Dynamic Pricing Engine for Wireless Ad Revenue Optimization

The patent introduces search engines as intermediary systems between customers and e-commerce sites. These search engines analyze customer search queries and return targeted lists of relevant e-commerce sites, acting as a mediator that connects customers who are unsure where to look with the appropriate shopping destinations. This resolves the contradiction by enhancing customer capture efficiency through the intermediary's ability to match customer needs with relevant sites.

The patent implements feedback mechanisms where e-commerce sites provide information about their products, pricing, and customer service quality to search engines. The search engines then use this feedback to refine their search results and provide more accurate recommendations to customers. This feedback loop improves customer acquisition by ensuring that customers are directed to sites that best meet their needs.

The patent segments the information retrieval process by having the search engine divide and conquer the task of finding relevant e-commerce sites. Instead of requiring customers to manually open multiple screens to compare information, the search engine segments the search space into manageable results based on customer queries, pre-processing and organizing information before presentation to the customer.

The search engine performs preliminary actions by pre-analyzing customer search queries and pre-compiling lists of relevant e-commerce sites before the customer even begins their shopping journey. This preliminary processing reduces the time customers would otherwise spend opening multiple screens and manually comparing information, as the relevant sites are already identified and presented in an organized manner.

The patent implements comprehensive feedback mechanisms that track customer behavior across multiple screens and e-commerce sites. By monitoring what customers view, click on, and ultimately purchase, the system gathers detailed feedback data about advertising effectiveness. This feedback is then used to precisely measure the impact of advertisements on customer procurement and product profitability, resolving the contradiction between system complexity and measurement precision.

The patent replaces traditional mechanical measurement methods (such as simple impression counting) with advanced analytical systems that use data mining, statistical analysis, and behavioral tracking. These computational methods substitute for simpler mechanical counting systems, enabling precise measurement of advertising effectiveness by analyzing complex patterns in customer behavior data rather than relying on basic exposure metrics.

The patent merges multiple functions into an integrated pricing and procurement support system. Instead of having separate systems for calculating net margin, adjusting bid/cost, and making procurement decisions, the patent combines these functions into a unified system that processes all calculations and decisions in real-time. This integration resolves the contradiction by enabling fast decision-making through consolidated processing, even though the system complexity increases.

The patent implements dynamic pricing and procurement adjustments that automatically adapt to changing market conditions, customer behavior, and advertising costs in real-time. The system continuously updates net margin calculations and bid/cost adjustments based on current data, making the pricing system dynamic rather than static. This dynamic approach enables rapid decision-making by automatically responding to changing conditions without requiring manual intervention, despite the increased computational complexity.