# US 2014/0195333 A1 · Social Commerce Return on Investment

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- Number: US 2014/0195333 A1
- Document ID: US20140195333A1
- Status: Published application
- Kind: A1
- Application number: 13/737,492
- Filed: 2013-01-09
- Published: 2014-07-10
- Earliest claimed: 2013-01-09
- Assignees: Dell Products L.P.
- Applicants: Dell Products L.P.
- Inventors: Munish Gupta; Rajiv Narang; Akintunde A. Ehindero; Jennifer W. Bruce; Ahmed Tariq
- Web page: https://patentgrep.com/patent/US20140195333A1

## CPC

- G06Q 30/0244: {Optimization}
- G06Q 10/40: Business processes related to social networking or social networking services
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

A system and method are disclosed for analyzing return on investment (ROI) for social commerce interactions. User data associated with a target group of social media users is collected and processed to generate a first set of social commerce metrics. The user data comprises a first set of social media interaction data corresponding to a first set of social commerce interactions with the target group of social media users. The user data is further processed to generate a second set of social commerce interactions, which are then performed. The performance of the second set of social commerce interactions generates a second set of social commerce interaction data, which in turn is processed to generate a second set of social commerce metrics. The first and second sets of social commerce metrics are then processed to generate social commerce ROI metrics.

## Claims

### Claim 1

A computer-implemented method for analyzing return on investment for social commerce interactions, comprising:
processing a set of user data associated with a set of social media users to generate a first set of social commerce metrics, the set of user data comprising a first set of social media interaction data corresponding to a first set of social commerce interactions with the set of social media users;
processing the set of user data and the first set of social media interaction data to generate a second set of social commerce interactions;
performing the second set of social commerce interactions with the set of social media users to generate a second set of social commerce interaction data;
processing the second set of social commerce interaction data to generate a second set of social commerce metrics; and
processing the first and second sets of social commerce metrics to generate a set of return on investment metrics corresponding to the second set of social commerce interactions.

### Claim 2 (depends on 1)

The method of claim 1, wherein the second set of social media interactions comprises at least one member of a group consisting of:
automated marketing operations;
sales lead nurturing operations; and
sales execution processes.

### Claim 3 (depends on 2)

The method of claim 2, wherein:
the set of user data is processed to generate a social presence map;
the first set of social media interaction data is processed to generate a predictive model; and
the social presence map and the predictive model are processed to generate the first set of social commerce metrics.

### Claim 4 (depends on 3)

The method of claim 3, wherein the social presence map and the predictive model are further processed to identify triggers to initiate the second set of social commerce interactions.

### Claim 5 (depends on 3)

The method of claim 3, wherein the predictive model is used to generate the sales leads.

### Claim 6 (depends on 1)

The method of claim 1, wherein the set of user data comprises at least one member of a group consisting of:
a set of active listening data;
a set of received media data;
a set of marketing and sales history data;
a set of social network behavior data;
a set of firmographic data;
a set of purchase history data; and
a set of vendor site visit footprint data.

### Claim 7

A system comprising:
a processor;
a data bus coupled to the processor; and
a computer-usable medium embodying computer program code, the computer-usable medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for:
processing a set of user data associated with a set of social media users to generate a first set of social commerce metrics, the set of user data comprising a first set of social media interaction data corresponding to a first set of social commerce interactions with the set of social media users;
processing the set of user data and the first set of social media interaction data to generate a second set of social commerce interactions;
performing the second set of social commerce interactions with the set of social media users to generate a second set of social commerce interaction data;
processing the second set of social commerce interaction data to generate a second set of social commerce metrics; and
processing the first and second sets of social commerce metrics to generate a set of return on investment metrics corresponding to the second set of social commerce interactions.

### Claim 8 (depends on 7)

The system of claim 7, wherein the second set of social media interactions comprises at least one member of a group consisting of:
automated marketing operations;
sales lead nurturing operations; and
sales execution processes.

### Claim 9 (depends on 8)

The system of claim 8, wherein:
the set of user data is processed to generate a social presence map;
the first set of social media interaction data is processed to generate a predictive model; and
the social presence map and the predictive model are processed to generate the first set of social commerce metrics.

### Claim 10 (depends on 9)

The system of claim 9, wherein the social presence map and the predictive model are further processed to identify triggers to initiate the second set of social commerce interactions.

### Claim 11 (depends on 9)

The system of claim 9, wherein the predictive model is used to generate the sales leads.

### Claim 12 (depends on 7)

The system of claim 7, wherein the set of user data comprises at least one member of a group consisting of:
a set of active listening data;
a set of received media data;
a set of marketing and sales history data;
a set of social network behavior data;
a set of firmographic data;
a set of purchase history data; and
a set of vendor site visit footprint data.

### Claim 13

A computer-usable medium embodying computer program code, the computer program code comprising computer executable instructions configured for:
processing a set of user data associated with a set of social media users to generate a first set of social commerce metrics, the set of user data comprising a first set of social media interaction data corresponding to a first set of social commerce interactions with the set of social media users;
processing the set of user data and the first set of social media interaction data to generate a second set of social commerce interactions;
performing the second set of social commerce interactions with the set of social media users to generate a second set of social commerce interaction data;
processing the second set of social commerce interaction data to generate a second set of social commerce metrics; and
processing the first and second sets of social commerce metrics to generate a set of return on investment metrics corresponding to the second set of social commerce interactions.

### Claim 14 (depends on 13)

The computer usable medium of claim 13, wherein the second set of social media interactions comprises at least one member of a group consisting of:
automated marketing operations;
sales lead nurturing operations; and
sales execution processes.

### Claim 15 (depends on 14)

The computer usable medium of claim 14, wherein:
the set of user data is processed to generate a social presence map;
the first set of social media interaction data is processed to generate a predictive model; and
the social presence map and the predictive model are processed to generate the first set of social commerce metrics.

### Claim 16 (depends on 15)

The computer usable medium of claim 15, wherein the social presence map and the predictive model are further processed to identify triggers to initiate the second set of social commerce interactions.

### Claim 17 (depends on 15)

The computer usable medium of claim 15, wherein the predictive model is used to generate the sales leads.

### Claim 18 (depends on 13)

The computer usable medium of claim 13, wherein the set of user data comprises at least one member of a group consisting of:
a set of active listening data;
a set of received media data;
a set of marketing and sales history data;
a set of social network behavior data;
a set of firmographic data;
a set of purchase history data; and