Best Web Scraping Projects: Insights from 1000s of Our Users

Web scraping is a foundation for many data-driven projects, allowing users to collect, analyze, and act on large datasets from online sources. Drawing insights from our vast user base, we’ve compiled a list of diverse and impactful web scraping projects that can inspire your next endeavor. Whether you’re a beginner or a seasoned scraper, these ideas highlight the incredible potential of this technology.

30 Best Web Scraping Projects: Data from Our 1000s of Users

1. Price monitoring for E-commerce

Track prices across e-commerce platforms to monitor market trends, offer competitive pricing, or identify the best deals for consumers. This project would expand to create historical price datasets for deeper analysis.

Why it’s a good idea:
With dynamic pricing becoming standard in e-commerce, price monitoring tools help businesses and consumers make informed decisions and stay competitive.

How to approach it:

• Identify popular e-commerce platforms (e.g., Amazon, eBay, Walmart).
• Use ScraperAPI to handle dynamic content and bypass bot protection.
• Extract product names, prices, discounts, and availability regularly.
• Build dashboards for real-time price tracking and historical comparisons.

Tools to use:

• ScraperAPI (for IP rotation and bypassing captchas)
• BeautifulSoup (for HTML parsing)
• Pandas (for data organization)

Importance in 2025:
As online shopping grows and pricing algorithms evolve, businesses will increasingly rely on price monitoring tools to remain competitive.

2. Real estate aggregators

Build a real estate aggregator to collect property listings from various websites. Include location, price, amenities, and availability, enabling users to compare options in one place. You can also collect property listings from different platforms and compare prices to know which is cheaper.

Why it’s a good idea:
Real estate data is often scattered across multiple platforms. Aggregators provide a centralized view of properties, simplifying the search process for buyers and renters.

How to approach it:

• Scrape property details, pricing, images, and agent contacts from real estate websites.
• Use ScraperAPI to navigate dynamic pages and avoid IP bans.
• Organize data into searchable categories (e.g., location, price range, property type).

Tools to use:

• ScraperAPI (to handle anti-scraping mechanisms)
• Selenium (for dynamic page rendering)
• Pandas (for data filtering and analysis)

Importance in 2025:
With housing markets becoming more data-driven, real estate aggregators will play a key role in simplifying property searches.

3. News aggregators

Scrape news websites to build a real-time news aggregator. You can provide users with a one-stop news platform by categorizing articles by topics, such as politics, technology, or sports. You can modify this to be sent to users based on importance, e.g., politics or environmental news.

Why it’s a good idea:
News is published across countless platforms, and aggregators help users access diverse perspectives in one place. It saves users time and provides centralized access to global news.

How to approach it:

• Leverage RSS feeds for efficient updates and enhance user experience with filters and notifications.
• Scrape headlines, summaries, and publication dates from trusted news sources.
• Use ScraperAPI to bypass paywalls and scraping restrictions.
• Organize content by category (e.g., politics, technology, sports).

Tools to use:

• ScraperAPI (for scalable and reliable scraping)
• BeautifulSoup (for content extraction)
• Pandas (for data organization)

Importance in 2025:
In an era of rapid information consumption, news aggregators will continue to play a crucial role in combating information overload.

4. Job board creation

Gather job listings from multiple sources to create a centralized job board. Include industry, location, salary, and company filters to make the platform user-friendly.

Why it’s a good idea:
Job seekers often miss opportunities that are spread across multiple platforms. Aggregators streamline job hunting by centralizing listings from various sources.

How to approach it:

• Identify major job portals (e.g., LinkedIn, Glassdoor, Indeed).
• Begin with a niche market (e.g., tech jobs) before scaling.
• Use ScraperAPI to bypass anti-bot systems and extract job titles, locations, and descriptions.
• Enable advanced search and filtering features.

Tools to use:

• ScraperAPI (for efficient large-scale scraping)
• BeautifulSoup (for HTML parsing)
• Pandas (for organizing extracted data)

Importance in 2025:
As remote work and global hiring grow, job board aggregators will become essential tools for job seekers and recruiters.

5. Product review aggregators

Collect reviews from multiple platforms to provide consumers with comprehensive product insights. Highlight pros, cons, and everyday consumer experiences.

Why it’s a good idea:
Consumers rely on product reviews before making purchases. Aggregators simplify decision-making by collecting reviews from multiple sources.

How to approach it:

• Scrape reviews, ratings, and user comments from e-commerce and review sites.
• Use ScraperAPI to manage high request volumes without blocks.
• Organize reviews by product category and sentiment analysis.

Tools to use:

• ScraperAPI (for bypassing bot protection)
• BeautifulSoup (for data parsing)
• Pandas (for sentiment analysis and organization)

Importance in 2025:
As e-commerce grows, review aggregators will be vital for building consumer trust and enabling informed purchase decisions.

6. Social media sentiment analysis

Scrape posts, comments, and hashtags from social media platforms to analyze sentiment trends. This data is valuable for marketing, product development, or tracking brand reputation.

Why it’s a good idea:
Brands need to understand customer opinions and trends to improve engagement and strategy (Provides actionable insights for brands and organizations).

How to approach it:

• Focus on a specific platform initially, then expand coverage.
• Scrape comments, likes, shares, and hashtags from social media platforms.
• Use ScraperAPI to bypass rate limits and anti-bot measures.
• Apply sentiment analysis to understand public opinion.

Tools to use:

• ScraperAPI (for scalable data extraction)
• TextBlob (for sentiment analysis)
• Pandas (for data manipulation)
• Tweepy (accessing Twitter API with Python)

Importance in 2025:
As digital engagement grows, sentiment analysis will remain a critical tool for understanding audience behavior.

7. Job salary insights tools

Scrape salary data from job boards, company websites, and employment review platforms to create a comprehensive tool for salary comparisons across industries, roles, and regions.

Why it’s a good idea:
Salary transparency is becoming a priority for job seekers and employers alike. A job salary insights tool can empower professionals to negotiate better pay, help employers set competitive salaries, and provide valuable data for workforce planning.

How to approach it:

• Scrape salary data, job titles, and locations from job boards and company websites.
• Use ScraperAPI to bypass restrictions and avoid IP bans.
• Organize data by job role, industry, and region.

Tools to use:

• ScraperAPI (for large-scale scraping)
• Pandas (for salary data analysis)
• Matplotlib (for visualization)

Importance in 2025:
With increasing focus on pay equity and remote work reshaping salary structures, salary insight tools will become invaluable for job seekers and employers to stay informed about fair compensation practices.

8. Local business directories

Collect data from local business directories to create a comprehensive database of companies in specific industries or regions, including contact details, reviews, and services offered. This can be monetized or used for marketing campaigns.

Why it’s a good idea:
Small businesses benefit from increased visibility, and users rely on centralized directories for local services.

How to approach it:

• Scrape business names, addresses, contact details, and reviews from directories.
• Use ScraperAPI to handle anti-bot systems effectively.
• Create a searchable directory with location and service filters.

Tools to use:

• ScraperAPI (for efficient scraping at scale)
• BeautifulSoup (for parsing business data)
• Pandas (for data analysis and filtering)

Importance in 2025:
With increasing reliance on local services, business directories will remain essential for local economies.

9. LLM training datasets

Gather diverse datasets for training large language models (LLMs). This includes scraping public text, transcripts, forums, and niche content to build robust, domain-specific datasets for AI development.

Why it’s a good idea:
Training data is the backbone of LLMs, and high-quality, diverse datasets are essential for improving their accuracy, reliability, and versatility. As industries adopt AI-driven tools, demand for tailored datasets will continue to grow.

Tools to use:

• ScraperAPI: For scalable and efficient data extraction from various web sources.
• Python: For data parsing, preprocessing, and integration into training pipelines.
• Selenium: To handle dynamic or JavaScript-rendered content.
• GPT Tools: For pre- and post-processing text data to ensure relevance and usability.

How to approach it:

• Identify target sources, including websites, forums, and public datasets.
• Use ScraperAPI to handle large-scale, automated scraping tasks without IP blocks.
• Preprocess data using Python to clean, structure, and remove duplicates.
• Organize datasets into meaningful categories for better AI training results.

Importance in 2025:
The demand for diverse, reliable, and ethically sourced datasets will skyrocket as the AI landscape advances. Companies developing LLMs will prioritize refined data pipelines, and projects that supply high-quality datasets will become indispensable to the AI ecosystem.

10. Event aggregation platforms

Scrape event listings from various sources to build an event aggregator. Include categories such as concerts, conferences, and workshops with details like dates, locations, and ticket prices.

Why it’s a good idea:
Finding events across different platforms can be time-consuming. Aggregators simplify discovery and help users plan effectively.

How to approach it:

• Start with niche event categories.
• Scrape event details, ticket prices, and schedules from event platforms.
• Use ScraperAPI to manage dynamic content and IP restrictions.
• Build filters for event type, location, and date.

Tools to use:

• ScraperAPI (for reliable scraping)
• BeautifulSoup (for parsing event data)
• Pandas (for organizing data)

Importance in 2025:
As virtual and hybrid events become more common, aggregators will be essential for centralized event discovery.

11. Travel comparison tools

Scrape travel websites for flight, hotel, and rental car prices. Build tools that allow users to compare options and secure the best deals.

Why it’s a good idea:
Travelers often spend hours comparing prices across multiple platforms. A travel comparison tool centralizes flight, hotel, and rental car data, offering users time and cost.

How to approach it:

• Identify popular travel platforms (e.g., Expedia, Booking.com, Skyscanner).
• Use ScraperAPI to handle dynamic content and bypass anti-bot mechanisms.
• Extract flight schedules, prices, hotel ratings, and rental car availability.
• Build a user-friendly interface with search and filter functionalities.

Tools to use:

• ScraperAPI (to handle scraping at scale and bypass captchas)
• Selenium (for dynamic content rendering)
• BeautifulSoup (for HTML parsing)
• Pandas (for data manipulation)

Importance in 2025:
As global travel demand surges and dynamic pricing becomes more prevalent, travel comparison tools will be essential for helping users make informed and cost-effective booking decisions.

12. Recipe and food aggregators

Scrape recipes from food blogs and categorize them by cuisine, dietary preferences, or preparation time. Build a searchable cooking platform.

Why it’s a good idea:
As cooking trends evolve and dietary needs become more specific, having a centralized recipe aggregator helps users discover and organize meal options efficiently.

How to approach it:

• Scrape recipes from food blogs, cooking websites, and social media platforms.
• Use ScraperAPI to navigate complex site structures and avoid IP bans.
• Collect data on ingredients, preparation time, cooking difficulty, and dietary tags.
• Organize recipes into searchable categories for ease of use.

Tools to use:

• ScraperAPI (to handle IP rotation and bypass blockers)
• BeautifulSoup (for HTML parsing)
• Pandas (for organizing and categorizing data)

Importance in 2025:
As more people turn to home cooking and specialized diets, recipe aggregators will serve as essential resources for daily cooking and culinary experimentation.

13. Stock market data collection

Scrape stock prices, trading volumes, and financial news to build dashboards for market tracking and analysis. Feed the data into trading algorithms for automated insights.

Why it’s a good idea:
Timely and accurate stock market data is vital for investors, analysts, and trading algorithms to make informed financial decisions.

How to approach it:

• Scrape stock prices, trading volumes, and financial news from market data sources.
• Use ScraperAPI to access real-time stock data while bypassing anti-scraping tools.
• Organize data into dashboards and enable historical trend analysis.

Tools to use:

• ScraperAPI (for reliable scraping of financial data without blocks)
• Pandas (for data organization and analysis)
• Matplotlib (for visualizing trends)

Importance in 2025:
With growing participation in retail and algorithmic trading, accurate and real-time stock data will continue to drive financial decisions.

14. Competitor analysis tools

Scrape data on competitor pricing, marketing strategies, and product offerings. Build insights to inform strategic business decisions.

Why it’s a good idea:
Staying ahead in competitive markets requires ongoing analysis of rivals’ pricing, promotions, and customer feedback.

How to approach it:

• Identify competitor websites and key data points (e.g., pricing, reviews, marketing campaigns).
• Use ScraperAPI to scrape data across multiple sites efficiently.
• Build dashboards to track trends and insights in real time.

Tools to use:

• ScraperAPI (to handle IP rotation and bypass bot detection)
• Pandas (for data manipulation)
• Power BI (for visual analytics)

Importance in 2025:
As markets become more data-driven, competitor analysis tools will be critical for strategic business planning and customer acquisition.

15. Scholarship portals

Aggregate scholarship opportunities from academic websites and centralize them for easy student access. Include filters for eligibility and deadlines.

Why it’s a good idea:
With the rising cost of education, a centralized scholarship platform simplifies the discovery of financial aid opportunities.

How to approach it:

• Scrape scholarship data from university websites, government portals, and scholarship directories.
• Use ScraperAPI to handle anti-bot systems effectively.
• Include details like eligibility criteria, deadlines, and application links.

Tools to use:

• ScraperAPI (for smooth and scalable scraping)
• BeautifulSoup (for HTML parsing)
• Pandas (for data organization)

Importance in 2025:
As tuition costs rise globally, scholarship aggregators will provide students with valuable resources to fund their education.

16. Sports statistics platforms

Scrape live scores, player statistics, and team standings to create dynamic sports dashboards. Cater to fans, analysts, and sports media outlets.

Why it’s a good idea:
Sports fans, analysts, and fantasy league players rely on accurate statistics for predictions, insights, and entertainment.

How to approach it:

• Scrape live scores, player statistics, and historical sports data from official sports websites
• Use ScraperAPI to bypass scrapping restrictions on dynamic and protected content.
• Organize data into real-time dashboards for users.

Tools to use:

• ScraperAPI (for handling frequent requests and bypassing captchas)
• Pandas (for data analysis)
• Matplotlib (for data visualization)

Importance in 2025:
With the growing popularity of fantasy sports and sports betting, accurate data tools will continue to attract a massive audience.

17. Educational content aggregators

Collect course information from online education platforms to allow users to compare programs, pricing, and certifications.

Why it’s a good idea:
Students and professionals benefit from having a one-stop platform to compare online courses, certifications, and academic programs.

How to approach it:

• Scrape course details, pricing, and reviews from Coursera, Udemy, and university websites.
• Use ScraperAPI to handle dynamic content and prevent IP bans.
• Build search filters for easier course discovery.

Tools to use:

• ScraperAPI (for large-scale scraping)
• BeautifulSoup (for parsing)
• Pandas (for data analysis)

Importance in 2025:
As e-learning adoption grows, educational aggregators will play a crucial role in helping users make informed learning choices.

18. Weather data dashboards

Scrape weather forecasts and historical data to create real-time dashboards or seamlessly integrate weather insights into existing platforms and applications. These dashboards can provide location-specific updates, severe weather alerts, and trend analysis, empowering users across industries to make informed decisions.

Why it’s a good idea:
Weather data impacts daily life, agriculture, logistics, and emergency planning. Real-time updates empower authorities and citizens to prepare for natural disasters like hurricanes, floods, or storms, ensuring timely responses and risk mitigation.

How to approach it:

• Scrape weather forecasts and historical data from weather APIs and websites.
• Use ScraperAPI to ensure reliable and consistent data extraction.
• Present the data in user-friendly dashboards.

Tools to use:

• ScraperAPI (for seamless data scraping)
• Pandas (for data manipulation)
• Matplotlib (for visualization)

Importance in 2025:
With increasing climate unpredictability, accurate and accessible weather dashboards will be more valuable than ever.

19. Fashion trend trackers

Scrape data from fashion blogs, retail websites, and social media to monitor emerging trends and predict upcoming styles.

Why it’s a good idea:
Fashion brands and retailers depend on trend analysis for timely design and inventory decisions.

How to approach it:

• Scrape fashion blogs, e-commerce sites, and social media for trending styles and products.
• Use ScraperAPI to avoid IP blocks and ensure data consistency.

Tools to use:

• ScraperAPI (for scalable scraping)
• BeautifulSoup (for parsing)
• Pandas (for organizing data)

Importance in 2025:
With fast fashion and sustainability trends shaping the industry, data-driven insights will drive decision-making.

20. Public opinion surveys

Scrape forums, comments, and polls to gauge public sentiment on trending topics, products, or social issues.

Why it’s a good idea:
Public sentiment is essential for marketing campaigns, political strategy, and product development.

How to approach it:

• Scrape social media, forums, and comment sections.
• Use ScraperAPI for seamless data extraction at scale.

Tools to use:

• ScraperAPI (for large-scale scraping)
• Sentiment Analysis Libraries (e.g., TextBlob)
• Pandas (for analysis)

Importance in 2025:
With public discourse increasingly shifting online, sentiment analysis will continue to shape decision-making in multiple industries.

21. Niche marketplaces

Scrape data for specialized products like eco-friendly goods, collectibles, or handmade items to build niche-focused e-commerce platforms.

Why it’s a good idea:
Niche marketplaces focus on specific audiences, such as collectors or eco-conscious shoppers, offering tailored experiences and products often overlooked by larger platforms.

How to approach it:

• Identify niche product categories (e.g., vintage goods, handmade crafts, eco-friendly products).
• Use ScraperAPI to extract product data, pricing, and seller details from relevant platforms.
• Organize data into searchable categories for better user experience.

Tools to use:

• ScraperAPI (for handling IP blocks and dynamic content)
• BeautifulSoup (for parsing product pages)
• Pandas (for data categorization)

Importance in 2025:
As consumers seek more personalized shopping experiences, niche marketplaces will thrive by catering to specific communities.

22. Affiliate marketing tools

Scrape product data, pricing, and affiliate program details to help marketers identify high-converting offers and optimize campaigns.

Why it’s a good idea:
Affiliate marketers rely on product data and pricing insights to optimize campaigns. Aggregating this data helps them focus on high-converting offers.

How to approach it:

• Scrape product details, affiliate links, and commission structures from affiliate platforms.
• Use ScraperAPI to manage large-scale scraping without bans.
• Build dashboards to compare affiliate opportunities.

Tools to use:

• ScraperAPI (for bypassing anti-bot measures)
• BeautifulSoup (for parsing product details)
• Pandas (for organizing affiliate data)

Importance in 2025:
As affiliate marketing grows, reliable tools will become essential for identifying profitable opportunities and optimizing strategies.

23. AI-powered chatbots

Scrape conversational data from public forums and chat platforms to train AI-powered chatbots for customer service or marketing purposes.

Why it’s a good idea:
High-quality conversational data is essential for training AI chatbots. Scraping real-world conversations helps improve chatbot responses and accuracy.

How to approach it:

• Scrape FAQs, support forums, and chat logs from public websites.
• Use ScraperAPI to handle dynamic and paginated content.
• Process and clean data for chatbot training datasets.

Tools to use:

• ScraperAPI (for large-scale conversational data extraction)
• BeautifulSoup (for parsing chat content)
• Pandas (for dataset structuring)

Importance in 2025:
As AI chatbots become more integrated into customer service, high-quality training data will remain essential for better user interactions.

24. Historical archives

Scrape old websites, news articles, and public databases to preserve historical information for researchers and enthusiasts.

Why it’s a good idea:
Preserving historical content, such as old articles, forums, and records, provides researchers, historians, and enthusiasts with valuable resources.

How to approach it:

• Identify archival sources (e.g., old websites, public databases).
• Use ScraperAPI to extract large datasets without interruptions.
• Organize data chronologically or thematically for easy access.

Tools to use:

• ScraperAPI (for reliable access to historical archives)
• BeautifulSoup (for content parsing)
• Pandas (for organizing datasets)

Importance in 2025:
In an era of rapid digital change, historical archives ensure valuable information isn’t lost to time.

25. Cryptocurrency tracking tools

Scrape real-time and historical data from cryptocurrency exchanges to create price tracking and market analysis dashboards.

Why it’s a good idea:
Cryptocurrency markets are highly volatile, and real-time tracking tools help traders and investors make informed decisions.

How to approach it:

• Scrape cryptocurrency prices, trading volumes, and historical data from exchanges.
• Use ScraperAPI to manage API rate limits and IP restrictions.
• Build dashboards with real-time updates and alerts.

Tools to use:

• ScraperAPI (for bypassing restrictions on exchange APIs)
• BeautifulSoup (for parsing exchange data)
• Pandas (for analyzing trends)

Importance in 2025:
As cryptocurrency adoption increases, tracking tools will become essential for market analysis and investment strategies.

26. Public data for advocacy

Scrape publicly available government and NGO data to support research and advocacy campaigns with actionable insights.

Why it’s a good idea:
Advocacy campaigns and policy research often rely on publicly available data. Scraping helps compile information efficiently.

How to approach it:

• Scrape public data from government and NGO websites.
• Use ScraperAPI to handle complex site structures and prevent blocks.
• Organize data into actionable insights and reports.

Tools to use:

• ScraperAPI (for large-scale data extraction)
• BeautifulSoup (for parsing public records)
• Pandas (for data analysis and filtering)

Importance in 2025:
Data-driven advocacy will become increasingly crucial for driving policy changes and raising public awareness.

27. Real-time alert systems

Scrape websites for updates on price changes, stock availability, or breaking news and trigger automated real-time alerts.

Why it’s a good idea:
Real-time alerts enable users to act quickly on opportunities like price drops, stock availability, or breaking news.

How to approach it:

• Scrape websites for price changes, stock status, or critical updates.
• Use ScraperAPI to ensure consistent monitoring without interruptions.
• Implement automated notification systems (e.g., email or SMS alerts).

Tools to use:

• ScraperAPI (for monitoring and scaling)
• BeautifulSoup (for content extraction)
• Pandas (for tracking changes)

Importance in 2025:
Real-time alerts will remain crucial for consumers and businesses looking to capitalize on time-sensitive opportunities.

28. Art and design inspiration portals

Scrape art and design portfolios to build inspiration hubs for creatives categorized by themes, styles, and mediums.

Why it’s a good idea:
Creative professionals often seek inspiration from art, design, and photography. Aggregating creative content simplifies discovery.

How to approach it:

• Scrape art portfolios, design blogs, and photography websites.
• Use ScraperAPI to handle dynamic galleries and pagination.
• Categorize inspiration by style, medium, and theme.

Tools to use:

• ScraperAPI (for accessing large image datasets)
• BeautifulSoup (for parsing metadata)
• Pandas (for organizing collections)

Importance in 2025:
As digital creativity grows, centralized inspiration hubs will become go-to resources for professionals.

29. Retail inventory trackers

Scrape product availability from retail websites to monitor stock levels, identify shortages, and track restocking trends.

Why it’s a good idea:
Inventory trackers help businesses monitor stock levels and prevent supply chain disruptions.

How to approach it:

• Scrape stock availability data from retail websites.
• Use ScraperAPI to bypass IP restrictions and anti-bot systems.
• Build dashboards with low-stock alerts and inventory trends.

Tools to use:

• ScraperAPI (for handling anti-bot mechanisms)
• BeautifulSoup (for parsing stock data)
• Pandas (for inventory analysis)

Importance in 2025:
Inventory tracking will play a critical role in managing supply chains efficiently amid fluctuating demand.

30. Pet adoption aggregators

Scrape animal shelter websites to centralize pet adoption listings, categorized by species, breed, and location, simplifying the adoption process.

Why it’s a good idea:
Centralized pet adoption platforms simplify the search for pets needing homes and increase adoption rates.

How to approach it:

• Scrape data from animal shelters and pet adoption websites.
• Use ScraperAPI to handle dynamic pages and IP restrictions.
• Organize listings by location, pet type, and adoption requirements.

Tools to use:

• ScraperAPI (for scalable scraping)
• BeautifulSoup (for parsing pet listings)
• Pandas (for data filtering and presentation)

Importance in 2025:
With growing awareness around pet adoption, aggregators will play a key role in connecting animals with loving homes.

Tips to ensure your web scraping projects go smoothly

• Respect website policies: Always check the terms of service before scraping a website.
• Use rotating proxies: Prevent IP bans by using a proxy service to rotate IPs.
• Implement error handling: Anticipate and handle common scraping errors like timeouts or captchas.
• Schedule scraping tasks: Use scheduling tools to scrape data at regular intervals.
• Store data efficiently: Choose a suitable database to manage and query your scraped data effectively.

FAQ about projects to learn web scraping