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Discover how Actowiz Solutions used web scraping to uncover market trends and competitor pricing insights for strategic business decisions.
In today’s digital-first landscape, market success depends heavily on real-time intelligence. For one fast-scaling eCommerce client, traditional market research couldn’t keep pace with shifting consumer preferences and competitor strategies. The company approached Actowiz Solutions, a leader in web scraping and data intelligence, to extract actionable insights from 5 competitive platforms.
The client needed to:
Each target website (including Amazon, Walmart, and niche vertical-specific competitors) had unique HTML/CSS layouts and used dynamic rendering, making uniform data extraction complex.
With thousands of SKUs and pricing updates occurring daily, speed and frequency were crucial.
Extracting not just star ratings but also sentiment-rich insights from unstructured review text was a top priority.
Actowiz deployed a custom scraping pipeline using Python (Scrapy + Selenium) with cloud-based proxy rotation and anti-bot bypass mechanisms to collect real-time data.
| Website | Product Name | Price | Avg Rating | Stock | Review Sentiment |
|---|---|---|---|---|---|
| Amazon | EcoSmart LED Bulb | $14.99 | 4.5 | In Stock | Positive |
| Walmart | Philips Hue Light | $18.50 | 4.2 | In Stock | Mixed |
| Target | GE Smart Bulb | $12.99 | 3.8 | Out of Stock | Negative |
| Niche 1 | Zigbee Hub | $39.99 | 4.6 | In Stock | Positive |
Once collected, Actowiz transformed the raw HTML into a structured format using:
The client discovered that 21% of their products were priced at least 8–10% higher than direct competitors. They implemented dynamic pricing, which increased conversion rates by 12.4% within 30 days.
Using scraped competitor product data, the client identified 12 high-velocity SKUs they weren’t offering. These were added to their catalog, resulting in a 17% increase in sales for the new product line.
Actowiz’s sentiment analysis of 25,000+ reviews revealed that “packaging issues” and “late delivery” were trending negatives for a top competitor. The client used this insight to prioritize faster shipping and eco-packaging—leading to a 9% boost in repeat purchases.
| Sentiment Category | Percentage |
|---|---|
| Positive | 62% |
| Mixed | 18% |
| Negative | 20% |
Most frequently mentioned keywords in reviews: “value for money,” “delivery delay,” “packaging damage”
| Component | Tools Used |
|---|---|
| Scraping Engine | Python, Scrapy, Selenium |
| Proxy Handling | Luminati, Bright Data |
| Review Sentiment | NLTK, TextBlob, VADER |
| Data Delivery | REST API, Amazon S3 |
| Visualization | Power BI, Excel Dashboards |
“Actowiz Solutions didn’t just give us data—they gave us market vision. Their scraping strategy helped us course-correct product pricing and stay three steps ahead of competitors.”
– VP, Product Strategy (Client)
This project proves that multi-site web scraping isn’t just a data collection task—it’s a strategic imperative. With Actowiz Solutions, the client turned fragmented online data into a competitive roadmap.
As markets become more dynamic, businesses that invest in data scraping for competitor pricing, product intelligence, and customer sentiment will always gain the edge.