• Scheduling scrapes during promotional events, like Grab’s birthday or holiday sales, ensures I capture the most relevant discounts.

If the store’s API isn’t open, I scrape only publicly available information, like product descriptions and prices, to respect their terms.

• For dynamic content, integrate Selenium with Java to fully render pages, enabling you to scrape updated product data accurately.

• For extracting reviews, focus on HTML tags associated with user feedback, like .review-text and .rating-stars, to ensure accuracy.

For region-specific trends, I adjust the API’s location parameter, allowing me to gather insights on trending topics in specific countries or cities.

For dynamically loaded data, Chromedp in Go is ideal, allowing for headless browsing and capturing elements like reviews and availability.

• Use PHP with headless Chrome through the symfony/panther package to handle MediaMarkt’s dynamically loaded product listings.

Setting my scraper to run periodically during peak sale times, like Black Friday or Prime Day, lets me capture the most relevant deals.

• For dynamically loaded elements like availability or reviews, combine Nokogiri with Watir, a Ruby browser automation tool, to render content.

• Rotating IP addresses helps avoid detection, especially when accessing popular restaurant listings with high review volumes.