Zilliant Incorporated

Predictix LLC

Loren Williams

Xingchu Liu

Nikolaos Vasiloglou

Shi Zhong

Reetabrata Mookherjee

Emir Pasalic

Embodiments of the present invention relate to systems and methods for determining sets of products which are similar to each other in terms of consumers' wants and needs. Queries are performed on a particular product. Documents relating to the query are received and stored. A dictionary is created from the received documents, whereby the documents, which are text files, are scrubbed of certain data to create a scrubbed text file. Topic modeling is then performed on the cleansed text file. Various methods can be used to perform topic modeling, including, but not limited to, latent semantic analysis, nonnegative matrix factorization, and singular value decomposition.

Systems and methods for identifying sets of similar products

To determine pricing recommendations for goods and service products in a business-to-business environment, a set of transaction data corresponding to a set of products are processed to generate a set of pricing recommendations optimized according to an objective. Furthermore, a set of product segments may be determined, transaction data may be associated with one or more of the product segments and a demand model and associated price elasticity may be formulated for one or more of the product segments based upon the transaction data associated with the segment. Using these formulated price elasticities, pricing recommendations for each product may be determined for each of a set of customers. Using an optimization process, price elasticities are used to determine price dependent entity goals for any combination of products, customers and sets of prices, using a mathematical objective function.

Method and system for generating pricing recommendations

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Decatur, GA, United States of America

Loren Williams