Abstract: Customers submit reports to a reporting center. Topic sentences are identified. For each of a plurality of values of k, a separate k-grouping matrix is created from a master matrix by the control circuit. Each k-grouping matrix arranges the topic sentences into k groupings based upon the similarity of words as between different topic sentences. Each of the k-grouping matrices is created at least in part by moving or rearranging some of the rows of the master matrix. The most frequent topic sentences are identified and used to identify an action.

Abstract: Systems and methods are disclosed that enable efficient management of requests for quotations (RFQs) on a large scale. Component cost sheets (CCSs) are used, which are exchanged between a sourcing function in a retailer or distributor organization and multiple suppliers (vendors). A CCS tool receives RFQ data, for example from a user; generates a CCS; transmits the CCS to at least one supplier; and based at least on information entered into the CCS by the supplier, generates a comparison of current product information with historical product information. By having the comparison available, negotiation between sourcing and the supplier is facilitated. For example, the CCS tool can generate a request for an updated CCS, with a reduced cost, and transmit it to the supplier for consideration.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to analyzing and presenting data associated with customer feedback. In some embodiments, a system comprises a display device configured to present a GUI, a database configured to receive and store the customer feedback, and a control circuit including a feedback parsing module configured to retrieve a review for a product, break the review for the product into segments, a sentiment calculation module configured to assign tags associated with aspects of the product to the segments, calculate a sentiment score for each of the segments, and normalize the sentiment score for each of the segments, an aspect weighted rating module configured to calculate an aspect weighted rating for each of the aspects, wherein the aspect weighted rating for each of the aspects represents an importance of each of the aspects, and a presentation module configured to generate the GUI.

Abstract: Customers submit reports to a reporting center. Topic sentences are identified. For each of a plurality of values of k, a separate k-grouping matrix is created from a master matrix by the control circuit. Each k-grouping matrix arranges the topic sentences into k groupings based upon the similarity of words as between different topic sentences. Each of the k-grouping matrices is created at least in part by moving or rearranging some of the rows of the master matrix. The most frequent topic sentences are identified and used to identify an action.

Abstract: In some embodiments, systems, apparatuses, and methods are provided herein useful to calculating and presenting information related to effectiveness of a promotion. In some embodiments, a system comprises a POS system configured to collect sales data for products, a display device configured to present the information related to the effectiveness of the promotion, and a control circuit configured to receive the sales data for products, determine actual sales for a product, calculate baseline sales for the product, calculate halo sales of the affined product, calculate cannibalized sales, calculate one or more of return sales and lost sales, calculate, based on one or more of the actual sales for the product, the baseline sales for the product, the halo sales, the cannibalized sales, the return sales, and the lost sales, a net lift, and present, via the display device, and indication of the net lift.

Abstract: Disclosed is a method and system for identifying an industry specific e-maven by analyzing textual data from social media. The system may collect textual data posted by users on social media. The system may then determine characteristics of the users by analyzing the textual data. The system may further calculate a maven score for the users by using the characteristics. The system may compute an industrial maven score for the users by using the maven scores and an industry adjustment factor. An industry specific e-maven may thus be identified based on the industry adjustment factor.