The Science of Revenue Optimization
Revenue optimization is a facet of scientific micro-market management, through which companies can sustain economic value through opportunities present at the granular level of customer-facing transactions. Revenue optimization is a means for companies with thousands upon thousands of price permutations to establish a rational framework for mastering their demand environments at that granular level of each discrete transaction. These tools help decision-makers to undertake all key activities that extend across the full lifecycle of the pricing process. As with scientists examining biomolecular phenomena in a Petri dish, these opportunities are invisible to the unaided human eye and require advanced technology to aid discovery. In revenue optimization the technology comes in the form of two distinct capabilities: leading-edge scientific modeling and robust computational engineering.
Scientific Modeling – methods grounded in probability-based optimization, nonlinear analysis and other sophisticated mathematical techniques to rationalize and logically arrange a vast amount of transactional information, and
Computational Engineering – raw computing power and software-based solutions to harness data via massively parallel computing technology capable of crunching trillions of calculations per second. This forms the platform for the third critical factor: the human insight and experience necessary to interpret, refine and deliver the opportunities presented.
The scientific models at the heart of revenue optimization are powered by sophisticated mathematical algorithms that identify relationships between a company’s products and the many variables of real-time customer demand. The models establish probabilities that enable decision-makers within the organization to improve the odds of making the right price decisions that lead to maximum revenue and profit generation. This paper will focus on some of the key modeling and computational engineering mechanics that drive Sentrana’s approach to revenue optimization.