Clear Demand, Inc.

Sap Ag

Other

Adam N Rosenberg

James A Sills

Jeffrey D Moore

Yetkin Ileri

Brent May

Brian W Bell

William M Chimitt, Jr

The disclosed technology improves the process of generating recommended prices for retail products by optimizing revenue and profit while complying with a set of business rules by assigning a monetary value to each business rule. Then for each decision price that violates a business rule constraint, a penalty value is added to the monetary value. If the monetary value including the penalty is better than an original monetary value, the decision price is included in the recommended prices.

System and method for integrating retail price optimization for revenue and profit with business rules

A demand rule can handle simultaneous retail purchasing options available to users such as brick and mortar, online, mobile, catalog, kiosk, coupon, loyalty, volume discounts, and multiples. The method can include a demand rule for each single purchasing option, a rule for marketing influence, and a rule for partitioning user demand across purchasing options. The demand rule for each single purchasing option, rule for marketing influence, and rule for partitioning user demand across purchasing options can each be measured independently to enable computationally efficient methods for forecasting and sales optimization.

System and method for rule based forecasting in multichannel, multi-offer, and multi-customer-segment environments

Business rules can govern a single price or they can define relationships between different products involving two or more decision prices. One problem that retailers can face is that business rules are generally not codified and are rarely followed consistently, and thus it can be difficult to articulate existing business rules or generate new business rules. However, existing price information inherently contains industry knowledge and experience, even if retailers find it difficult to express that knowledge. The disclosed technology generates business rules by reverse engineering rule bounds and coefficients from existing price information. The reverse engineered rule bounds and coefficients can be used in price optimization to generate recommended prices for retail products that optimize revenue and profit while complying with a set of business rules.

System and method for determining retail-business-rule coefficients from current prices

A method for transforming transactional data into a forecast and confidence interval for controlling a commerce system involves moving goods between members of a commerce system, and recording transaction data related to movement of goods between the members of the commerce system. The transaction data includes price, product, time, and promotion. The model parameters are estimated based on the transactional data using a demand model to generate a forecast of demand for the goods based on a proposed price or promotion. A confidence interval of the certainty associated with the forecast of demand for the goods is determined based on the proposed price or promotion. The forecast of demand for the goods and confidence interval is provided to the commerce system to control the movement of goods based on the forecast of demand for the goods and confidence interval. The forecast and confidence interval can be graphically displayed.

System and method of using demand model to generate forecast and confidence interval for control of commerce system

A method () and system () for providing a promotion plan () for merchandising products () receives base data () for the products () that includes allowable offers () and price rules () that affect the offers (). A margin budget () is established for the promotion plan () that defines an amount of margin an enterprise is willing to forgo for a promotion event implementing the promotion plan (). A scenario () is generated in response to the base data (). The scenario () is optimized to obtain decisions () for the promotion plan () that are constrained by the margin budget (). The promotion plan (), indicating the obtained decisions (), is presented for implementation by the enterprise during the promotion event. The obtained decisions () include a list of the products (), each of which is associated with one offer () and one price rule ().

System and method for optimization of a promotion plan

Markdown optimization may be performed using a computer system. Markdown objectives may include margin maximization or inventor minimization. Markdown schedule optimization uses an efficient, iterative, targeted combinatorial search. First, permissible discount steps are identified, then for each permissible discount step, a subspace of permissible step dates is identified. Elements from the date step subspace and price reduction subspace are combined and evaluated against the markdown objectives. If an improved markdown schedule is located, a new subspace of permissible step dates is defined to search the subregion of the solution space where the improved markdown optimization schedule was identified. Scheduling of inventory allocation from a distribution center is also disclosed.

Method and system for determining price markdown schedule

An articulated phonograph tonearm includes a multipivot parallelogram linkage means for supporting the phonograph cartridge. The linkage means is mounted at one end of a rigid beam. The beam is constrained to move in a plane parallel to the surface of the record and the parallelogram linkage structure forces the cartridge to remain in the same plane as it moves over warps. A stylus is attached to the cartridge and is adapted to ride in the grooves of the record. The stylus rotates about a virtual center which is preferably located on the surface of the record. Several alternative linkage structures are also disclosed. The apparatus is especially effective in minimizing the undesirable effects associated with record warp.

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Scottsdale, AZ, United States of America

Adam N Rosenberg