END USER PERFORMANCE ANALYSIS

• US 20150271026A1
• Filed: 03/24/2014
• Published: 09/24/2015
• Est. Priority Date: 03/24/2014
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Tiwana, Pravjit, Meduri, Venkata Kiran Kumar
• Application Number:
  US14/223,931
• Publication Number:
  US 20150271026A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0621 Item configuration or customization
• CPC Class Codes: G06Q 30/0629 for generating comparisons
• CPC Class Codes: G06Q 50/60 Business processes related to postal services shipping G06Q10/083; franking apparatus G07B17/00
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 41/5067 Customer-centric QoS measurements
• CPC Class Codes: H04L 43/0888 Throughput
• CPC Class Codes: H04L 67/1095 Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
• CPC Class Codes: H04L 67/303 Terminal profiles
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal

Abstract

A performance monitoring system collects profile data relative to an already-existing user, or a potential user. A predictive analysis is performed to predict whether the current performance, or predicted performance, meets an expected performance level. Key performance indicators are output and are indicative of the comparison.

Claims

1. A computer-implemented method, comprising:

obtaining profile information corresponding to a user system;

performing a prediction analysis to obtain a predicted performance of a the user system, when accessing a computer system, based on the profile information; and

displaying a predicted performance indicator indicative of the predicted performance.

2. The computer-implemented method of claim 1 wherein performing the prediction analysis comprises:

obtaining a set of key performance indicators indicative of the predicted performance.

3. The computer-implemented method of claim 2 wherein obtaining the set of key performance indicators comprises:

obtaining a page load time indicator indicative of a predicted page load time for the user system, when accessing the computer system.

4. The computer-implemented method of claim 2 and further comprising:

obtaining an actual performance indicator indicative of actual performance of the user system when assessing the computer system.

5. The computer-implemented method of claim 4 and further comprising:

comparing the predicted performance indicator to the actual performance indicator to obtain a comparison value.

6. The computer-implemented method of claim 5 wherein outputting the predicted performance indicator comprises:

outputting the comparison value.

7. The computer-implemented method of claim 6 wherein outputting the comparison value comprises:

outputting an indication of whether the actual performance indicator is within a threshold value of the predicted performance indicator.

8. The computer-implemented method of claim 7 and further comprising:

if the actual performance indicator is not within the threshold value of the predicted performance indicator, outputting a suggested action to bring the actual performance indicator within the threshold value of the predicted performance indicator.

9. The computer-implemented method of claim 1 wherein performing a prediction analysis comprises:

comparing the profile information to performance information for other user systems to identify similar user systems; and

obtaining actual performance data for the similar user systems.

10. The computer-implemented method of claim 9 wherein performing the prediction analysis comprises:

performing the prediction analysis to obtain the predicted performance indicator based on the actual performance data for the similar user systems.

11. The computer-implemented method of claim 1 and further comprising:

receiving scheduling inputs to schedule obtaining the profile information and performing the prediction analysis.

12. The computer-implemented method of claim 1 wherein obtaining profile information comprises:

obtaining geographic information indicative of a geographic location of the user system.

13. The computer-implemented method of claim 1 wherein obtaining profile information comprises:

obtaining service provider information indicative of service providers for the user system.

14. The computer-implemented method of claim 1 wherein obtaining profile information comprises:

obtaining page load times for the user system.

15. The computer-implemented method of claim 1 wherein obtaining profile information comprises:

obtaining network and hardware configuration information for the user system.

16. A computer system, comprising:

a user system profile collection component that collects user system profile information;

a network profile collection component that collects network profile information for the user system;

a user experience prediction component that predicts an expected user system performance in accessing a computer system user system profile information and the network profile information;

a user interface component that outputs a predicted performance indicator indicative of the expected user system performance; and

a computer processor that is a functional part of the system and activated by the user system profile collection component, the network profile collection component, and the user experience prediction component to facilitate collecting the user system profile information and the network profile information and prediction of the expected user system performance.

17. The computer system of claim 16 wherein the user system profile information includes actual performance data indicative of an actual performance of the user system in accessing the computer system and wherein the user experience prediction component determines whether the actual performance is within an threshold value of the expected user system performance, and further comprising:

a recommendation engine that generates recommendations for improving the user system performance if the actual performance is outside the threshold value of the expected user system performance.

18. The computer system of claim 16 wherein the user experience prediction component identifies similar user systems with similar user system profile information and network profile information, and predicts the expected user system performance based on actual performance information for the similar user systems.

19. A computer readable storage medium that stores computer readable instructions which, when executed by a computer, cause the computer to perform a method, comprising:

obtaining profile information corresponding to a user system;

performing a prediction analysis to obtain a predicted performance indicator indicative of a predicted performance of the user system, when a computer system, based on the profile information, the predicted performance indicator including a page load time indicator indicative of a predicted page load time for the user system, when accessing the computer system; and

displaying the predicted performance indicator.

20. The computer readable storage medium of claim 19 wherein performing the prediction analysis comprises:

obtaining a set of key performance indicators indicative of the predicted performance.