• Parsing JSON responses in Java enables faster data extraction if travel package details are available via AJAX.

• Organizing data by brand or product type makes it easier to compare similar items, like TVs or appliances, across different sellers.

• I focus on high-priority products only, reducing the number of requests while ensuring key items are monitored for price changes.

If the site provides only a summary of reviews, I set up periodic scraping to capture updates and track changes in ratings over time.

For large inventories, I focus on high-demand products only, which reduces the load on my scraper and avoids unnecessary data collection.

• For video data, frame extraction at specific intervals allows me to capture key visual elements without processing every frame.

Scheduling periodic scrapes enables tracking auction trends, such as price changes as auctions near their end time.

• Randomized delays and IP rotation help reduce detection when frequently accessing popular product listings.

• Organizing rentals by genre or product type makes the data more useful for analysis, allowing me to identify trending items.