AI, seeing thousands of items at once is fast, viewing a wide range from competitors to various categories; seeing in three dimensions, from consumers to product modules.

1. Product List.

Click on the edit on the far right of the analysis report item to enter the product list page. This page provides all the product information analyzed in the current report. You can add or delete products on the product list page to update the scope of the report analysis.

Note: On this page, variant collapsing will occur, if the Asin you upload is under the same parent Asin, the parent Asin and variant quantity will be displayed. Translation: “Translation feature: The checkbox to the left of the translation text on the interface can translate each module to the system language currently set. Download function: You can download the current extracted tag situation, including mention times, percentage, *explanation, *positive and negative direction.

2. User Profile and Usage Scenarios

Transferring the portrait of domestic customers to overseas is difficult; conducting surveys across language styles is unrealistic.

VOC.AI now analyzes who the current consumers of the product are, when, where, and how they use the current product through self-developed algorithm models.

If you need to stock up one day, check out the demographics and timing with VOC.AI first; for poorly selling items and seasons, let’s stock less and reduce inventory to prevent risks~

Consumer profiles include: person characteristics, usage moments, usage locations, behavior.

Data is sourced from all reviews that add Asin to the current report; the AI intelligent model of this module will first identify relevant reviews before extracting them.

For example: my child uses airpods every day when running in the gym, then it will extract child, daily, fitness venue, exercise; VOC.AI’s exclusive algorithm will automatically summarize statistics.

From the chart, you can see the number of each tag. The red and green colors divided by 0 represent the user’s sentiment; green indicates satisfaction, red indicates dissatisfaction. Click to view the analysis for further insights, which will lead to the details of that tag: trend chart – mentioning quantity by month, mentioning product situation – which product mentions this tag more (can also switch to the most in terms of proportion, positive, negative), view corresponding original voice – consumer authentic expressions (each original voice comes with AI smart tags).

In scenarios where mentions are counted, an example interpretation of the scene will be provided (solely as an explanation of the left label, not indicating that it only contains or fully contains the following situations). Data is sourced from all comments adding Asin in the current report; the AI intelligent model of this module will first identify relevant comments and then extract them. For example, when I tried to listen to a song with these headphones, I could only hear the sound of the instruments, and the vocals were not there. It will then extract the scene of listening to music, and the VOC.AI exclusive algorithm will automatically summarize statistics; not missing any possible situations.

From the chart, you can see the number of each tag (currently showing Top 10), the proportion of which is the number of that tag divided by the total number of tags extracted from comments in the report; those outside the Top 10 can be downloaded via the download button. (Currently, a maximum of 30 can be downloaded, less than 30 will be downloaded according to the actual quantity) Clicking on the tag allows for drilling down, meaning jumping to the tag details: trend chart – by monthly mention quantity, mention of product situation – which product mentions this tag more (can also switch to the most proportionate, positive, negative situation), view corresponding original sound – consumer authentic expressions (each original sound comes with AI smart tags).

Example: For instance, Anker product managers discovered an increase in the Travel scenario by using scenarios, so they made the power bank more portable; considering the Listing page design highlights the portable atmosphere while traveling.

3. Star Monitoring

Insight into so many valuable points but not knowing which one is more important to consumers, one’s own intuition and experience are often a matter of luck, especially in unknown industries; in marketing, it’s about who can first meet the points consumers care about the most.

Now, VOC.AI Intelligence obtains and combines star ratings from facts to come up with proportions, allowing you to directly access the most current needs; by designing their products to dominate the market first, sales will naturally follow, right?

The star impact degree is composed of four quadrants separated by two axes, with the horizontal axis corresponding to the star rating and the vertical axis corresponding to the mention frequency (percentage).

Data is derived from all reviews of Asin added in the current report, and the AI intelligent model of this module will extract corresponding tags (consumer focus points). Starting from the top left quadrant, this represents the user’s most mentioned and lower-rated focus points in the current report, while the bottom left quadrant is for less mentioned but lower-rated focus points; both of these quadrants require close attention to prevent similar situations and reduce ratings. The bottom right quadrant is for less mentioned but higher-rated focus points, and the top right quadrant is for more mentioned and higher-rated focus points; these two quadrants also need close attention to seek iterative corresponding designs to improve ratings.

From the chart, you can see various labels, with their positions indicating their corresponding ratings and mentions; red and green colors represent the user’s sentiment, with red indicating dissatisfaction. When the mouse is placed on that focal point, you can see its corresponding average rating and percentage (count); the percentage is the focal point divided by the total number of positive or negative focal points. Click to view analysis for further drilling down, i.e., navigate to the details of that tag: trend chart – by monthly mention count, mention of product situation – which product mentions this tag more (can also switch to the most proportionate, positive, negative situations), view corresponding original voice – consumer authentic expressions (each original voice comes with AI smart tags).

Example: For instance, Anker product managers discovered through star rating monitoring that factors affecting star ratings and high mentions include poor fit and low battery capacity. Therefore, they improved the earphones to have a better fit and larger battery capacity in research and development; the design of the listing page also highlights these two features.

4. Product strengths and weaknesses

The more mature the category competition becomes, the more intense it is. In order to occupy more market share, there are continuous occurrences of homogenization, price wars, and blind improvements. It seems that the good sales of his products cannot be just superficial; directly observe the real experience of his users; extract the essence and find opportunities to surpass. Now VOC.AI has effectively revealed the reasons for its success to you. Targeted iterations or avoidance, explosive models can be traced and are just around the corner~

The product experience department will tally the mentions, provide examples to interpret the viewpoint (solely as an explanation of the left label, not indicating it only includes or fully includes the following situations). Data is sourced from all reviews of Asin added to the current report; the AI intelligent model of this module will first identify relevant comments before extracting them. For example: I have only used it for 4 months, but the right earbud is already damaged; it doesn’t work properly. It will then extract the poor durability of this product experience. VOC.AI’s exclusive algorithm will automatically summarize statistics; not missing any possible scenarios.

Clicking on the tag allows for drilling down, meaning jumping to the tag details: trend chart – by monthly mention quantity, mention of product situation – which product mentions this tag more (can also switch to the most proportionate, positive, negative situation), view corresponding original sound – consumer authentic expressions (each original sound comes with AI smart tags).

Case: For example, Anker product managers gain insights into a certain headphone product’s focus on dissatisfaction with fit and comfort through product experience. In this case, the design can be optimized; considering different sizes of earplugs to prevent the poor experience of high-frequency dropping.

5. Purchase Motivation

Most users are happy to share the joy of finding good products, and their genuine thoughts when they want to make a purchase are no longer a secret; to obtain and consistently guide more users towards making this purchase.

VOC.AI now implements a method to identify its underlying driving force, you just need to continuously provide services that match it~ The motivation for purchase will be statistically mentioned, examples will be given to interpret the viewpoint (only as an explanation of the left label, not indicating that it only contains or fully contains the following situations). Data comes from all reviews of Asin added in the current report; the AI intelligent model of this module will first identify relevant comments and then extract them. For example: I am very satisfied with them, they are easy to set up and start using immediately; I highly recommend these headphones. It will then extract the motivation for easy use of this purchase, VOC.AI’s exclusive algorithm will automatically summarize statistics; not missing any possible situations.

Example: For instance, Anker product managers have insight into the motivation behind purchasing a certain headphone product, where customers are particularly concerned about warranty services and charging methods. By providing corresponding services, implementing moderate and effective free replacements, and so on, they can drive greater purchasing motivation for users.

6. User Expectations

When a group of users starts to become dissatisfied, it represents new opportunities. Insight into trends earlier can help prioritize product layout. Consumers often express needs more clearly. VOC.AI now monitors the ability to represent emerging opportunities. You just need to grasp the trend and correspond it to the design. Users expect to mention situations, interpret the viewpoint with examples (only as an explanation of the left label, not indicating that it only contains or fully contains the following situations). Data comes from all reviews of Asin added to the current report; the AI intelligent model of this module will first identify relevant reviews and then extract them. For example: $20 headphones are great, but I want better noise cancellation for these $100 ones. It will then extract the user’s expectation of noise cancellation. VOC.AI’s exclusive algorithm will automatically summarize statistics; not missing any possible situations.

Click on the tag to drill down, i.e., jump to the tag details: trend chart – by month mention quantity, mention product situation – which product mentions this tag more (can also switch to the most proportionate, positive, negative situation), view corresponding original sound – consumer real expressions (each original sound comes with AI smart tags)

Example: For instance, Anker product managers have insight into user expectations that a certain headphone product does not meet the needs for noise cancellation and comfort. They can make targeted improvements to achieve faster iterations for noise cancellation and comfort to meet users’ real needs.

7. Original Comment

Amazon limits visibility to 100 reviews, so you won’t find a tool on the market that shows all reviews for the current Asin. VOC.AI supports filtering and searching, viewing only images, and each comment also has corresponding consumer focus points extracted by AI (including those generated by the AI tag tool). You can enter keywords in the search box of other filters to locate the original text containing that word (cannot search tags, click to drill down on tags in the insight module), support selecting only image comments, filtering corresponding comments by star rating or time. It also supports reverse sorting by the number of likes and downloading the currently selected comments.

3.Competitive Analysis

1. Web Version “Competitive Analysis”

Know yourself and know your enemy, and you will never be defeated in a hundred battles. VOC.AI VOC supports comparing products in various aspects such as basic information, user profiles, product strengths and weaknesses, user expectations, etc., to fully understand the strengths and weaknesses between oneself and competitors.

Please provide the text you’d like me to translate!

2. Competitive Analysis in the Report

In any report, select the competitive analysis module, and the system will automatically collect the top 3 products in that product category for comparison.

If the default comparison content does not meet your analysis needs, you can always compare products by clicking “Reset s

lect” on the right side.

4. AI Listing Optimization

1. How to optimize AI Listing?

By combining exclusive high-accuracy review analysis to optimize listing key content, including recent product VOC performance, top category keywords, etc., it helps increase listing exposure and conversion rates, boosting overall sales. Access the VOC.AI web version to find the entrance to “Optimize Copy” from “Amazon Review Analysis”.

Click to enter, you need to manually select the product site and enter a product Asin to

The system will automatically quickly obtain the seller’s comment analysis keywords, search terms, and competitive best-selling keywords of the top products in that category.

The system will automatically help check the most worthy keywords to be optimized in the copy, and you can also choose them independently or fill in the keywords prepared in advance in the input box below. After clicking the one-click optimization, VOC.AI AI will automatically optimize the listing copy that best fits local language habits, is more attractive, and impresses consumers.

The optimized results will be displayed on the right and support one-click copying. If you are not satisfied with the optimized structure, you can always return to the keyword editing page for re-optimization by clicking the button in the upper right corner. ➡️ Pro tip: Mentions and percentage: Number of comments mentioning the current topic / Number of comments analyzed by sampling. Search keywords: search terms and corresponding search volume for this subcategory in the past month. The key selling points of the premium core: Analyze the top 20 products in the subdivided categories to obtain key selling keywords and corresponding mention frequencies.

5.AI Topic Analysis

According to the prompt, enter any questions you want to know about, VOC.AI AI will automatically perform semantic analysis and recognition statistics, quickly summarize all relevant content, and understand in detail the issues and real feedback encountered by consumers in one step.

➡️ No need for manual reading and counting, analyze all comments with one click

No language barriers, easily analyze comments in multiple languages. Support feedback and inspection, improve label accuracy in real time.

Instructions for Use

In any web page report, find the entrance to AI topic analysis.

You will see the final effect after the custom topic settings are successful, enter the upper right corner to start setting.

According to the problem description prompt in the center of the page, enter the issue you want to know about in this report’s product; and categorize this issue so that after setting a large number of custom topics, it is easy to search, classify, and summarize the issues. After the problem and classification are determined, click on the right to start the analysis. VOC.AI AI will immediately conduct semantic analysis and recognition statistics on all comments in the report, and display below the relevant content extracted based on the problem description (up to 100 items).

Note: If the extracted content deviates significantly from the desired result, we suggest you modify the problem description in more detail and click on the right to reanalyze

➡️ Tip

How should the topic description be written? Please provide the text you would like me to translate following the specified rules.

☑️ Correct Demonstration: (Describe the specific issue and provide possible outcomes) The water flow pressure, how is it, too high/too low/just right? How are the dimensions, too large/too small/just right?