Introduction
Analyzing product reviews is critical for understanding customer sentiment, improving products, and making informed business decisions. With the rise of e-commerce, Amazon and Walmart are two of the largest online marketplaces generating millions of reviews annually. Using scrape Amazon and Walmart reviews without coding, businesses can access 50K+ reviews monthly, uncover consumer preferences, and derive actionable insights without technical expertise. This approach allows companies to analyze trends, detect product issues, and enhance marketing strategies efficiently. Leveraging no-code tools simplifies data collection, reduces manual effort, and accelerates decision-making. By transforming unstructured review data into structured datasets, businesses can track performance across categories, monitor competitor products, and predict market trends.
Understanding Review Volume Trends
Using Scrape Amazon and Walmart Product Reviews, companies can automatically collect product reviews for analysis. Between 2020 and 2025, the total number of reviews analyzed grew from 1 million to over 6 million monthly, reflecting the surge in online shopping. Review collection allows businesses to monitor product performance, detect common complaints, and identify highly praised features.
Table 1: Total Reviews Collected (2020–2025)
| Year |
Reviews Collected |
Products Covered |
Avg Reviews per Product |
| 2020 |
1,000,000 |
10,000 |
100 |
| 2021 |
2,000,000 |
15,000 |
133 |
| 2022 |
3,500,000 |
20,000 |
175 |
| 2023 |
4,500,000 |
25,000 |
180 |
| 2024 |
5,500,000 |
30,000 |
183 |
| 2025 |
6,000,000 |
35,000 |
171 |
Automating review scraping enables businesses to quickly adapt to customer needs and improve products across categories.
Tracking Popular Products
Monitoring scrape amazon search results allows businesses to identify trending items and competitor listings. Between 2020 and 2025, the number of products tracked grew by 250%, highlighting the increasing need for competitive intelligence. Companies can extract product titles, prices, ratings, and reviews from search results to identify top-performing products, optimize pricing, and refine marketing strategies.
Table 2: Search Result Analysis (2020–2025)
| Year |
Products Tracked |
Avg Price ($) |
Avg Rating |
Top Category |
| 2020 |
5,000 |
25 |
4.2 |
Electronics |
| 2021 |
10,000 |
26 |
4.3 |
Toys |
| 2022 |
15,000 |
27 |
4.4 |
Home Goods |
| 2023 |
20,000 |
28 |
4.5 |
Beauty |
| 2024 |
25,000 |
29 |
4.6 |
Apparel |
| 2025 |
30,000 |
30 |
4.7 |
Electronics |
Analyzing search results helps businesses understand emerging trends and adjust inventory to meet consumer demand efficiently.
Insights from Amazon Reviews
Table 3: Amazon Review Analytics (2020–2025)
Using a no code Amazon review scraper, businesses can extract detailed review data including ratings, review text, reviewer details, and helpfulness votes. From 2020 to 2025, the volume of reviews collected per month grew from 500K to 3 million. Analyzing sentiment trends and recurring themes allows businesses to enhance product features and improve customer satisfaction.
| Year |
Reviews Extracted |
Avg Rating |
Positive Feedback (%) |
Negative Feedback (%) |
| 2020 |
500,000 |
4.2 |
78 |
22 |
| 2021 |
1,000,000 |
4.3 |
80 |
20 |
| 2022 |
1,500,000 |
4.4 |
82 |
18 |
| 2023 |
2,000,000 |
4.5 |
83 |
17 |
| 2024 |
2,500,000 |
4.6 |
85 |
15 |
| 2025 |
3,000,000 |
4.7 |
87 |
13 |
This approach ensures timely insights and helps businesses optimize product positioning based on customer feedback.
Walmart Review Analysis
A no code Walmart review scraper enables extraction of thousands of customer reviews. From 2020 to 2025, Walmart review data increased by 300%, reflecting growing consumer engagement. Extracted data includes ratings, review content, and purchase verification status, which can be used to measure customer satisfaction, identify product gaps, and detect counterfeit or low-quality products.
Table 4: Walmart Review Analysis (2020–2025)
| Year |
Reviews Extracted |
Avg Rating |
Verified Purchase (%) |
Top Product Category |
| 2020 |
400,000 |
4.1 |
70 |
Electronics |
| 2021 |
700,000 |
4.2 |
72 |
Home Appliances |
| 2022 |
1,000,000 |
4.3 |
75 |
Toys |
| 2023 |
1,500,000 |
4.4 |
77 |
Grocery |
| 2024 |
2,000,000 |
4.5 |
80 |
Health & Beauty |
| 2025 |
2,500,000 |
4.6 |
82 |
Apparel |
Walmart review scraping helps brands measure performance, improve quality, and track competitor products efficiently.
QCross-Platform Insights
Businesses can Scrape Data From Any Ecommerce Websites to analyze reviews and product trends across multiple platforms. Between 2020 and 2025, multi-platform review scraping grew by 200%, covering over 50,000 SKUs monthly. This enables companies to compare product performance, pricing, and consumer sentiment across marketplaces.
Table 5: Multi-Ecommerce Review Coverage (2020–2025)
| Year |
SKUs Tracked |
Reviews Collected |
Avg Rating |
Platforms Covered |
| 2020 |
10,000 |
500,000 |
4.2 |
3 |
| 2021 |
15,000 |
750,000 |
4.3 |
4 |
| 2022 |
20,000 |
1,000,000 |
4.4 |
5 |
| 2023 |
25,000 |
1,500,000 |
4.5 |
5 |
| 2024 |
30,000 |
2,000,000 |
4.6 |
6 |
| 2025 |
35,000 |
2,500,000 |
4.7 |
6 |
This data allows for cross-platform comparison, identifying trends and opportunities to improve product offerings.
E-Commerce Product Data Analysis
With Extract Amazon E-Commerce Product Data, businesses can collect product details, reviews, and ratings for in-depth analysis. Between 2020 and 2025, extracted data points increased from 200,000 to over 3 million monthly, helping identify consumer preferences and top-performing products.
Table 6: Amazon Product Data Extraction (2020–2025)
| Year |
Products Extracted |
Data Points |
Avg Reviews per Product |
Top Category |
| 2020 |
5,000 |
200,000 |
40 |
Electronics |
| 2021 |
8,000 |
400,000 |
50 |
Toys |
| 2022 |
12,000 |
800,000 |
66 |
Home Goods |
| 2023 |
18,000 |
1,200,000 |
66 |
Beauty |
| 2024 |
25,000 |
2,000,000 |
80 |
Apparel |
| 2025 |
35,000 |
3,000,000 |
85 |
Electronics |
This data supports trend forecasting, marketing strategy, and product development decisions.
Why Choose Product Data Scrape?
Product Data Scrape provides accurate Walmart E-commerce Product Dataset solutions for businesses. By leveraging structured review and product data, companies can monitor trends, track competitor performance, and optimize products. Insights from scrape Amazon and Walmart reviews without coding allow businesses to gain a competitive edge, improve customer satisfaction, and make data-driven decisions across multiple e-commerce platforms.
Conclusion
Analyzing reviews with scrape Amazon and Walmart reviews without coding enables businesses to access 50K+ reviews monthly, track sentiment, and optimize product offerings. Real-time insights allow companies to adjust pricing, identify high-demand products, and improve inventory planning. By using no-code scraping tools, businesses save time, reduce errors, and gain actionable intelligence that drives growth and enhances competitiveness.
Start using Product Data Scrape today to scrape Amazon and Walmart reviews without coding and unlock valuable market insights for your business.
FAQs
1. How can I scrape Amazon and Walmart reviews without coding?
Use no-code scraping tools from Product Data Scrape to extract reviews, ratings, and consumer feedback effortlessly for analysis.
2. How many reviews can I analyze monthly?
You can scrape and analyze over 50,000 reviews monthly from Amazon and Walmart using no-code tools.
3. Is it safe to scrape reviews from Amazon and Walmart?
Yes, using compliant no-code tools ensures data extraction is safe and adheres to website policies.
4. Can I extract both ratings and review text?
Absolutely, no-code solutions allow extraction of star ratings, review text, reviewer details, and verified purchase info.
5. Can this data help improve product strategy?
Yes, insights from reviews help optimize products, track competitors, forecast trends, and enhance customer satisfaction.
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