Coupa Software Inc.

Vincent Toesca

Scott Harris

Ahmad Sadeddin

Prasanna Kumar

Amit Vijayant

Kira Letskina

Donna Wilczek

David Williams

Parand Tony Darugar

Techniques for community-based spend analysis in a software-as-a-service computing environment are disclosed. For example, embodiments disclose a method that may include receiving, at a spend management computer system (SMCS) instance of a region, a request for one or more optimization recommendations. The method may include analyzing, by the SMCS instance of the region, spend data, and determining, based on the analyzed spend data, community-based spend comparison information. The method may include causing display of a graphical user interface (GUI) that includes the community-based spend comparison information, and causing displaying in the GUI of one or more filtering options configured to filter the spend comparison information. The method may further include, in response to the request for one or more optimization recommendations, causing displaying in the GUI of a recommendation associated with the community-based spend comparison information.

Community-based data analysis in a software-as-a-service system using a deep learning classifier

Techniques are disclosed for improving spend approval cycle time in a software-as-service (SasS) electronic spend management system based on community spend approval information. The techniques include the spend management system collecting information about spend approval cycle times across a community of users that use the system. A graphical user interface is then provided by the spend management system to individual customer users of the spend management system where the graphical user interface includes a graphical comparison of the user's individual spend approval cycle time performance against the community's spend approval cycle time performance. By doing so, the individual user can be motivated to improve or maintain his or her spend approval cycle time performance.

Community influenced approval cycle times in a software-as-a-service system

Techniques for community-based spend analysis in a software as a service computing environment are disclosed. The techniques leverage information available about community spend to provide new insights into a particular customer's spend. The new insights result from receiving a request for an optimization recommendation, importing spend data comprising a plurality of spend data lines, and using a trained deep learning classifier to classify the spend data lines in a set of standard spend categories to compute a first and second aggregate of monetary amounts. An optimization recommendation is sent to the customer based on a comparison of the first and second aggregate of monetary amounts is sent to a particular customer.

A method and apparatus for generating recommendation data for cataloging items in an e-procurement system is provided. In various embodiments, a database of records is created and maintained corresponding to a plurality of transactions in an e-procurement system. In various embodiments, database records are weighted and sorted according a transaction method associated with the records. In various embodiments, recommendation data is generated for items associated with the records to suggest more efficient methods for offering items for procurement in an e-marketplace based on the weights and sort order of the records.

Catalog enablement data for supplier systems based on community activities

Techniques for community-based spend analysis in a software as a service computing environment are disclosed. The techniques leverage information available about community spend to provide new insights into a particular customer's spend. The new insights result from using a trained deep learning classifier to classify spend data lines from both the community of customers and the particular customer in standard spend categories. The spend data lines may be from invoices, requisitions and purchase orders, for example. According to some of the techniques, after classifying the spend data lines in standard spend categories, a highly accurate community-based comparison between spend of the community versus spend of the particular customer in one or more particular standard spend categories is provided in a graphical user interface.

Techniques for tracking software platform utilization by a plurality of entities are described herein. In an embodiment, a management computer system stores first entity data defining a first entity and associating the first entity with a plurality of first accounts, the first entity having access to the management computer system programmed which provides options for performing a plurality of tasks. The management computer system tracks a first plurality of interactions with the management computer system that are performed by each of the plurality of first accounts. The management computer system stores first interaction data defining one or more aspects of interaction with the management computer system that are performed by each of the plurality of first accounts. The management computer system stores second entity data defining a plurality of second entities and associating each of the plurality of second entities with a plurality of second accounts. The management computer system tracks a second plurality of interactions with the management computer system that are performed by each of the plurality of second accounts. The management computer system stores second interaction data defining the one or more aspects of interaction with the management computer system performed by each of the plurality of second accounts. The management computer system computes one or more first metrics for the first entity based, at least in part, on the tracked first interaction data. The management computer system computes one or more second metrics for the plurality of second entities based, at least in part, on the tracked second interaction data. The management computer system generates a display comprising a comparison between the one or more first metrics for the first entity and the one or more second metrics for the plurality of second entities.

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San Francisco, CA, United States of America

Vincent Toesca