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Intelligent Revenue Management


Description

 

Revenue Management is the process of achieving maximum revenue from the sale of perishable assets as well as controlling demand and managing resources, implanted in the forms of capacity allocation, market segmentation, dynamic pricing, markdown pricing, promotional pricing, inventory control, and demand forecasting/optimization. 

Currently, many companies across many industries apply a variety of models in order to maximize revenue and resources across the whole of a product's life-cycle. In the next few years the customer will have more control over when and what they purchase and will put themselves into the heart of the service chain.

The main goal of this project is to maximize the revenue while optimizing the network utilization by driving the customers' demand. The demand for data is usually high at peak times, which causes slow network service whereas the data is underutilized during off-peak times, which is a waste of valuable resources. In addition, allocating optimal capacity for segmented customers based on historical demand data is another feature of this framework.

The project of Intelligent Revenue Management aims to: 

  • Provide a clear understanding of customer data usage behaviors and network health
  • Maximize revenue through variable pricing
  • Alleviate of network resource overload to avoid data traffic congestion
  • Minimize of underutilized network resources
  • Provide an intelligent planning of network resource expansion with the consideration of existing customers' demand.
  • Enhance customer satisfaction through effective data traffic management
  • Identify the bottleneck and suggest intelligent resource distribution based on geographical and time conditions
  • Allocate capacity based on service level agreements and current and past demand data

Having these specific goals in mind and based on the architecture depicted in Figure1. We have developed Intelligent Revenue Management system that optimizes revenue by utilizing AI (Artificial Intelligent) optimization techniques. The system will analyze historical data of network usages and customer demands, and provide different prices/mobile packages in order to maximize the expected revenue.

architecture

Figure 1. Intelligent Revenue Management System Overview

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