Social network marketing plan monitoring method and system

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.

This application is related to application Ser. No. 12/685,206 filed on Jan.11, 2010.

FIELD OF THE INVENTION

The present invention relates to a method and associated system for measuring and monitoring a social network marketing plan.

BACKGROUND OF THE INVENTION

Monitoring various processes typically comprises an inefficient process with little flexibility. Accordingly, there exists a need in the art to overcome at least some of the deficiencies and limitations described herein above.

SUMMARY OF THE INVENTION

The present invention provides a method comprising: retrieving, by a computer processor of a computing system, first data associated with a marketing plan associated with social networks; receiving, by the computer processor, second data associated with marketing plan objectives; identifying, by the computer processor based on the first data and the second data, social network effects associated with the marketing plan objectives; identifying, by the computer processor, business key performance indicators (KPIs) associated with the marketing plan objectives; identifying, by the computer processor, social network KPIs associated with the associated social network effects; representing, by the computer processor, a marketing plan measurement model comprising a mathematical relationship between the business KPIs and the social network KPIs; monitoring, by the computer processor, changes associated with the business KPIs and the social network KPIs; generating, by the computer processor, a report indicating the changes; and storing, by the computer processor, the report.

The present invention provides a computing system comprising a computer processor coupled to a computer-readable memory unit, the memory unit containing instructions that when enabled by the processor implement a monitoring method comprising; retrieving, by the computer processor, first data associated with a marketing plan associated with social networks; receiving, by the computer processor, second data associated with marketing plan objectives; identifying, by the computer processor based on the first data and the second data, social network effects associated with the marketing plan objectives; identifying, by the computer processor, business key performance indicators (KPIs) associated with the marketing plan objectives; identifying, by the computer processor, social network KPIs associated with the associated social network effects; representing, by the computer processor, a marketing plan measurement model comprising a mathematical relationship between the business KPIs and the social network KPIs; monitoring, by the computer processor, changes associated with the business KPIs and the social network KPIs; generating, by the computer processor, a report indicating the changes; and storing, by the computer processor, the report.

The present invention advantageously provides a simple method and associated system capable of monitoring various processes.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1illustrates a system5for measuring and monitoring a social network marketing plan, in accordance with embodiments of the present invention. System2enables a method for identifying social network key performance indicators (KPI) and business KPIs that are associated with a social network marketing plan. Additionally, system2generates a model representing a relationship between the social network KPIs and the business KPIs. A social network is defined herein as a social structure comprising individuals (or organizations) that may be referred to as nodes. The nodes are connected to each other by one or more specific types of interdependency such as, inter alia, friendship, family, interests, beliefs, knowledge, etc. A social network may comprise any type of devices linked together including, inter alia, a telephone network, a computer network, etc. A KPI is defined herein as a tool allowing an organization to define and measure progress towards organizational goals. A KPI comprises a number used to measure and express business impacts in terms of financial and social network parameters.

System5ofFIG. 1comprises devices8a. . .8nconnected through a network7to a computing system10. Network7may comprise any type of network including, inter alia, a telephone network, a cellular telephone network, a local area network, (LAN), a wide area network (WAN), the Internet, etc. Devices8a. . .8nmay comprise any type of devices capable of implementing a social network including, inter alia, a telephone, a cellular telephone, a digital assistant (PDA), a video game system, an audio/video player, a personal computer, a laptop computer, a computer terminal, etc. Each of devices8a. . .8nmay comprise a single device or a plurality of devices. Devices8a. . .8nare used by end users for communicating with each other and computing system10. Computing system10may comprise any type of computing system(s) including, inter alia, a personal computer (PC), a server computer, a database computer, etc. Computing system10is used to measure and monitor a social network marketing plan implemented using devices8a. . .8n. Computing system10comprises a memory system14. Memory system14may comprise a single memory system. Alternatively, memory system14may comprise a plurality of memory systems. Memory system14comprises a software application18and a database12. Database12comprises all retrieved and calculated associated with measuring and monitoring a social network marketing plan. Software application18enables a method to measure and monitor a social network marketing plan. Software application18enables a four phase process for aligning a social network effect based marketing plan with business goals as follows:1. An identification phase that identifies a social network marketing plan objectives, intended social network effects (i.e., associated with marketing plan objectives), etc. A social network effect is defined herein effects observed in social networks of people as direct and indirect effects of announcing and implementing marketing plans. The objectives are well-defined on behalf of the marketing plan owner company and their stakeholders and may be optionally announced to the people.2. A formulation phase that identifies appropriate business KPIs for each marketing plan objective and network KPIs for each intended social network effect.3. An association phase that organizes business and network KPIs and specifies their relationship in a marketing plan measurement model.4. A monitor phase that gathers data for each previously identified network KPI, calculates business KPIs, and highlights any KPI that violates tolerance thresholds (i.e., changes associated with business KPIs and social network KPIs effected by a marketing plan). Additionally, the monitor phase specifies formal notations for the marketing plan measurement model in order to: represent KPI entities, represent relationships, and represent different relationship types.

Software application18additionally formal notations for a marketing plan measurement model in order to represent: KPI entities, relationships, different relationship types, etc. The marketing plan measurement model may be used monitor:1. Emergence (or vanishing) of intended/predicted social network effects (i.e., predicted elemental, structural, and behavioral changes in a social network with respect to a given marketing plan or a given set of marketing plans).2. Emergence (or vanishing) of unintended/unpredicted social network effects.3. A top-down analysis comprising changes in financial metrics root-caused to network effects.4. A bottom-up analysis comprising estimated implications of network effects on financial metrics.

Each of the four stages (i.e., identification phase, formulation phase, association phase, and monitor phase) enabled by software application18are described in detail as follows:

Identification Phase

During the identification phase, software application18identifies data associated with a business, marketing plan components (i.e., social network structures, behavior KPIs, and financial KPIs associated with a given marketing plan), and a social network associated with the business.1. Business dataa. Identify marketing plan objectives.b. List a marketing plan budget.c. List a marketing plan duration.d. List stakeholders and roles.e. Identify stakeholder's success criteria for the marketing plan.2. Marketing plan components dataa. List marketing plan's components (product/service/bundle).b. Identify component characteristics.c. Identify target market segment.d. Identify similar products (from same/different) merchant for same segment.3. Social network dataa. List predicted social network effects.b. List an expected time for the social network effects to emerge.c. List an expected time period duration associated with the social network effects.d. List expected risks for the social network.

The following implementation example describes implementation of the identification phase. In this example, a marketing plan objective comprises increasing a number of subscribers (i.e., for a telecom network A) retrieved from a second telecom network B by offering an incentive to existing subscribers (i.e., of the telecom network A) to enroll subscribers of the telecom network B in the telecom network A. Marketing plan component features (i.e., the incentive) comprise offering an existing member M (i.e., for each new subscriber N that existing member M brings in to telecom network A from telecom network B):A. A 50% discount on all calls that existing member M makes to new subscriber N.B. A 10% discount on all calls that existing member M makes to people associated with new subscriber N.C. A 2% discount on all other calls.
Formulation Phase

During the formulation phase, software application18identifies business KPIs and social network KPIs.1. Business KPIsa. List business success criteria (i.e., from the identification phase).b. Identify one or more KPI for each criteria.c. Decompose each high level KPI to other business KPIs/metrics.d. Derive formulas to express each KPI in terms of lower level KPIs.2. Social network KPIsa. List predicted social network effects (i.e., from the identification phase).b. Identify one or more KPI to measure each social network effect.c. Identify a data source to measure each KPI.d. Define an algorithm to calculate each KPI.e. Combine multiple network KPIs to form higher level KPIs.f. Derive formulas to express each higher level network KPI in terms of lower level KPIs.

The following implementation example describes implementation of the formulation. In this example, identifies appropriate business KPIs (and expectations) and social network KPIs (and expectations) associated with increasing a number of subscribers (i.e., for a telecom network A) retrieved from a second telecom network B by offering an incentive to existing subscribers (i.e., of the telecom network A) to enroll subscribers of the telecom network B in the telecom network A.

Business KPIs and Expectations

A. Increased call minutes.B. Increase in total revenue.C. Increased ARPU.D. Reduced interconnection charges.
Network KPIs and ExpectationsA. Social Networks evolving to denser patterns.B. Number of nodes must remain the same (Foreign subscribers in the social network switch from telecom network B to telecom network A) or must see an increase (new subscribers take up connection to social network A).C. Increased weight of edges between nodes (i.e., increased number of calls)D. Reduced participation of foreign subscribers in subscriber M's social network.
Association Phase

During the association phase, software application18: associates business KPIs with social network KPIs, Identifies types of relationships between KPIs, and calculate variance thresholds for KPIs.1. Associate business and social network KPIsa. Represent each social network and business KPI in a marketing plan measurement model.b. Derive formulas to express each lowest business KPIs with a highest network KPI2. Identify types of relationships between KPIsa. Fixed relationships comprising a pair of KPIs equivalent to each other.b. Proportional relationships comprising a pair of KPIs that change linearly with each other.c. Variable relationships comprising a KPI that changes with a change in another KPI.d. Expression relationships comprising a KPI that may be expressed in terms of a mathematical formula that comprises other KPIs.3. Calculate variance thresholdsa. Starting from a top-most business criteria, calculate each business and social network KPI.b. Starting from top-most business criteria, define a variance threshold for each business and social network KPI.
Monitor Phase

During the monitor phase, software application18: calculates business KPI values (a bottom-up analysis comprising estimating implications of network effects on financial metrics) and compares variance thresholds or calculates social network KPI values (a top-down analysis comprising changes in financial metrics root-caused to social network effects) and compares variance thresholds.1. Calculate Business KPI Valuesa. Using a network monitor tool (e.g., software application18) to measure values of each social network KPI.b. Enter measured values (for each social network KPI) in a marketing plan measurement model.c. Using relationships identified in the association phase, derive all remaining social network and Business KPIs in the marketing plan measurement model.2. Calculate social network KPI Values.a. Measure values of each business KPI (i.e., using financial reporting tools).b. Enter measured values (for each business KPI) in a marketing plan measurement model.c. Using relationships identified in the association phase, derive all remaining business and social network KPIs. The aforementioned method for calculating social network KPI Values may result in multiple combinations of values for all derived KPIs. In these cases, additional KPI measurements are taken to reduce a number of combinations to a minimum.3. Compare variance thresholds and generate alertsa. In a completed marketing plan measurement model, compare measured value of each KPI against a respective variance threshold. If a measured value is greater than or less than a min/max threshold, then a user is alerted. Additionally, corrective actions associated with results of the comparison process may be enabled. The following corrective actions may be enabled: modify variance thresholds, modify business/social network KPIs (e.g., define new KPIs, update/delete KPIs, etc), modify marketing plan or marketing plan goals, suspend/terminate marketing plan, etc.

FIG. 2illustrates a flowchart describing an algorithm used by system5ofFIG. 1for measuring and monitoring a social network marketing plan, in accordance with embodiments of the present invention. In step202, a computing system (e.g., computing system10ofFIG. 1), retrieves marketing plan data associated with social networks. In step204, the computing system identifies marketing plan objectives data. In step208, the computing system identifies (i.e., based on the marketing plan data and the marketing plan objectives data) social network effects associated with marketing plan objective (i.e., of the marketing plan objectives data). In step210, the computing system identifies business key performance indicators (KPIs) associated with the marketing plan objectives. In step218, the computing system identifies social network KPIs associated with the social network effects. In step220, the computing system represents a marketing plan measurement model comprising a mathematical relationship between the business KPIs and the social network KPIs. In step224, the computing system monitors changes associated with the business KPIs and the social network KPIs. In step228, the computing system generates and stores a report indicating the changes associated with the business KPIs and the social network KPIs.

FIG. 3illustrates a flowchart detailing step204of the algorithm ofFIG. 2, in accordance with embodiments of the present invention. In step302, the computing system receives budget data associated with the marketing plan. In step304, the computing system receives time duration data associated with implementing the marketing plan. In step308, the computing system receives stakeholders and roles data associated with the marketing plan. In step310, the computing system receives business success criteria data associated with the stakeholders and the marketing plan. In step318, the computing system identifies components associated with first products associated with the marketing plan. In step320, the computing system identifies characteristics associated with the components. In step324, the computing system identifies a target marketing segment associated with the marketing plan. In step328, the computing system identifies second products comprising competing products associated (i.e., competing with) with the first products.

FIG. 4illustrates a flowchart detailing step210of the algorithm ofFIG. 2, in accordance with embodiments of the present invention. In step402, the computing system generates a list comprising the business success criteria. In step404, the computing system associates at least one business KPI of the business KPIs with a first business success criteria of the business success criteria. In step408, the computing system derives mathematical formulas configured to express each business KPI in terms of a lower level business KPI.

FIG. 5illustrates a flowchart detailing step208of the algorithm ofFIG. 2, in accordance with embodiments of the present invention. In step502, the computing system receives predicted social network effects. In step504, the computing system receives an expected duration for the social network effects. In step508, the computing system receives expected risks associated with the social network effects.

FIG. 6illustrates a flowchart detailing step218of the algorithm ofFIG. 2, in accordance with embodiments of the present invention. In step602, the computing system generates a list comprising the predicted social network effects. In step604, the computing system identifies at least one social network KPI associated with measuring each predicted social network effect of the predicted social network effects. In step608, the computing system derives mathematical formulas configured to express each social network KPI in terms of a lower level social network KPI.

FIG. 7illustrates a flowchart detailing step220of the algorithm ofFIG. 2, in accordance with embodiments of the present invention. In step702, the computing system associates the business KPIs with the social network KPIs. In step704, the computing system identifies relationships between the business KPIs and the social network KPIs. In step708, the computing system calculates variance thresholds associated with the business KPIs and the social network KPIs.

FIG. 8illustrates a flowchart detailing a first embodiment associated with step224of the algorithm ofFIG. 2, in accordance with embodiments of the present invention. In step802, the computing system receives monitored values associated with the business KPIs. In step804, the computing system calculates (i.e., based on the monitored values) first possible values for the social network KPIs. In step808, the computing system compares the first possible values to first associated variance thresholds of the variance thresholds. In step810, the computing system determines (i.e., based on results of step808) that at least one value of the first possible values exceeds an associated variance threshold. In step820, the computing system generates and transmits (i.e., to a user) an alert indicating the least one value exceeds the associated variance threshold. In step828, the computing system receives (i.e., from the user in response to the alert) a command for modifying the variance thresholds, the social network KPIs, and/or the marketing plan.

FIG. 9illustrates a flowchart detailing a second embodiment associated with step224of the algorithm ofFIG. 2, in accordance with embodiments of the present invention. In step902, the computing system receives monitored values associated with the social network KPIs. In step904, the computing system calculates (i.e., based on the monitored values) first possible values for the business KPIs. In step908, the computing system compares the first possible values to first associated variance thresholds of the variance thresholds. In step910, the computing system determines (i.e., based on results of step908) that at least one value of the first possible values exceeds an associated variance threshold. In step920, the computing system generates and transmits (i.e., to a user) an alert indicating the least one value exceeds the associated variance threshold. In step928, the computing system receives (i.e., from the user in response to the alert) a command for modifying the variance thresholds, the business KPIs, and/or the marketing plan.

FIG. 10illustrates a computer apparatus90(e.g., computing system10ofFIG. 1) used for measuring and monitoring a social network marketing plan, in accordance with embodiments of the present invention. The computer system90comprises a processor91, an input device92coupled to the processor91, an output device93coupled to the processor91, and memory devices94and95each coupled to the processor91. The input device92may be, inter alia, a keyboard, a software application, a mouse, etc. The output device93may be, inter alia, a printer, a plotter, a computer screen, a magnetic tape, a removable hard disk, a floppy disk, a software application, etc. The memory devices94and95may be, inter alia, a hard disk, a floppy disk, a magnetic tape, an optical storage such as a compact disc (CD) or a digital video disc (DVD), a dynamic random access memory (DRAM), a read-only memory (ROM), etc. The memory device95includes a computer code97. The computer code97includes algorithms (e.g., the algorithms ofFIGS. 2-9) for measuring and monitoring a social network marketing plan. The processor91executes the computer code97. The memory device94includes input data96. The input data96includes input required by the computer code97. The output device93displays output from the computer code97. Either or both memory devices94and95(or one or more additional memory devices not shown inFIG. 10) may comprise the algorithms ofFIGS. 2-9and may be used as a computer usable medium (or a computer readable medium or a program storage device) having a computer readable program code embodied therein and/or having other data stored therein, wherein the computer readable program code comprises the computer code97. Generally, a computer program product (or, alternatively, an article of manufacture) of the computer system90may comprise the computer usable medium (or said program storage device).

Still yet, any of the components of the present invention could be created, integrated, hosted, maintained, deployed, managed, serviced, etc. by a service provider who offers to measure and monitor a social network marketing plan. Thus the present invention discloses a process for deploying, creating, integrating, hosting, maintaining, and/or integrating computing infrastructure, comprising integrating computer-readable code into the computer system90, wherein the code in combination with the computer system90is capable of perform ring a method for measuring and monitoring a social network marketing plan. In another embodiment, the invention provides a method that performs the process steps of the invention on a subscription, advertising, and/or fee basis. That is, a service provider, such as a Solution Integrator, could offer to measure and monitor a social network marketing plan. In this case, the service provider can create, maintain, support, etc. a computer infrastructure that performs the process steps of the invention for one or more customers. In return, the service provider can receive payment from the customer(s) under a subscription and/or fee agreement and/or the service provider can receive payment from the sale of advertising content to one or more third parties.