QuickStudy: Revenue Optimization Software
Computerworld - Just about all any business is looking for is a way to maintain precisely the right amount of product inventory or resources to supply a service and to know the highest possible price the market for its products or services will bear. That would mean no overstocks, no disappointed customers and no write-offs to explain to investors. And the price would always be right to maximize profits.
Until someone comes up with a working crystal ball, revenue optimization software may offer the best hope to companies looking to achieve those goals.
This business intelligence software factors variables such as demand, the cost of a good or service, and the amount of revenue the company needs to be profitable. It then calculates the best sales price for a good or service. When key parameters change, the software revises prices almost instantly.
For example, if a travel company selling space on a cruise ship knows from historical trends that February is a bad month for a particular trip, it can drop the price to a level most likely to close the deal with a given customer.
At the same time, the company's price planners, using a revenue optimization system, can draw data from applications that handle sales and marketing operations, as well as from data repositories containing customer-related information, in order to make their calculations.
The planners can also factor in other variables, such as the cost of the trip at this particular time of the year based on fuel prices or the weather. They can even launch marketing campaigns targeted at the audience most likely to respond to an offer.
"Revenue optimization takes a finite good, factors in demand and comes out with a price," explains Donald Davidoff, vice president of pricing and revenue management at Archstone-Smith, an Englewood, Colo.-based national apartment owner-operator.
Archstone-Smith uses an application from Manugistics Inc. in Rockville, Md., that forecasts the demand and supply for its space to create the best pricing across a variety of leasing scenarios.


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