Method and system for social media sales

• US 9,852,477 B2
• Filed: 02/27/2014
• Issued: 12/26/2017
• Est. Priority Date: 03/20/2013
• Status: Active Grant

• Current Assignee: Kaptivating Technology LLC
• Original Assignee: Kaptivating Technology LLC
• Inventors: Palmer, Michael C., Tulk, Steven A.
• Primary Examiner(s): Singh, Gurkanwaljit
• Application Number:
  US14/192,358
• Publication Number:
  US 20140289006A1
• Time in Patent Office: 1,398 Days
• Field of Search: None
• CPC Class Codes: G06F 16/243 Natural language query formulation
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0256 User search
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0633 Lists, e.g. purchase orders, compilation or processing
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A system and method to match product supply with demand by identifying potential customers on social media. The system comprising a database, a social search module, a lead analysis module, a customer engagement module, a transaction module, a blog integration module and an inventory classification module, where the database and the modules are all communicatively coupled to each other.

Claims

1. A system to match product supply with demand using social media, the system comprising:

a database; and

,

a plurality of processors each communicatively coupled to said database;

wherein said plurality of processors comprise a first processor, a second processor, a third processor, a fourth processor and a fifth processor;

wherein said first processor comprises a social search code segment that comprises non-transitory instructions, wherein the first processor comprising the social search code segment is configured to analyze keywords entered by users of social media, wherein the social search code segment is further configured to store the entered keywords in the database and generate customer leads of users seeking products, services or both products and services based on the analysis of keywords;

wherein the second processor comprises a lead analysis code segment that comprises non-transitory instructions, wherein the second processor comprising the lead analysis code segment is configured to rank customer leads generated by the social search code segment;

wherein the third processor comprises a customer engagement code segment that comprises non-transitory instructions, wherein the third processor comprising the customer engagement code segment is configured to generate a message associated with the customer leads, the generated message being based on user defined templates, customer demographics and user activity history of the corresponding users, the message being indicative of a demand for a product;

wherein the fourth processor comprises a transaction code segment that comprises non-transitory instructions, wherein the fourth processor comprising the transaction code segment is configured to generate buying affinity based landing pages and interfaces embedded within social media based on the message generated by the customer engagement code segment;

wherein the fifth processor comprises a blog integration code segment that comprises non-transitory instructions, wherein the fifth processor comprising the blog integration code segment is configured to link the transaction code segment with a third party vendor; and

,

wherein the sixth processor comprises an inventory classification code segment that comprises non-transitory instructions, wherein the sixth processor comprising the inventory classification code segment is configured to retrieve product inventory information from the third party vendor, wherein the product inventory information is indicative of a product supply, and wherein sixth processor comprising the inventory classification code segment is further configured to match the demand for product with the product supply;

wherein each of said plurality of processors are communicatively connected to one another via one or more of HTTPS, HTTP POST, AJAX, JSON, XML, REST, SQL queries and direct database access,

wherein each of said plurality of processors are coupled to one another by exchanging, storing and retrieving data between each of said plurality of processors and said database,

wherein said database stores information from each of said plurality of processors,

wherein the fourth processor further comprises a shopping cart code segment and a user interface, wherein the user interface displays various formats to a customer using customer affinity determined by the engagement code segment,

wherein the third processor analyzes the information stored in said database and further refines a likelihood of the customer'"'"'s intent to purchase the products, services or both products and services, and

wherein the plurality of processors

track how the customer visits and leaves a site before purchasing as additional information,

collect said additional information to determine when the customer is considering a purchase,

analyze said additional information to indicate the customer'"'"'s intent,

determine a trajectory of how the customer'"'"'s search is progressing from said additional information, and

dynamically generate further messages from said analysis of said additional information and said trajectory, wherein said further messages are specific to offers, availability or price of the products, services or both the products and services to convert the customer into a buyer.

2. The system of claim 1, wherein each processor of said plurality of processors is a discrete processor remotely located from each other.

3. The system of claim 1, wherein the first processor is further configured to analyze the keywords using the non-transitory instructions thereof, wherein said non-transitory instructions comprise one or more of natural language processing algorithms, statistical methods of classification and assignment of taxonomy categories.

4. The system of claim 1, wherein the second processor is further configured to rank the customer leads using the non-transitory instructions thereof, wherein said non-transitory instructions comprise one or more of Bayesian classifiers and Naive Bayesian classifiers.

5. The system of claim 1, wherein said plurality of processors dynamically generate said further messages in response to a social media post based on available information and attributes to engage said customer.

6. The system of claim 1, wherein the user activity history further includes a previous post analysis attribute and a previous customer interaction attribute.

7. The system of claim 6, wherein the previous customer interaction attribute is stored in the database.

8. The system of claim 6, wherein the previous customer interaction attribute is determined and classified from a customer profile on one or more than one social media website.

9. The system of claim 5, wherein the generated message comprises a unique Universal Resource Locator (URL) that links the customer to the transaction code segment.

10. The system of claim 9, wherein the generated message comprises an interface customized to a specific buying affinity, demographic and request.

11. The system of claim 1, wherein the non-transitory instructions of said plurality of processors define, store and retrieve attributes pertaining to customers in the database.

12. The system of claim 11, wherein the stored attributes comprises demographics, product affinity, products, and customer interaction with the system over time.

13. The system of claim 1, wherein the transaction code segment comprises additional interfaces to connect to proprietary third party product supply interfaces.

14. The system of claim 1, wherein the fourth processor comprising the transaction code segment further comprises instructions to support interfaces branded to a specific merchant.

15. The system of claim 1, wherein the fourth processor is further configured to generate analytics, display reports, display user created landing pages, integrate with additional social media platforms and integrate with third-party product platforms.

16. The system of claim 1, wherein the first processor is further configured to search various social media sites using keywords entered by the users.

17. The system of claim 1, wherein the second processor is further configured to rank the strength of the customer leads using an algorithm.

18. The system of claim 17, wherein the algorithm comprises one or more of of Bayesian Classifiers, Semantic Classifiers, and natural language processing.

19. The system of claim 1, wherein the third processor is further configured to communicate with the customer leads and transmit product related offers to the customer leads.

20. The system of claim 1, wherein the fourth processor is further configured to operate as a standalone website, a landing page, or within the social media.

21. The system of claim 1, wherein the fifth processor is further configured to insert the transaction code segment into third party web sites and blogs through keyword linking.

22. The system of claim 1, wherein the fifth processor is further configured to automatically convert keywords stored in the database to HTML anchors with hover-overs, tool-tip type balloons or both hover-overs and tool-tip type balloons in the third-party website.

23. The system of claim 22, wherein the hover-overs and tool-tip type balloons comprises customer incentives to purchase, where the incentives are a text, an image and a video.

24. The system of claim 1, wherein the fourth processor is further configured to accept input from the user to perform a search for keywords related to the products, services or both the products and services via the user interface, wherein results of the search are stored in the database and displayed in a quick list.

25. The system of claim 24, wherein the user interface comprises a filter button, wherein the fourth processor is further configured to

accept a second input from the user to click the filter button to filter the results,

accept a third input from the user to select specific customers to save or send said dynamically generated further messages.

26. The system of claim 1, wherein the user interface comprises a plurality of functional areas comprising a settings component, a search manager component, a filter box component, a page selector and a post listing component, wherein the search manager component comprises a search box and a list box, wherein the search box provides the user an area to enter keywords to search through social media posts that are relevant one or more of the products and services that the user has to offer for sale, and wherein the list box comprises previous searches that the user has conducted and saved in the database.

27. The system of claim 26, wherein the previous searches are used to automatically generate the dynamically generated further message on a daily basis to new potential customers that are not stored in the database.

28. The system of claim 1, wherein the sixth processor is further configured to evaluate one or more third party descriptions of inventory, process the inventory descriptions to classify the inventory descriptions into system defined terms to facilitate matching, transform the supply in terms common to the demand and normalize evaluations between a plurality of third party sources.

29. The system of claim 1, wherein the sixth processor is further configured to

retrieve data on one or more of the products and services available for matching using one or more of an application program interface (API), structured data feeds, data files, submission forms, and manual entry,

apply business logic to evaluate one or more third party descriptions and other stated attributes of one or more of the products and services compiling an inventory,

assign a standard system value for the attributes of one or more of the products and services based on proprietary taxonomy and other classification methods,

index normalized descriptions of the inventory, and

store the results in the database,

wherein the results stored in the database are used to match the demand for product with the product supply using one or more of an automated method and a manual method the first processor, the second processor, the third processor the fifth processor.