METHOD AND SYSTEM FOR SOCIAL MEDIA SALES

• US 20160055543A1
• Filed: 11/05/2015
• Published: 02/25/2016
• Est. Priority Date: 03/20/2013
• Status: Abandoned Application

• Current Assignee: Kaptivating Hospitality, LLC
• Original Assignee: Kaptivating Hospitality, LLC
• Inventors: Palmer, Michael C., Tulk, Steven A.
• Application Number:
  US14/933,574
• Publication Number:
  US 20160055543A1
• Time in Patent Office: Days
• US Class Current: 1/1
• 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) a database;

b) a social search module communicatively coupled to the database;

c) a lead analysis module communicatively coupled to the database;

d) a customer engagement module communicatively coupled to the database;

e) a transaction module communicatively coupled to the database;

f) a blog integration module communicatively coupled to the database; and

g) an inventory classification module communicatively coupled to the database.

2. The system of claim 1, where the modules are communicatively coupled to one another.

3. The system of claim 1, where each module is a discrete module remotely located from each other.

4. The system of claim 1, where the modules comprise non-transitory instructions executable on a processor for intent based marketing, transaction processing or both intent based marketing and transaction processing.

5. The system of claim 1, where the social search module can comprise non-transitory instructions selected from the group consisting of keyword analysis, natural language processing algorithms, statistical methods of classification and assignment of taxonomy categories.

6. The system of claim 5, where instructions for the keyword analysis is selected from the group consisting of Bayesian classifiers and Naive Bayesian classifiers to search various social media sites to identify customers seeking products, services or both product and services.

7. The system of claim 5, where instructions for the natural language processing algorithms are selected from the group consisting of Bayesian classifiers and Naive Bayesian classifiers to search various social media sites to identify and classify customers seeking products, services or both product and services according to a taxonomy.

8. The system of claim 5, where instructions for the statistical methods are selected from the group consisting of Bayesian classifiers and Naive Bayesian classifiers to search various social media sites to identify customers seeking products, services or both product and services.

9. The system of claim 1 further comprising instruction to dynamically generate a message in response to a social media post based on available information and attributes to engage a potential customer.

10. The system of claim 9, where the attributes can comprise a demographic attribute, a previous post analysis attribute, and a previous customer interaction attribute.

11. The system of claim 10, where the previous customer interaction is stored in the database.

12. The system of claim 10, where the previous customer interaction is determined and classified from a customer profile on one or more than one social media website.

13. The system of claim 9, where the dynamically generated message can comprise a unique URL that links the potential customer to the transaction module.

14. The system of claim 13, where the dynamically generated message can comprise an interface customized to a specific buying affinity, demographic and request.

15. The system of claim 1, where the modules comprise non-transitory instructions to define, store and retrieve attributes pertaining to potential customers in the database.

16. The system of claim 15, where the stored attributes can comprise demographics, product affinity, products, and customer interaction with the system over time.

17. The system of claim 1, where customer engagement module comprises instruction to analyze the attributes to match product supply with customer demand and dynamically generate a message, a proposition or both a message and a proposition to the customer based on the customer'"'"'s previous interactions.

18. The system of claim 1, where the transaction module can comprise additional interfaces to connect to proprietary third party product supply interfaces.

19. The system of claim 1, where the transaction module comprises instructions to support interfaces branded to a specific merchant.

20. The system of claim 1, where the transaction module comprises instructions to dynamically generate landing pages based on the stored customer attributes.

21. The system of claim 1, where the transaction module comprises instructions to generate analytics, display reports, display user created landing pages, integrate with additional social media platforms and integrate with third-party product platforms to extend the system'"'"'s capabilities.

22. The system of claim 1, where the social search module comprises non-transitory instructions executable on a processor to search various social media sites using keywords entered by the user.

23. The system of claim 1, where the lead analysis module comprises non-transitory instructions executable on a processor to analyze potential customer leads found by the search module.

24. The system of claim 1, where the lead analysis module comprises non-transitory instructions executable on a processor to rank the strength of the lead using an algorithm.

25. The system of claim 24, where the algorithm can be selected from the group consisting of Bayesian Classifiers, Semantic Classifiers, and natural language processing.

26. The system of claim 1, where the engagement module comprises non-transitory instructions executable on a processor to generate a manual response message, an automatic response message or both a manual and an automated response message to the customer leads returned by the search module.

27. The system of claim 1, where the engagement module further comprises instructions to communicate with customer leads and improve engagement by transmitting product related offers to the customer leads based on attributes identified by the engagement module.

28. The system of claim 1, where the transaction module comprises non-transitory instructions executable on a processor to generate buying affinity based landing pages and interfaces embedded within social media.

29. The system of claim 1, where the transaction module comprises a shopping cart module and a customizable user interface module.

30. The system of claim 29, where the customer interface comprises instruction to display various formats to the customer using customer buying affinity determined by the engagement module.

31. The system of claim 1, where the transaction module comprises non-transitory instructions operable on a computer to operate as a standalone website, a landing page, and within the social media site.

32. The system of claim 1, where the engagement module comprises instructions to analyze the stored data and further refine the likelihood of a customer'"'"'s intent to purchase the user'"'"'s products or services.

33. The system of claim 1, where the blog integration module comprises non-transitory instructions executable on a processor to insert system transaction modules into third party websites and blogs through keyword linking.

34. The system of claim 1, where the blog integration module further comprises instructions 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.

35. The system of claim 34, where the hover-overs and tool-tip type balloons can comprise customer incentives to purchase, where the incentives are a text, an image and a video.

36. The system of claim 1, where the inventory classification module can comprise non-transitory instructions selected from the group consisting of keyword analysis, natural language processing algorithms, statistical methods of classification and assignment of taxonomy categories.

37. The system of claim 36, where the instructions for the natural language processing algorithms comprise Bayesian classifiers and Naive Bayesian classifiers to search third party product supply interfaces to identify and classify products, services or both product and services according to a taxonomy.

38. A method to match product supply with demand using social media, the method comprising the steps of:

a) accessing the system of claim 1;

b) setting system preferences;

c) searching for keywords related to a product, a service or both a product and a service;

d) storing the search results in a database;

e) analyzing the search results;

f) relating search results to relevant inventory available; and

g) dynamically generating messages to select customers.

39. The method of claim 38, further comprising the step of displaying the stored search results in a quick list.

40. The method of claim 38, further comprising the step of filtering the search results.

41. The method of claim 38, further comprising the step of manually, automatically or both manually and automatically responding to posts displayed from the search results.

42. The method of claim 38, further comprising the step of displaying customer demographics for a selected filter and a date range.