Frequency: Determine whether data scraping will be real-time, scheduled (e.g., daily or weekly), or on-demand

1. Real-Time Data Scraping

• What It Is: Data is collected and updated as it becomes available, almost instantaneously.
• When to Choose This: Real-time scraping is suitable for cases where you need up-to-the-minute updates, such as tracking stock levels, monitoring rapidly changing prices, or getting alerts on new product listings.
• Benefits: Provides the most current and accurate information. Ideal for competitive markets where decisions must be based on the latest data.
• Drawbacks: Requires a robust and scalable infrastructure, which can be expensive and complex to maintain. Not always necessary for businesses that don't require constant updates.

2. Scheduled Data Scraping

• What It Is: Data scraping occurs at regular intervals (e.g., hourly, daily, or weekly).
• When to Choose This: A good option if your business needs regular updates but doesn't require real-time accuracy. For example, you could schedule daily scraping to keep product catalogs, price comparisons, or inventory lists up to date.
• Benefits: Cost-effective compared to real-time scraping. Ensures data freshness while being less resource-intensive.
• Drawbacks: There might be a lag between updates, which can be problematic if product information changes frequently or if your competitors are using more up-to-date data.

3. On-Demand Data Scraping

• What It Is: Data is collected only when requested, either manually or via a trigger in your system.
• When to Choose This: Suitable for one-time or occasional needs, like a specific market research project or checking product details when launching a new product line.
• Benefits: Very cost-effective, as resources are used only when needed. Flexible and easy to implement for one-off tasks.
• Drawbacks: Not suitable for applications that need continuous or regular updates. Might require manual intervention, which can slow down decision-making.

• How Often the Data Changes: If the product information (e.g., prices or stock levels) is highly dynamic, real-time or frequent scheduled updates are preferable.
• Business Needs: Do you need the most current data for decision-making, or are regular updates sufficient?
• Budget Constraints: Real-time scraping is more expensive due to the continuous infrastructure use, while scheduled and on-demand options are more cost-effective.
• Infrastructure and Resources: Ensure your systems can handle the data volume and frequency of updates.