In advanced mode diffserver builds up a history of changes across entire competition sites and market segments allowing complex data mining of behavior.
Beyond simple change detection lies the real power and future of Diffserver. As Diffserver retrieves and analyzes pages it builds statistics on page changes across products, markets, brands and services. This raw data allow us to ask questions across the system, examples of these questions might be:
- for a brand tell me all the price changes that have occurred in the last 6 months
- for a generic product tell me the average specifications across a named list of manufacturers
- given a price and product, tell me all brands that manufacture within that market
- given the following market segment, name the most promoted to least promoted brand
- what is the most active brand in this named market segment
- what brand is the most aggressive on price changes in the last 2 years
These questions are viable queries that can be run against the Diffserver cluster today, the more pages Diffserver retrieves on a regular basis, the more accurate the results become.