Amazon Review Analyzer
Analyze reviews to find sentiment, themes, and key pros and cons. Get a clear summary to improve products and listings.
Paste an Amazon product URL. The system will fetch reviews and generate a detailed review analysis report.
Scrape hundreds of webpages in one click with the Thunderbit Chrome Extension. Prefer to hand this job to AI? Use the Thunderbit API or Thunderbit MCP. Want us to run it for you? Use our Web Scraping Service.
Extract Amazon Review Data FasterUse Thunderbit to scrape reviews and product pages with AI, then extract structured fields in a couple of clicks. Automate collection across listings and export to Sheets, Airtable, or Notion.
Install fromChrome Web Store
Extract Amazon Review Data Faster
Collect review text, ratings, dates, and product details from Amazon pages and related subpages using Thunderbitâs AI web scraper. Extract structured tables, categorize feedback themes, and format outputs for analysis without writing code.
Scrape across pagination, pull supporting files from PDFs or docs when needed, and capture images for reference. Export results to Google Sheets, Airtable, or Notion to share with your team and track changes over time.
How to Analyze Amazon Reviews Using Thunderbit
STEP 1Download and InstallDownload and install the Thunderbit Chrome Extension from the Thunderbit Chrome Extension Download Page. Once installed, log in or create a free account to get started.
STEP 2Open ExtensionOpen the Amazon product page you want to evaluate, or prepare your review data as a CSV file or pasted text. Click the Thunderbit extension icon in Chrome, then open the Amazon Review Analyzer. Choose one input method: (1) Analyze an Amazon Product URL and paste the ASIN page link, (2) Upload a CSV of Reviews and upload one CSV file, or (3) Paste Raw Review Texts with one review per line. Set optional parameters such as the maximum number of reviews, a review date range, and star rating filters.
STEP 3Click the Analyze reviews ButtonClick the "Analyze reviews" button to run the analysis. Thunderbit will process the provided reviews and return a structured report with overall sentiment, sentiment breakdown, top pros and cons, keyword trends, recurring issues, customer suggestions, and representative quotes. After the report is generated, copy the results into your documentation, or export and save them in your preferred workflow such as Google Sheets, Notion, Airtable, or a local file.
Learn how to analyze Amazon product reviews for sentiment, themes, and recurring issues
Analyze reviews from an Amazon product URL
Paste an Amazon product URL and choose how many reviews to analyze, plus optional filters like date range and star ratings. The Amazon Review Analyzer turns unstructured review text into a structured report with overall sentiment, top pros and cons, and recurring issues. It is built for Amazon sellers, ecommerce operators, and product teams who need a fast way to understand customer feedback without reading hundreds of reviews.
Process review text from CSV uploads or pasted notes
Upload a CSV of reviews or paste raw review text to analyze feedback you already have from exports, support tickets, or research docs. If your file includes rating and date columns, you can apply the same filters to focus on specific segments. This helps teams compare feedback across time periods, product variants, or star-rating bands, while keeping the analysis consistent across different data sources.
Turn feedback into a seller-ready summary report
Get a concise report that includes overall sentiment, a sentiment breakdown, frequently mentioned pros and cons, keyword trends, recurring defects with severity, and customer suggestions. The output is designed to be easy to share with stakeholders, turning scattered comments into clear themes. It also includes representative quotes so you can validate the findings and use real customer language in listings, FAQs, and support responses.
Use insights to improve listings, product quality, and roadmap decisions
Use the findings to prioritize fixes and messaging updates: address repeated complaints, clarify expectations in the product page, and highlight the benefits customers mention most. Ecommerce teams can monitor shifts by filtering recent reviews, while product teams can track defect patterns and feature requests. Agencies and marketers can use the pros, cons, and quotes to shape positioning, ad angles, and competitive comparisons.
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What users say about Thunderbit
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated resultsâno coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no codingâjust usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpagesâperfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. Itâs fast, flexible, and doesnât need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbitâs AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated resultsâno coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no codingâjust usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpagesâperfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. Itâs fast, flexible, and doesnât need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbitâs AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
