SOCIAL NETWORK MARKETING PLAN MONITORING METHOD AND SYSTEM

• US 20110173051A1
• Filed: 01/11/2010
• Published: 07/14/2011
• Est. Priority Date: 01/11/2010
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Modani, Natwar, Zhu, Zheng, Prasad, Subramanya Kabbinahithlu Narayana, Dey, Kuntal, Nanavati, Amit Anil
• Granted Patent: US 8,332,256 B2
• Time in Patent Office: Days
• US Class Current: 705/7.39
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A monitoring method and system. The method retrieving by a computer, first data associated with a marketing plan associated with social networks and second data associated with marketing plan objectives. The computer processor identifies social network effects associated with the marketing plan objectives, business key performance indicators (KPIs) associated with the marketing plan objectives, and social network KPIs associated with the associated social network effects. The computer processor represents a marketing plan measurement model comprising a mathematical relationship between the business KPIs and the social network KPIs. The computer processor monitors changes associated with the business KPIs and the social network KPIs and generates and stores a report indicating the changes.

Claims

1. A method comprising:

retrieving, by a computer processor of a computing system, first data associated with a marketing plan associated with social networks;

identifying, by said computer processor, second data associated with marketing plan objectives;

identifying, by said computer processor based on said first data and said second data, social network effects associated with said marketing plan objectives;

identifying, by said computer processor, business key performance indicators (KPIs) associated with said marketing plan objectives;

identifying, by said computer processor, social network KPIs associated with said social network effects;

representing, by said computer processor, a marketing plan measurement model comprising a mathematical relationship between said business KPIs and said social network KPIs;

monitoring, by said computer processor, changes associated with said business KPIs and said social network KPIs;

generating, by said computer processor, a report indicating said changes; and

storing, by said computer processor, said report.

2. The method of claim 1, wherein said identifying said second data associated with said marketing plan objectives comprises:

receiving, by said computer processor, budget data associated with said marketing plan;

receiving, by said computer processor, time duration data associated with implementing said marketing plan;

receiving, by said computer processor, stakeholders and roles data associated with said marketing plan;

receiving, by said computer processor, business success criteria data associated with said stakeholders and said marketing plan;

identifying, by said computer processor, components associated with first products associated with said marketing plan;

identifying, by said computer processor, characteristics associated with said components;

identifying, by said computer processor, a target marketing segment associated with said marketing plan; and

identifying, by said computer processor, second products comprising competing products associated with said first products.

3. The method of claim 2, wherein said identifying said business KPIs comprises:

generating, by said computer processor, a list comprising said business success criteria;

associating, by said computer processor, at least one business KPI of said business KPIs with a first business success criteria of said business success criteria; and

deriving, by said computer processor, mathematical formulas configured to express each business KPI of said business KPIs in terms of a lower level business KPI.

4. The method of claim 3, wherein said identifying said social network effects comprises:

receiving, by said computer processor, predicted social network effects;

receiving, by said computer processor, an expected duration for said social network effects; and

receiving, by said computer processor, expected risks associated with said social network effects.

5. The method of claim 4, wherein said identifying said social network KPIs comprises:

generating, by said computer processor, a list comprising said predicted social network effects;

identifying, by said computer processor, at least one social network KPI of said social network KPIs associated with measuring each predicted social network effect of said predicted social network effects; and

deriving, by said computer processor, mathematical formulas configured to express each social network KPI of said social network KPIs in terms of a lower level social network KPI.

6. The method of claim 1, wherein said representing said marketing plan measurement model comprises:

associating, by said computer processor, said business KPIs with said social network KPIs;

identifying, by said computer processor, relationships between said business KPIs and said social network KPIs; and

calculating, by said computer processor, variance thresholds associated with said business KPIs and said social network KPIs.

7. The method of claim 6, wherein said relationships are selected from the group consisting of fixed relationships, proportional relationships, variable relationships, and expressional relationships.

8. The method of claim 6, wherein said monitoring said changes comprises:

receiving, by said computer processor, monitored values associated with said business KPIs;

calculating, by said computer processor based on said monitored values, first possible values for said social network KPIs;

first comparing, by said computer processor, said first possible values to first associated variance thresholds of said variance thresholds; and

first determining, by said computer processor based on said first comparing, if any of said first possible values exceed any of said first associated variance thresholds.

9. The method of claim 8, wherein said first determining determines that at least one value of said first possible values exceeds an associated variance threshold of said first associated variance thresholds, and wherein said method further comprises:

generating, by said computer processor, an alert indicating that said at least one value exceeds said associated variance threshold; and

transmitting, by said computer processor to a user, said alert.

10. The method of claim 9, further comprising:

receiving, by said computer processor from said user in response to said alert, a command for modifying said variance thresholds, said social network KPIs, and/or said marketing plan.

11. The method of claim 6, wherein said monitoring said changes comprises:

receiving, by said computer processor, monitored values associated with said social network KPIs;

calculating, by said computer processor based on said monitored values, first possible values for said business KPIs;

first comparing, by said computer processor, said first possible values to first associated variance thresholds of said variance thresholds; and

first determining, by said computer processor based on said first comparing, if any of said first possible values exceed any of said first associated variance thresholds.

12. The method of claim 11, wherein said first determining determines that at least one value of said first possible values exceeds an associated variance threshold of said first associated variance thresholds, and wherein said method further comprises:

generating, by said computer processor, an alert indicating that said at least one value exceeds said associated variance threshold; and

transmitting, by said computer processor to a user, said alert.

13. The method of claim 12, further comprising:

receiving, by said computer processor from said user in response to said alert, a command for modifying said variance thresholds, said business KPIs, and/or said marketing plan.

14. A process for supporting computer infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in said computing system, wherein the code in combination with said computing system is capable of performing the method of claim 1.

15. A computer program product, comprising a computer storage medium comprising a computer readable program code embodied therein, said computer readable program code configured to perform the method of claim 1 upon being enabled by a processor of said computing system.

16. A computing system comprising a computer processor coupled to a computer-readable memory unit, said memory unit containing instructions that when enabled by the processor implement a monitoring method comprising;

retrieving, by said computer processor, first data associated with a marketing plan associated with social networks;

receiving, by said computer processor, second data associated with marketing plan objectives,

identifying, by said computer processor based on said first data and said second data, social network effects associated with said marketing plan objectives;

identifying, by said computer processor, business key performance indicators (KPIs) associated with said marketing plan objectives;

identifying, by said computer processor, social network KPIs associated with said associated social network effects;

representing, by said computer processor, a marketing plan measurement model comprising a mathematical relationship between said business KPIs and said social network KPIs;

monitoring, by said computer processor, changes associated with said business KPIs and said social network KPIs;

generating, by said computer processor, a report indicating said changes; and

storing, by said computer processor, said report.

17. The computing system of claim 16, wherein said identifying said marketing plan objectives comprises:

receiving, by said computer processor, budget data associated with said marketing plan;

receiving, by said computer processor, time duration data for implementing said marketing plan;

receiving, by said computer processor, stakeholders and roles data associated with said marketing plan;

receiving, by said computer processor, business success criteria data associated with said stakeholders and said marketing plan;

identifying, by said computer processor, components associated with first products associated with said marketing plan;

identifying, by said computer processor, characteristics associated with said components;

identifying, by said computer processor, a target marketing segment associated with said marketing plan; and

identifying, by said computer processor, second products comprising competing products associated with said first products.

18. The computing system of claim 17, wherein said identifying said business KPIs comprises:

generating, by said computer processor, a list comprising said business success criteria;

associating, by said computer processor, at least one business KPI of said business KPIs with a first business success criteria of said business success criteria; and

deriving, by said computer processor, mathematical formulas configured to express each business KPI of said business KPIs in terms of a lower level business KPI.

19. The computing system of claim 17, wherein said identifying said associated social network effects comprises:

receiving, by said computer processor, predicted social network effects;

receiving, by said computer processor, an expected duration for said social network effects; and

receiving, by said computer processor, expected risks associated with said social network effects.

20. The computing system of claim 19, wherein said identifying said social network KPIs comprises:

generating, by said computer processor, a list comprising said predicted social network effects;

identifying, by said computer processor, at least one social network KPI of said social network KPIs associated with measuring each predicted social network effect of said predicted social network effects; and

deriving, by said computer processor, mathematical formulas configured to express each social network KPI of said social network KPIs in terms of a lower level social network KPI.