I started selling on Amazon while still in college. Got lucky early on: one of my first products took off and I made a decent chunk of money from that single listing. But when I tried to replicate that success, I quickly realized luck only gets you so far. Selling well consistently means understanding the market: competitor pricing, listing copy, keyword trends. To get that data consistently, I needed a way to scrape Amazon at scale.
But I can’t code. I didn’t want to learn Python or mess with scraping APIs either. Over the past few years, I’ve tested quite a few amazon scraper tools, from hiring freelancers to no-code browser extensions. In this post, I’ll share how to scrape Amazon product data without coding, the amazon product scraper tools that actually work, and some competitive analysis tips I’ve picked up as a seller. Whether you need an amazon price scraper for weekly monitoring, an amazon review scraper for bulk analysis, or an amazon keyword scraper for ranking visibility, I have tried a tool for each.
What I Tried (and Why Most of It Failed)
Hiring Freelancers to Scrape ($300/Month and Still Waiting)
My first attempt was hiring freelancers on Upwork to scrape Amazon data for me. If you search “python amazon scraper” or “amazon web scraper python” online, you will find dozens of freelancers offering this service.
The going rate was about $60 per scrape for 200 rows of data. That sounds manageable until you realize how often you need fresh data. I was scraping about 5 times a month (weekly price checks plus the occasional deeper pull), which put me at roughly $300/month just for data collection.
On top of that, the scripts would break every few weeks when Amazon changed its page structure. When that happened, the freelancer would charge extra to fix it. And because most of them were in different time zones, I would send a request on Monday morning and not get the data until Tuesday or Wednesday. By then, a competitor could have already undercut my price and I would not know.
I do not blame the freelancers. Amazon actively changes its page structure to break scrapers. But between the cost, the delays, and the constant back-and-forth, it was not a sustainable way to get competitive data.
Scraping APIs (Worked, But Not Independent)
After the freelancer experience, I started researching alternatives online. A lot of guides recommended using an amazon scraper api like Oxylabs and ScrapingBee. These are cloud services that handle proxies and anti-bot measures for you. You send them a URL, they return structured data. For anyone searching for the best amazon scraper api, these names come up constantly.
The concept sounded perfect, but there was a catch: connecting to these APIs still requires writing code. I asked a friend who knows programming to help me set it up, and the data quality was solid. Pricing ran $50-100/month for my volume, which was reasonable.
The problem was maintenance. Every few weeks something would break or need adjusting, and I would have to message my friend again to fix it. I felt bad constantly asking for favors, and waiting on someone else’s schedule to get my own competitive data was not much better than waiting on a freelancer. I needed something I could run entirely on my own.
The No-Code Scrapers I Actually Tested
After the API experience, I turned to no-code browser extensions. Every amazon scraper chrome extension I found let you extract data without writing code. Tools like Web Scraper, Instant Data Scraper, Bardeen, Octoparse, Thunderbit, and Chat4Data all work as browser-based amazon scraper software. Some use a point-and-click approach where you select page elements visually. Others use AI to detect or navigate pages for you.
The older point-and-click tools (Web Scraper, Instant Data Scraper) technically require no code, but you still need to understand how HTML elements are structured and troubleshoot when Amazon changes its layout. I spent more time debugging selectors than actually analyzing data. The newer AI-powered tools were a different story. I tested four of them seriously.
Bardeen
Bardeen is a well-known no-code automation platform, and its scraper is one of many features it offers. It has pre-built templates for popular websites including Amazon, which sounds great on paper.
What I liked:
- AI-assisted template creation. I described what I wanted in plain language and Bardeen generated a scraper template for me, which saved me the trouble of manually clicking on page elements. For my first Amazon price check, I had data in a spreadsheet within about 10 minutes.
- Direct export to Google Sheets. Since my competitive tracking spreadsheet lives in Google Sheets, not having to download a CSV and re-upload it was a nice touch.
What didn’t work for me:
- Templates broke constantly on Amazon. I set up a template for tracking “wireless earbuds” search results, and it worked fine for about two weeks. Then Amazon tweaked its product page layout and my template started pulling blank price fields. I had to go back in, re-select the price element, and save again. This happened three times in two months. It turns out this is common: one reviewer documented that about 15% of their scraping playbooks broke at least once in four months due to layout changes.
- Credits disappeared faster than I expected. I did not realize that every single action costs a credit: scraping one row is 1 credit, exporting that row to Google Sheets is another credit, and if you want to enrich it, that is 3 more. My first weekly scrape of 10 competitor product pages with export cost around 30 credits. The Pro plan gives you 500 credits for $10/month, and I burned through most of them in the first 10 days just doing basic price monitoring. I am not the only one who hit this wall: multiple users on Product Hunt said things like “3 basic webscraping tasks consumed credits really fast” and “made the calc for my need and it cost me an eye.”
- Too many features I would never use. Bardeen connects to HubSpot, Slack, LinkedIn, Salesforce, and dozens of other apps. That is great if you are a sales team automating outreach, but I just need Amazon data in a spreadsheet. I was paying for a Swiss Army knife when I only needed the blade.
Bottom line: If you are already using Bardeen for other automations (lead gen, CRM workflows), the scraper is a nice add-on. But if Amazon scraping is your primary need, the template fragility and credit burn rate make it frustrating.
Octoparse
Octoparse is one of the more established no-code scraping platforms. It has been around since 2016, has over 600 pre-built templates (including several for Amazon), and offers both local and cloud-based scraping. I actually used Octoparse for quite a while before switching, and there is a lot to like about it.
What I liked:
- The free Amazon templates are the best part. I entered my target keyword, hit run, and got back product titles, prices, ASINs, ratings, review counts, and images in a clean, structured table. No configuration, no selecting page elements. For pulling competitive data before a product launch, these templates saved me hours. It works as an amazon asin scraper too, since every result includes the ASIN. The data is thorough too: you get everything from shipping info to seller names, all exported to Excel, CSV, or JSON with one click. If you just need to scrape amazon product data as a one-time pull, Octoparse templates are hard to beat.
- Scheduled scraping is a real time-saver. I set up a task to run every Monday morning automatically, so my competitive pricing data was waiting for me when I opened my laptop. For ongoing monitoring, this is a huge advantage over tools that require you to manually trigger every scrape.
- Huge template library beyond Amazon. Octoparse has 600+ templates covering eBay, Google Maps, Yelp, LinkedIn, and more. If you sell on multiple platforms or need data from various sources, having ready-made templates for almost any popular website is genuinely convenient.
- The data quality is solid. When the templates work, the extracted data is clean, well-structured, and ready to drop into my analysis spreadsheet without much cleanup.
- Affordable compared to the alternatives I had tried. The Standard plan runs around $69/month on an annual basis, and honestly, I never even used up my full monthly allowance. After spending $300/month on freelancers and $50-100/month on scraping APIs that still required a coder to maintain, $69/month for a tool I could operate myself felt like a bargain.
What didn’t work for me:
- There is a learning curve upfront. The first time I opened Octoparse, I was a bit overwhelmed by all the options: local vs. cloud execution, workflow builder, pagination settings, proxy configuration. It took me a couple of hours of watching tutorials to feel comfortable. For simple template-based scrapes this is manageable, but if you ever need to build a custom scraper (for a website without a template), the visual workflow editor takes real time to learn.
- It is a heavyweight tool for a lightweight job. Octoparse can handle complex multi-step scraping workflows, database integrations, API access, and team collaboration. That power is great for scraping teams and agencies, but I just need “give me the top 50 products for this keyword every Monday.” Most of the platform’s capabilities went unused in my workflow.
Bottom line: Octoparse is a genuinely capable platform with the best pre-built Amazon templates I have tried. If you have the budget for the Standard plan and you need deep, scheduled data extraction across multiple sites, it is hard to beat. I used it for a long time and the data quality never let me down. I eventually moved on because I wanted something lighter and cheaper for my specific weekly routine, not because the tool itself fell short.
AI Web Scrapers: Chat4Data vs. Thunderbit
Octoparse served me well for a while, but I kept thinking: there has to be something lighter. Around that time, I started seeing a new wave of AI-powered web scrapers that promised a completely different approach. Instead of clicking on page elements or configuring templates, you just tell the AI what you want and it figures out the rest.
I tried two tools in this category: Chat4Data and Thunderbit. Both are Chrome extensions, both use AI, but they work in fundamentally different ways.
Chat4Data
I first noticed Chat4Data when it launched on Product Hunt last year and took both #1 Product of the Day and #1 Product of the Week. I figured anything that popular was worth a quick test, so I installed the extension and gave it a try. The result genuinely surprised me, and over the past year it has become my go-to tool.
What I liked:
- I just chat with it, and the data comes out exactly right. I type something like: “Open Amazon, search for ‘wireless earbuds’, sort by best sellers, and scrape product name, brand, price, rating, and number of ratings from the first 5 pages.” That is the entire setup. No clicking on page elements, no configuring fields. The scrape pulls exactly the columns I asked for, in the order I asked for them. Export is one click to Excel, CSV, or JSON. No merged fields, no cleanup needed.
- Tasks are reusable, which makes weekly monitoring effortless. Once I set up a scrape, I can save it and re-run it with one click every Monday. My Monday price check is literally: open the extension, click my saved task, let it run. That alone saves me 10+ minutes per session compared to tools where you start from scratch every time.
- It shows me the execution plan before running. Before anything happens, the extension lays out every step: open Amazon, type the search query, click the sort dropdown, scroll through results, extract data, click next page, repeat. I review the plan, adjust if needed, and then let it run. I catch mistakes before they cost me credits.
- Way more affordable than everything else I tried. Free tier gives you 100 credits on signup to test it properly. The Pro plan is $10/month for 2,000 credits, which covers my weekly price monitoring (about 450 credits/month) plus a monthly review deep-dive (about 500 credits) with room to spare. Dollar for dollar, it is not even close to the other options.
What I wish were better:
- The initial setup takes a moment. When you first describe a task, Chat4Data spends about 2 minutes analyzing the page and configuring the scraping plan.The good news is that once the plan is ready, the actual scraping runs fast, and you only go through this setup once per task since saved tasks skip this step entirely on re-runs. Still, if you are impatient like me, those first 2 minutes feel long.
- Product updates and new features come out slower than I would like. Compared to Thunderbit and Bardeen, which seem to ship updates every few weeks, Chat4Data’s development pace is more measured. That said, for Amazon scraping specifically, everything I need already works well. I just hope they keep adding features over time.
- It runs in your active browser tab, so I cannot browse in Chrome while a scrape is running. For my 15-minute Monday price checks, I just switch to another browser or check my phone. For the longer monthly review scrapes, I grab coffee.
- Very large scrapes (hundreds of pages) are slower than API-based tools since Chat4Data navigates like a real human. If you need to scrape tens of thousands of pages daily, an API service like Oxylabs or Octoparse’s cloud platform is a better fit. But for my volume (a few hundred products per week), speed has never been an issue.
For reference, Chat4Data currently has a 4.6 rating from 178 reviews on the Chrome Web Store with over 10,000 users.
I Also Tried Thunderbit
After Chat4Data became my main tool, Thunderbit started getting a lot of buzz online. It markets itself as “2-click scraping” and it seems more mainstream than Chat4Data, with a bigger marketing presence and more visibility on social media. I gave it a fair shot for a few weeks.
What I liked:
- Fast for quick, one-off checks. I could land on a product page and have a data table within 30 seconds. For those “let me quickly see what this competitor is charging” moments, it is hard to beat.
- The interface is clean and intuitive. Of all the tools I tested, Thunderbit has probably the most polished user experience. Everything feels modern and well-designed, and you can tell the team puts a lot of effort into making the product approachable for non-technical users.
- Export is free and flexible. I could send data directly to Google Sheets, Excel, Notion, or Airtable without paying extra. Most other tools either charge for exports or limit the format options, so this is a genuine advantage.
What didn’t work for me:
- For Amazon scraping specifically, it is not as good as Chat4Data or Octoparse. Thunderbit uses a point-and-click approach where you select fields one by one on the page. It works, but compared to Octoparse, which lets you run a pre-built Amazon template with one click, the setup feels slower. And compared to Chat4Data, where I just type what I want in a conversation and reuse saved tasks, the manual clicking felt like a step backward.
- The AI field detection was not always reliable on Amazon. It merged “rating” and “number of ratings” into a single column more than once, giving me entries like “4.5 out of 5 stars 2,847” that I had to manually split in Excel. Small thing, but it adds up when you are scraping weekly.
- It is significantly more expensive than Chat4Data for the same workload. This is my biggest gripe. The paid plan is $15/month for 500 credits (1 credit = 1 row). I would top up, run a few scrapes, and the credits would be gone before I got through two weeks of monitoring. The same workload costs me $10/month on Chat4Data with credits to spare. I have seen similar complaints on Trustpilot from other users who felt the credits ran out too quickly for what they were paying. If budget is not a concern, Thunderbit is a fine tool. But for no-code users who want the best value, Chat4Data is the clear winner in my experience.
Bottom line: Thunderbit is a solid, well-known scraper with a polished interface. But for Amazon specifically, Octoparse offers better templates and Chat4Data offers a simpler workflow at a lower price. I went back to Chat4Data after one week.
My Actual Weekly Workflow
Here is exactly how I use scraping for competitive analysis:
Weekly price monitoring (15 minutes). Every Monday, I re-run my saved Chat4Data scrape for my top 3 keywords. It pulls price, rating, seller name, and review count for the first 3 pages of results. It doubles as an amazon seller scraper since I can see exactly which sellers are competing on each listing. I paste the export into my tracking spreadsheet and scan for price drops, stockouts, and new entrants. This used to take me 3+ hours by hand.
Monthly review analysis (45 minutes). On the first Monday of each month, I scrape amazon reviews for my top 10 competitors in bulk. I filter by 1-star and 2-star reviews, looking for complaints that show up in 10%+ of negative reviews. Then I search for “I wish” and “if only” phrases to find feature requests. This is how I decided what features to add to my last product launch.
Quarterly category deep dive (1 hour). I scrape 50+ products across multiple keywords to spot trends: new brands entering, pricing shifts, rating changes over time. I also pull the top-ranked products in my category to see who is gaining traction.
The Bottom Line
If you are an Amazon seller trying to figure out how to scrape data from Amazon without writing code, hiring a developer, or paying $100+/month for proxies and APIs, an AI-powered browser extension is the most practical solution I have found.
I landed on Chat4Data after testing seven different approaches over a year. Your needs might lead you to a different amazon web scraper, but the category of AI-powered browser scraping is where I would start looking. The best amazon scraper is the one you will actually use every week.
Frequently Asked Questions
How do I scrape Amazon without coding?
AI-powered Chrome extensions like Chat4Data, Thunderbit, and Bardeen let you scrape Amazon data without writing code. With Chat4Data, you describe what data you want in plain English and the AI handles navigation, extraction, and export. With Thunderbit, the AI auto-detects fields on the page for you to confirm. With Bardeen or Octoparse, you select page elements visually. No scripts or HTML knowledge needed for any of them. If you want to scrape Amazon products from search results, any of these tools can handle it.
Will Amazon ban my seller account for scraping?
Account bans for scraping are extremely rare for individual sellers. Scraping publicly available pages is different from violating seller policies. Aggressive scraping (thousands of pages per hour from one IP) can trigger temporary IP blocks, but browser-based tools that mimic normal browsing behavior minimize this risk. Keep your volume reasonable and you should be fine.
How often should I scrape competitor prices?
Weekly works for most categories. If you sell in a fast-moving niche where prices change daily (electronics, supplements, commodity products), daily monitoring may be worth it. I started weekly and never felt the need to increase.
Can I use scraped data to automatically reprice my products?
Not directly from the scraping tool, but you can export competitor pricing data as CSV and feed it into repricing software like RepricerExpress or Informed.co. Some sellers build spreadsheet formulas to calculate target prices based on the scraped data and update listings manually. Full automation requires API-based scraping and custom code.
What is the difference between scraping and Amazon’s official APIs?
Amazon’s Product Advertising API and Selling Partner API provide limited, approved data access for specific use cases (affiliate marketing, your own inventory management). Neither gives you broad competitive intelligence like full category search results, competitor seller data, or bulk review analysis. Scraping fills that gap.
How do I scrape Amazon product reviews for competitor research?
If you want to scrape reviews from Amazon, use a no-code scraping tool to extract all reviews from a competitor’s product page. You do not need to scrape amazon reviews python style with custom scripts. Export them to Excel, then filter by 1-star and 2-star reviews to find recurring complaints. Search for phrases like “I wish” or “if only” to surface unmet customer needs. This method is how many sellers identify gaps in the market before launching new products. Any decent amazon reviews scraper can handle this workflow.
Is it legal to scrape Amazon product data?
Scraping publicly visible data (prices, titles, ratings, reviews) is generally considered legal. The hiQ Labs v. LinkedIn case established a precedent around accessing public data. Amazon’s Terms of Service do restrict automated access, but this is a contractual matter, not criminal. I only scrape public pages, never behind login walls, and keep volumes reasonable. For large-scale commercial use, consult a lawyer.
