COMPETITOR PREDICTION TOOL

• US 20150081392A1
• Filed: 09/17/2013
• Published: 03/19/2015
• Est. Priority Date: 09/17/2013
• Status: Abandoned Application

• Current Assignee: Kalibrate Technologies Ltd. (Hanover Investors Management LLP)
• Original Assignee: Kalibrate Technologies Ltd. (Hanover Investors Management LLP)
• Inventors: Fox, David, Zeng, Xiaojun
• Application Number:
  US14/029,432
• Publication Number:
  US 20150081392A1
• Time in Patent Office: Days
• US Class Current: 705/7.35
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors

Abstract

A method of generating fuel price data for a retail fuel site. The method comprises receiving relationship data indicating a relationship between the retail fuel site and a competitor retail fuel site and receiving fuel price data for the competitor retail fuel site. The fuel price data for the competitor retail fuel site is processed to generate estimated fuel price data for the competitor retail fuel site and the fuel price data for the retail fuel site is generated based upon the relationship data and the estimated fuel price data.

Claims

1-41. -41. (canceled)

42. A computer-implemented method of generating fuel price data for a retail fuel site, the method being implemented in a computer comprising a memory in communication with a processor, the method comprising:

receiving, as input to the processor, relationship data indicating a relationship between the retail fuel site and a competitor retail fuel site;

receiving, as input to the processor, fuel price data for the competitor retail fuel site;

processing, by the processor the fuel price data for the competitor retail fuel site to generate estimated fuel price data for the competitor retail fuel site; and

generating, by the processor, said fuel price data for the retail fuel site based upon the relationship data and the estimated fuel price data.

43. The method of claim 42, wherein said estimated fuel price data for the competitor retail fuel site is a prediction of fuel price for the competitor retail fuel site at a time in the future.

44. The method of claim 42, wherein said estimated fuel price data for the competitor retail fuel site is an estimate of historical fuel price for the competitor retail fuel site that is unavailable.

45. The method of claim 42, wherein said fuel price data for the competitor retail fuel site comprises a value for each of a plurality of variables associated with the competitor retail fuel site.

46. The method of claim 45, wherein said plurality of variables associated with the competitor retail fuel site comprises at least one value selected from the group consisting of:

a value indicating a current weekday;

a value indicating a time for which a prediction is to be made;

a value indicating a current cost difference between a fuel price at the competitor retail fuel site at first and second times;

a value indicating a difference between fuel price at the retail fuel site at a first time and fuel price at the competitor retail fuel site at a second time;

a value indicating a change in fuel price at the retail fuel site since a previous a change in fuel price at the competitor retail fuel site; and

a time since a most recent competitor price change.

47. The method of claim 42, wherein processing the fuel price data for the competitor retail fuel site to generate estimated fuel price data for the competitor retail fuel site comprises:

receiving, as input to the processor, a model; and

processing, by the processor, the fuel price data for the competitor retail fuel site based upon the received model.

48. The method of claim 47, wherein said model is a support vector regression model.

49. The method of claim 47, further comprising generating said model, said generating comprising:

receiving, as input to the processor, a training set of data, said training set of data providing fuel price data for the competitor retail fuel site at a plurality of times; and

processing, by the processor, the training set of data using a quadratic programming method to determine at least one Lagrangian multiplier.

50. The method of claim 49, wherein said training of set of data comprises an observed price for the competitor retail fuel site at each of said plurality of times, and wherein processing the training set of data to determine at least one Lagrangian multiplier comprises, for each of said plurality of times:

determining, by the processor, an estimated price for the competitor site for said plurality of times;

determining, by the processor, whether a difference between said estimated price and said observed price exceeds a predetermined value; and

if said difference exceeds a predetermined value, assigning, by the processor, a penalty to said data for said time.

51. The method of claim 47, wherein said model comprises an average value.

52. The method of claim 47, wherein said average value is generated based upon a training set of data providing fuel price data for the competitor retail fuel site at a plurality of times.

53. The method of claim 42, further comprising:

receiving at least one bound associated with the competitor retail fuel site; and

generating said estimated fuel price data for the competitor retail fuel site based upon the at least one bound.

54. The method of claim 53, wherein said at least one bound is associated with a maximum change of fuel price data at the competitor retail fuel site.

55. An intangible computer readable medium carrying a computer program comprising computer readable instructions configured to cause a computer to carry out a method comprising:

receiving, as input to the processor, relationship data indicating a relationship between the retail fuel site and a competitor retail fuel site;

receiving, as input to the processor, fuel price data for the competitor retail fuel site;

processing, by the processor the fuel price data for the competitor retail fuel site to generate estimated fuel price data for the competitor retail fuel site; and

generating, by the processor, said fuel price data for the retail fuel site based upon the relationship data and the estimated fuel price data.

56. A computer apparatus for generating fuel price data for a retail fuel site, the apparatus comprising:

a memory storing processor readable instructions; and

a processor arranged to read and execute instructions stored in said memory;

wherein said processor readable instructions comprise instructions arranged to control the computer to carry out a method comprising;

receiving, as input to the processor, relationship data indicating a relationship between the retail fuel site and a competitor retail fuel site;

receiving, as input to the processor, fuel price data for the competitor retail fuel site;

processing, by the processor the fuel price data for the competitor retail fuel site to generate estimated fuel price data for the competitor retail fuel site; and

generating, by the processor, said fuel price data for the retail fuel site based upon the relationship data and the estimated fuel price data.