Predicting whether a party will purchase a product

• US 9,733,917 B2
• Filed: 02/20/2013
• Issued: 08/15/2017
• Est. Priority Date: 02/20/2013
• Status: Active Grant

• Current Assignee: Ivanti, Inc. (Ivanti Software, Inc.)
• Original Assignee: Crimson Corporation
• Inventors: Lehner, Brandon
• Primary Examiner(s): Singh, Gurkanwaljit
• Application Number:
  US13/771,753
• Publication Number:
  US 20140236674A1
• Time in Patent Office: 1,637 Days
• Field of Search: None
• CPC Class Codes: G06F 3/01 Input arrangements or combined input and output arrangements for interaction between user and computer G06F3/16 takes precedence
• CPC Class Codes: G06F 8/61 Installation
• CPC Class Codes: G06F 9/445 Program loading or initiating bootstrapping G06F9/4401; security arrangements for program loading or initiating G06F21/57
• CPC Class Codes: G06F 9/452 Remote windowing, e.g. X-Window System, desktop virtualisation protocols for virtual reality H04L67/131
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

A method for predicting whether a party will purchase a product. The method includes accessing data wherein the data is obtained from a plurality of computing environments of a plurality of parties, analyzing the data; and predicting whether one of the plurality of parties will purchase a product based on the analyzed data.

Claims

1. A computer-implemented method for predicting whether a party will purchase a product, said method comprising:

downloading a scan utility to a plurality of computing environments of a plurality of parties, wherein an installed version of the scan utility does not remain on the computing environments after scanning, wherein an executable file for the scan utility remains in temporary storage on the computing environments after the scanning;

receiving data wherein said data is scanned from the plurality of computing environments using the scan utility on each of the plurality of computing environments;

accessing the data;

analyzing said data by a machine learning algorithm on a cloud environment, wherein said cloud environment is in electronic communication with said plurality of computing environments, wherein said analyzing is performed by a hardware processor of said cloud environment, and wherein said analyzing said data by a machine learning algorithm further comprises grouping said plurality of parties into clusters based on a plurality of properties; and

predicting whether one of said plurality of parties will purchase a product based on analyzing the data that indicates a software configuration of at least one of the computing environments.

2. The computer-implemented method of claim 1, wherein said accessing data further comprises:

accessing data, by a vendor, wherein at least one of said plurality of parties is a user of a product of said vendor.

3. The computer-implemented method of claim 1, wherein said predicting whether one of said plurality of parties will purchase a product further comprises:

predicting whether one of said plurality of parties will accept an upsell offer.

4. The computer-implemented method of claim 1, wherein said predicting whether one of said plurality of parties will purchase a product further comprises:

predicting which one of said plurality of parties will most likely accept an upsell offer.

5. The computer-implemented method of claim 1, wherein said predicting whether one of said plurality of parties will purchase a product further comprises:

predicting whether a potential new customer of a vendor will purchase a product of said vendor.

6. The computer-implemented method of claim 1, wherein said predicting whether one of said plurality of parties will purchase a product further comprises:

predicting revenue generation of said plurality of parties.

7. The computer-implemented method of claim 1, further comprising:

providing a notification of said prediction.

8. The computer-implemented method of claim 7, wherein said providing a notification further comprises:

providing a notification to a management team of a vendor.

9. The computer-implemented method of claim 7, wherein said providing a notification further comprises:

automatically providing a notification to said one of said plurality of parties predicted to purchase said product from a vendor.

10. The computer-implemented method of claim 7, further comprising:

prioritizing which of said plurality of parties to provide an upsell offer.

11. A system comprising:

a cloud environment having a hardware processor and a tangible computer-readable medium in electronic communication with said hardware processor, wherein the cloud environment downloads a scan utility to a plurality of computing environments of a plurality of parties, wherein an installed version of the scan utility does not remain on the computing environments after scanning, wherein an executable file for the scan utility remains in temporary storage on the computing environments after the scanning;

a database stored on said tangible computer-readable medium comprising data obtained from the plurality of computing environments of a plurality of parties, wherein the data was received from the scan utility on each of the plurality of computing environments;

a data analyzer to analyze said data by a machine learning algorithm on said cloud environment, wherein said cloud environment is in electronic communication with said plurality of computing environments, wherein said analyzing is performed by said hardware processor of said cloud environment, and wherein said analyzing said data by a machine learning algorithm further comprises grouping said plurality of parties into clusters based on a plurality of properties; and

a product purchase predictor to predict whether one of said plurality of parties will purchase a product based on analyzing the data that indicates a software configuration of at least one of the computing environments.

12. The system of claim 11, further comprising:

a notification generator to generate a notification of said prediction.