公开(公告)号：US11379860B2

公开(公告)日：2022-07-05

申请号：US15410665

申请日：2017-01-19

Applicant: MASTERCARD INTERNATIONAL INCORPORATED

Inventor： Ameya Pathare ,  Brian Pujanauski ,  Simon Krauss ,  Jenna Kanterman ,  Cornelius Kaestner ,  Christopher Piccoli

IPC: G06Q30/00 ,  G06Q30/02

Abstract: Systems and methods for dynamically determining an optimal baseline algorithm for calculating lift values are disclosed. The system receives data associated with a control strategy, and then randomly selects a control location, a time period, and an item that may not be associated with the control strategy but meets the one or more criteria of the control strategy such as relevance and sales volume. Using the randomly selected inputs and a plurality of null baselines values determined by a plurality of null baseline algorithms, the system iteratively calculates a plurality of null lift values for each of the applied plurality of null baselines values to determine a likelihood for a false positive lift for each of the applied plurality of null baselines values. An optimal baseline algorithm is selected from the plurality of null baselines algorithms based on their corresponding likelihood of false positive lifts.

公开(公告)号：US20220335453A1

公开(公告)日：2022-10-20

申请号：US17857579

申请日：2022-07-05

Applicant: Mastercard International Incorporated

Inventor： Ameya Pathare ,  Brian Pujanauski ,  Simon Krauss ,  Jenna Kanterman ,  Cornelius Kaestner ,  Christopher Piccoli

IPC: G06Q30/02

Abstract: Systems and methods for dynamically determining an optimal baseline algorithm for calculating lift values are disclosed. The system receives data associated with a control strategy, and then randomly selects a control location, a time period, and an item that may not be associated with the control strategy but meets the one or more criteria of the control strategy such as relevance and sales volume. Using the randomly selected inputs and a plurality of null baselines values determined by a plurality of null baseline algorithms, the system iteratively calculates a plurality of null lift values for each of the applied plurality of null baselines values to determine a likelihood for a false positive lift for each of the applied plurality of null baselines values. An optimal baseline algorithm is selected from the plurality of null baselines algorithms based on their corresponding likelihood of false positive lifts.

公开(公告)号：US12039553B2

公开(公告)日：2024-07-16

申请号：US17857579

申请日：2022-07-05

Applicant: Mastercard International Incorporated

Inventor： Ameya Pathare ,  Brian Pujanauski ,  Simon Krauss ,  Jenna Kanterman ,  Cornelius Kaestner ,  Christopher Piccoli

IPC: G06Q30/00 ,  G06Q30/0201 ,  G06Q30/0242

CPC classification number: G06Q30/0201 ,  G06Q30/0242

Abstract: Systems and methods for dynamically determining an optimal baseline algorithm for calculating lift values are disclosed. The system receives data associated with a control strategy, and then randomly selects a control location, a time period, and an item that may not be associated with the control strategy but meets the one or more criteria of the control strategy such as relevance and sales volume. Using the randomly selected inputs and a plurality of null baselines values determined by a plurality of null baseline algorithms, the system iteratively calculates a plurality of null lift values for each of the applied plurality of null baselines values to determine a likelihood for a false positive lift for each of the applied plurality of null baselines values. An optimal baseline algorithm is selected from the plurality of null baselines algorithms based on their corresponding likelihood of false positive lifts.