Top 5 Industries that Benefit Most from Web Data Scraping

Competitive moat is the key differentiator in the online or offline business world. Companies, enterprises, and online businesses that are able to create a ‘competitive edge’ or ‘x-factor’ that differentiates them from key competitors are the ones that survive and thrive in the modern business environment. One such edge is data-driven competence. It is the sum total of all insights and metrics that industries can get from scraping and analyzing their industry-specific data.

For getting this data, industries go for web data scraping – the automated extraction of valuable information from specific websites and online platforms relevant in a particular business vertical. What once required teams of analysts manually combing through websites has now become an automated, efficient process thanks to advanced scraping technologies.

For instance, an ecommerce business needs data from websites like Amazon, eBay, Target, etc. to fetch data that can provide insights, patterns, trends and product intelligence that is valuable for online businesses. Data extraction and analysis power ‘intelligence’--competitive, price, and location. It can generate metrics that can transform how industries sell products, which products they sell, to whom and where. The benefits of data scraping for creating a competitive moat are not immense but tangible too.

In this article, we will discuss the top 5 industries that benefit the most from ethical, legal, and sophisticated data scraping by deploying automated web scrapers or custom APIs.

Data Scraping: Meaning, Need, and Tools

Data scraping is a method where a software with custom script or code is deployed to extract data from various online sources, databases or touch-points. It's an automated process that once implemented, harvests web data from target platforms (websites, apps). The data scrapers can go to thousands of web pages and extract data that is required for analysis. This data is presented in tabulated form. It is also cleaned and made error-free by employing data-cleaning processes.

The process is technical and therefore not all companies or enterprises working in a particular industry are self-sufficient to conduct it on their own. Generally, they don’t have any such departments or experts that can do data scraping. Even IT teams that can do basic maintenance of industry applications, business apps, and servers are not proficient enough to do data scraping. Data scraping also has legal and ethical implications. For instance, data scrapers must be able to deal with anti-scraping measures at the target websites and also, know what to scrape and what not to. For instance, scraping personal data can cause legal repercussions.

This is where specialized data scraping services providers help various industries and businesses throughout the data scraping process.

The need for data scraping has grown exponentially as industries seek to:

• Monitor competitors’ pricing, products, and strategies in real-time
• Gather market intelligence and identify emerging trends
• Enhance decision-making with data-driven insights
• Improve customer experience through personalization
• Optimize pricing strategies based on market conditions

Common tools used for web scraping include:

• Programming Libraries: Python-based tools like BeautifulSoup, Scrapy, and Selenium
• Scraping Software: Scraping Intelligence, X-Byte, iWeb Scraping
• Cloud-based Scraping Services: X-Byte, Scraping Intelligence
• Browser Extensions: Web Scraper, Data Miner, and Instant Data Scraper
• API Integration Tools: Like those offered by iWeb Scraping, X-Byte, 3i Data Scraping, Foodspark, Retailgators, Scraping Intelligence

Top 5 Industries Benefiting the Most From Data Scraping

E-commerce & Retail

Online shops and e-stores face tough competition. They need to keep up with changing prices, products, and how they service customers. There's a ton of info to handle - a typical web store might need to monitor thousands of items on many rival websites. Prices can change several times a day. This makes it impossible to track manually.

With companies like Amazon updating prices up to 2.5 million times a day, e-retailers cannot implement price intelligence or dynamic pricing unless they employ automated scraping solutions. Automated Web scraping ecommerce product data has become indispensable in this industry. The data output and subsequently derived insights help online businesses monitor their competitors, optimize pricing strategies, and improve CX based on review data scraping.

Type of Data or Data Sets the E-commerce and retail industry can scrape

• Product pricing
• Customer reviews
• Product catalogs
• Promotional offers
• Stock availability

Use Cases

• Competitive pricing analysis
• Sentiment analysis
• Market gap identification
• Marketing strategy development,
• Inventory management

Hotels and Travel

Travel companies depend on competitor price tracking to set their own prices. Airlines tweak ticket costs based on how many people want to fly. Hotels set room rates higher when it's busy. Web scraping gives them the up-to-date info they need to stay in the game.

According to Statista, the global online travel market reached nearly 642 billion USD with prices fluctuating constantly based on demand, seasonality, and competitor strategies. The data volume in this industry is colossal – a global OTA (Online Travel Agency) or travel booking websites need to monitor millions of hotel listings and flight options that change by the minute.

The extraction difficulty is particularly high due to sophisticated anti-scraping measures employed by many travel aggregator platforms, making specialized scraping technologies essential. Data scraping services in this sector include Trip Advisor data scraping, Booking.com data scraping, Agoda Travel data scraping, and more.

Type of Data or Data Sets the Hotels and Travel Industry can scrape

• Dynamic pricing
• Fare prediction
• Reputation management
• Demand forecasting

Real Estate

The real estate industry has undergone a digital transformation in recent years, with online listings becoming the primary source of property information. Scraping real estate platforms and sites like MagicBricks, Movoto, Homes.com and Realtor enables real estate companies to gather comprehensive market intelligence, track property valuation trends, and identify investment opportunities.

The real estate data ecosystem is vast but fragmented – with property listings spread across multiple platforms and websites, often with inconsistent data formats. Advanced Scrapers built for real estate scraping provide the data in easy to read and analyze formats like JSON, CSV, Excel, HTML, etc.

The differentiation potential is significant – companies with access to comprehensive, real-time market data can identify undervalued properties and market trends before competitors.

Type of Data or Data Sets the Real Estate industry can scrape

• Property listings
• Rental rates
• Historical sales data
• Neighborhood statistics

Use Cases

• Market analysis
• Investment research
• Valuation models
• Location analytics
• Development Tracking

Food & Grocery Delivery (Quick Commerce)

The food and grocery delivery sector has experienced explosive growth, accelerated by changing consumer behaviors. Market intelligence derived from data scraping helps delivery services optimize pricing, expand their restaurant and product offerings, and improve delivery logistics.

The online food delivery market reached approximately $1.5 trillion globally in 2025. The data volume in this industry is substantial and diverse – ranging from restaurant menus and prices to delivery times and customer reviews across thousands of food delivery establishments including ghost kitchens, delivery only restaurants, and food delivery aggregators.

Grocery delivery websites that list thousands of grocery products are also go-to websites for insights about the quick commerce delivery segment. The top websites that are scraped for valuable data in this industry include: Zomato, KFC, Swiggy, Zepto, Gopuff, Hungryroot, etc.

Type of Data or Data Sets the Food & Grocery Delivery industry can scrape

• Restaurant menus
• Competitor pricing
• Customer reviews
• Delivery times
• Special offers

Use Cases

• Catalog expansion
• pricing strategy
• Quality control
• Logistics optimization
• Promotional planning

OTT & Entertainment

The streaming and entertainment world now runs on data, with tailored content suggestions and better user experiences leading the way in staying ahead. Entertainment companies use data scraping to understand how content performs, what viewers like, and what competitors offer. For instance, you can know what genres are currently making waves among viewers by analyzing Netflix, Hotstar, Amazon Prime, and Hulu.

Netflix provides recommendations through its data-driven system. This industry deals with huge amounts of data, including lists of shows and movies, how viewers rate them, and how much they watch across different platforms.

Type of Data or Data Sets the OTT industry can scrape

• Content catalogs
• Viewer ratings
• Engagement metrics
• Pricing structures
• Regional availability

Use Cases

• Content recommendation
• Library development
• Content acquisition
• Programming strategy
• Subscription modeling
• Market expansion

How Can Industry-specific Data Scraping Services Help the above industries?

How Can Industry-specific Data Scraping Services Help the above industries?

• Compliance Expertise: Industry-specific scrapers know the legal and ethical limits of data collection in their fields. This cuts down on regulatory risks.
• Custom Data Processing: Specialized services can pull out, clean up, and organize data to meet industry-specific needs. This makes the data ready to use for business insights right away. It also lessens the in-house data processing workload.
• Advanced Anti-blocking Measures: Industry experts create smart ways to get around anti-scraping tools unique to their target websites. This ensures a steady flow of data.
• Integrated Analytics: Many industry-specific services now offer built-in tools to analyze data. These tools turn raw scraped data into useful insights that match industry key performance indicators.
• Scalable Infrastructure: Special services can handle the exact volume and frequency needs of each industry. They scale resources during busy scraping times. For retail, this happens in the holiday seasons. For travel, it occurs during booking windows.

Conclusion

Web data scraping has become a key competitive edge in many industries. It changes how companies collect intelligence, reach decisions, and craft strategies. The five sectors we've looked at – e-commerce & retail, hotels & travel real estate, food & grocery delivery, and OTT & entertainment – show the biggest gains from these tools right now.

As data keeps growing in size and value, being able to pull, handle, and examine web info will be even more key for companies to do well. Businesses that put money into strong data scraping tools, either by building them in-house or hiring expert services, set themselves up to make smarter choices, react faster to market shifts, and give customers better experiences.

Excited to know more about how data scraping can transform your business intelligence capabilities?

Get in touch with Scraping Intelligence today to explore customized solutions tailored to your industry’s specific requirements.

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