ParsePilot

1. Define the target e-commerce websites and product pages.

2. Use the visual selector to identify product names, prices, and availability indicators.

3. Configure pagination handling to extract data from all product pages.

4. Schedule the extraction to run daily.

5. Export the extracted data to a CSV file for analysis.

1. Identify the real estate websites to scrape.

2. Use the visual selector to extract property details like address, price, and number of bedrooms.

3. Configure the scraper to handle dynamic content loading.

4. Implement data transformation to standardize addresses and prices.

5. Export the extracted data to a JSON file and load it into a database.

1. Select the target review websites and product forums.

2. Use the visual selector to extract review text, ratings, and author information.

3. Implement sentiment analysis to categorize reviews as positive, negative, or neutral.

4. Schedule the extraction to run bi-weekly.

5. Analyze the extracted data to identify trends and customer sentiment.

1. Define target news websites.

2. Configure the scraper to extract article titles, content, and publication dates.

3. Set up filters to extract articles based on keywords or categories.

4. Schedule the extraction to run hourly.

5. Store the extracted articles in a database for further analysis.

1. Select the target job board websites.

2. Use the visual selector to extract job titles, descriptions, and company information.

3. Configure pagination to extract data from all job listing pages.

4. Normalize the extracted data to ensure consistency across different job boards.

5. Export the extracted data to an Excel file for easy review.

1. Authenticate with the social media platform's API.

2. Define the keywords and hashtags to track.

3. Extract relevant posts, comments, and user profiles.

4. Analyze the extracted data to identify trends and influencers.

5. Generate reports to summarize brand sentiment and engagement.

1. Identify the travel websites to scrape.

2. Configure the scraper to extract flight prices, hotel rates, and availability.

3. Handle dynamic content to extract data from AJAX-driven websites.

4. Implement data transformation to standardize currencies and dates.

5. Store the extracted data in a database for real-time querying.