use-data-scraping-and-cleaning-for-amazon-competitor-research

While running an ecommerce business on Amazon, it is essential to check the prices of competing companies using competitor price monitoring. However, it is only a tiny part of competitor analysis, and you can use Amazon data for countless things.

In this post, let's dive into the process of performing competitor research on e-commerce websites like Amazon using competitor data collection and cleaning. And use the collected data for Amazon competitor research, check ways for brand protection, review promotional insights for advertising campaigns, assortment analytics to manage inventory, etc. Though you are a newbie and scraping product data from Amazon for the first time, check out the following steps.

To simplify the guide, let's take an example of Earbuds and Headphones from Amazon. Scraping Amazon, we'll find each product's average rating and reviews from the example category.

Why Perform Competitor Research for Amazon Products?

Having over 6 million product sellers on platforms that sell more than 350 million products worldwide, it is easy for Amazon to provide the correct product data for Amazon's competitor research. You can quickly check product prices, reviews, ratings, listings, and discounts on the platform for each product. You can scrape Amazon Product data to collect all these data fields.

Hence, Amazon is a fantastic place to conduct market research for e-commerce businesses. It gives enough data to monitor competitors, find market trends, study customer sentiments, and use these factors to make data-driven decisions.

Scrape Amazon Competitor Data using Product Data Scrape

To start Amazon competitor data scraping, you can try our customized solution. Further, you can also use our no-code tool to scrape e-commerce data from platforms like Amazon. If you are new to using our tool, you can visit our website to access it on your device.

If you still need to access the tools, you must create an account on our platform. After that, follow the below process.

Step 1: Click the new tab and then the custom task option. After that, paste the URL to target into the search bar. Then, create a new task by clicking the save button.

For example, here is the target URL for the required product.

https://www.amazon.com/s?rh=i%3Aelectronics%2Cn%3A172541%2Cp_n_feature_four_browse-bin%3A12097501011&ie=UTF8&lo=electronics

For-example,-here-is-the-target-URL-for-the-required-product

Step 2: Our tool will load the targeted page in the built-in web browser after successfully creating the new task. Once it completes loading the page, visit the Tips panel and click the option to detect web page data automatically. Our tool will scan the targeted page and discover the required data. It will highlight the discovered data in red color. You can make necessary changes in the data once you preview it as below.

Step-2-Our-tool-will-load-the-targeted-page-in-the-built-in

Step 3: After completing the above two steps, click the option to create a workflow. Then, our software will automatically create the scraping workflow. It has exact steps to scrape the required data. Before executing the workflow, remember to read it and make necessary changes so that it will work without errors and give you accurate data.

Step-3-After-completing-the-above-two-steps

Step 4: Click the Run option after verifying each setting. Then our tool will give two options for server location to run the project. If your project is small and quick, run the Amazon competitor data collection project on your device. But if your project needs a large amount of data for the long term, you can use cloud servers from our platform that never stop working.

Step-4-Click-the-Run-option-after-verifying-each-setting

Step 5: Once you complete all the above steps and scrape competitor data, you can download it in any digestible format like CSV, JSON, or Excel.

Filter and Analyze Amazon Competitor Data Using QuickTable

Even though we've collected the Amazon data, it contains some unwanted data points. Therefore, you can't use the data directly. It means we have to do something extra to clean the data. Here, we'll use QuickTable to filter and study the data.

Here are a few simple steps to clean the scraped Amazon competitor data.

  • Open QuickTable on your devices and log in with the necessary credentials. After that, create a new task named Amazon Competitor Data.
  • Upload the file of collected data as a new dataset to QuickTable. You'll see around 48 columns after opening the tool. Now, remove the unwanted data to clean it for further analysis.
  • To get the rating and average price for this sample data, only keep columns aiconalt, asizebaseplus1, Price, Like URL1, etc. Then rename them according to your choices.
  • You'll find some blank price rows for some products. You can filter those by filtering and deleting empty cells.
  • You can still find some empty cells for the original price column. Here, use the following formula to set these prices.
  • IF(IS_NULL(`Original_price`),`Sales_price`,`Original_price`)

  • Now, you'll see both cells, namely the original price and sales price, have value in the string format. It would help if you converted string values to numerical values. Use the following process to get number values.
  • Select Format->Substring->Extract number

    Then, rename new number value columns and select string columns.

    Then,-rename-new-number-value-columns-and-select-string-columns
  • Another column that has string formats with more complexity is Stars. There are two numerical values in all cells. You need the first number from them.
  • Again use a similar process: Format->Substring->Extract number but retain the first number only in the resulting column. You will see a new column that will display the first number. Rename that column as Star_number.

Perform Simple Competitor Research with Cleaned Amazon Data

Perform-Simple-Competitor-Research-with-Cleaned-Amazon-Data

So far, you have a clean file of data that you can analyze in various aspects.

For example, you can use the Group By option of QuickTable to calculate product count for ratings. You'll get the result with product count having a similar average rating.

Now, you will see the output in two columns. You can create a reader-friendly chart using the output. Follow the conventional steps to create a chart by filling required parameters and seeing the chart.

It is evident that top products are under average rating, and the start range lies between 4.1 to 4.5. It shows how popular these products are among buyers. It will help you find the rating and performance of your product in the market.

It-is-evident-that-top-products-are-under-average-rating

You can examine the data with original and sales price columns by following the same steps.

Conclusion

This way, we've shared how to use Amazon data scraping and cleansing for Amazon competitor research for your e-commerce business. If you have any more queries regarding e-commerce scraping services, contact Product Data Scrape.

LATEST BLOG

Why Choose a Data Extraction Service From Namshi UAE for Fashion Insights?

Boost retail intelligence with a Data Extraction Service From Namshi UAE for Fashion Insights and real-time decisions.

What Makes Web Scraping Product Data from Jumia Website a Game-Changer for Retail Analytics?

Web Scraping Product Data from Jumia Website enables businesses to monitor prices, analyze trends, and optimize strategies efficiently.

How Can You Extract Wine Product Data from Wine.com for Better Business Insights?

Extract Wine Product Data from Wine.com for Better Business Insights and drive smarter decisions with accurate wine intelligence.

Case Studies

Discover our scraping success through detailed case studies across various industries and applications.

Why Product Data Scrape?

Why Choose Product Data Scrape for Retail Data Web Scraping?

Choose Product Data Scrape for Retail Data scraping to access accurate data, enhance decision-making, and boost your online sales strategy.

Reliable-Insights

Reliable Insights

With our Retail data scraping services, you gain reliable insights that empower you to make informed decisions based on accurate product data.

Data-Efficiency

Data Efficiency

We help you extract Retail Data product data efficiently, streamlining your processes to ensure timely access to crucial market information.

Market-Adaptation

Market Adaptation

By leveraging our Retail data scraping, you can quickly adapt to market changes, giving you a competitive edge with real-time analysis.

Price-Optimization

Price Optimization

Our Retail Data price monitoring tools enable you to stay competitive by adjusting prices dynamically, attracting customers while maximizing your profits effectively.

Competitive-Edge

Competitive Edge

With our competitor price tracking, you can analyze market positioning and adjust your strategies, responding effectively to competitor actions and pricing.

Feedback-Analysis

Feedback Analysis

Utilizing our Retail Data review scraping, you gain valuable customer insights that help you improve product offerings and enhance overall customer satisfaction.

Awards

Recipient of Top Industry Awards

clutch

92% of employees believe this is an excellent workplace.

crunchbase
Awards

Top Web Scraping Company USA

datarade
Awards

Top Data Scraping Company USA

goodfirms
Awards

Best Enterprise-Grade Web Company

sourcefroge
Awards

Leading Data Extraction Company

truefirms
Awards

Top Big Data Consulting Company

trustpilot
Awards

Best Company with Great Price!

webguru
Awards

Best Web Scraping Company

Process

How We Scrape E-Commerce Data?

Resource Hub: Explore the Latest Insights and Trends

The Resource Center offers up-to-date case studies, insightful blogs, detailed research reports, and engaging infographics to help you explore valuable insights and data-driven trends effectively.

Get in Touch

Why Choose a Data Extraction Service From Namshi UAE for Fashion Insights?

Boost retail intelligence with a Data Extraction Service From Namshi UAE for Fashion Insights and real-time decisions.

What Makes Web Scraping Product Data from Jumia Website a Game-Changer for Retail Analytics?

Web Scraping Product Data from Jumia Website enables businesses to monitor prices, analyze trends, and optimize strategies efficiently.

How Can You Extract Wine Product Data from Wine.com for Better Business Insights?

Extract Wine Product Data from Wine.com for Better Business Insights and drive smarter decisions with accurate wine intelligence.

Extract Grocery Product Data from BJs Wholesale Club to Monitor Pricing and Stock Trends

Extract Grocery Product Data from BJs Wholesale Club to track real-time pricing, stock, and category trends.

Enhance Retail Decision-Making Using Real-time Kroger Grocery Data Scraping API

Real-time Kroger Grocery Data Scraping API delivers instant access to pricing, stock, and product insights across locations.

Scrape Hyperlocal Pricing Data for Market Insights to Drive Regional Pricing Strategies

Scrape Hyperlocal Pricing Data for Market Insights to optimize regional strategies, monitor trends, and enhance competitiveness.

Unlocking Retail Insights by Web Scraping Grocery Prices from San Francisco Stores

Web Scraping Grocery Prices from San Francisco Stores enables real-time insights into pricing, trends, and retail competition.

Extract Grocery Retail Trends 2025 for Smarter Decision

Extract Grocery Retail Trends 2025 to uncover evolving consumer behavior, pricing shifts, digital adoption, and private label growth.

Leverage the Top Grocery Store Location Datasets to Identify Market Gaps

Top Grocery Store Location Datasets reveal regional market gaps, guiding retailers in optimizing expansion and strategic planning decisions.

Driving Retail Decisions with Grocery Store Pricing Data Intelligence

: Retailers make informed pricing, promotion, and stocking decisions using accurate Grocery Store Pricing Data Intelligence insights.

Unlocking Grocery & FMCG Insights with Quick Commerce Price Data Scraping

Unlock Grocery & FMCG Insights with real-time data scraping for smarter pricing, inventory, and market trend decisions.

Exploring Web Scraping: Unlocking Insights for Businesses & Researchers

Exploring web scraping to uncover valuable insights that benefit businesses and researchers in various industries.

Inside U.S. Grocery Industry 2025: Trends, Strategies, and the Power of Data Scraping

Exploring the US Grocery Industry 2025 with key trends strategic insights and the impact of data scraping

Real-Time E-Commerce Web Scraping for Assessing Price Change Frequency

Real-Time E-Commerce Web Scraping for Assessing Price Change Frequency Across Amazon, eBay, and Walmart Platforms

Discover Best Buy’s Market Secrets Through Web Scraping

Unlock Best Buy’s market secrets with web scraping: track prices, reviews, and trends for strategic insights.

Sainsbury’s: Dominating UK Retail with Size, Growth, and Green Goals

Sainsbury’s leads UK retail with a vast store network, substantial revenue, and ambitious sustainability goals.

FAQs

E-Commerce Data Scraping FAQs

Our E-commerce data scraping FAQs provide clear answers to common questions, helping you understand the process and its benefits effectively.

E-commerce scraping services are automated solutions that gather product data from online retailers, providing businesses with valuable insights for decision-making and competitive analysis.

We use advanced web scraping tools to extract e-commerce product data, capturing essential information like prices, descriptions, and availability from multiple sources.

E-commerce data scraping involves collecting data from online platforms to analyze trends and gain insights, helping businesses improve strategies and optimize operations effectively.

E-commerce price monitoring tracks product prices across various platforms in real time, enabling businesses to adjust pricing strategies based on market conditions and competitor actions.

Let’s talk about your requirements

Let’s discuss your requirements in detail to ensure we meet your needs effectively and efficiently.

bg

Trusted by 1500+ Companies Across the Globe

decathlon
Mask-group
myntra
subway
Unilever
zomato

Send us a message