Method and system for determining levels of search sophistication for users of a customer self-help system to personalize a content search user experience provided to the users and to increase a likelihood of user satisfaction with the search experience

1. A method performed by one or more processors of a system, the method comprising:

providing a system user with access to customer support content;

receiving a request from the system user to display a particular portion of the customer support content;

generating a search sophistication value for the system user based on an analysis of the system user's request;

selecting one of a plurality of search experience options for the system user based on the system user's search sophistication value; and

presenting the system user with the particular portion of the customer support content via the selected search experience option.

2. The method of claim 1 , further comprising:

generating a set of user data for the system user based at least in part on the system user's request; and

personalizing the selected search experience option for the system user based on the generated set of user data.

3. The method of claim 1 , wherein the system is for financial management.

4. The method of claim 1 , wherein the system is at least one of a tax return preparation system, a business financial management system, or a personal financial management system.

5. The method of claim 1 , wherein the system user's request is received from a third-party search engine.

6. The method of claim 5 , wherein the system user's request is embedded in a Uniform Resource Locator (“URL”) associated with the third-party search engine.

7. The method of claim 1 , wherein the analysis of the system user's request includes analyzing at least one of a set of pronouns within the system user's request, punctuation within the system user's request, a character count of the system user's request, a number of search terms within the system user's request, or one or more misspellings within the system user's request.

8. The method of claim 1 , wherein the analysis of the system user's request includes analyzing at least one of adjacent key misspellings within the system user's request, incorrect letter ordering within the system user's request, phonetical misspelling within the system user's request, or one or more mobile device autocorrections within the system user's request.

9. The method of claim 1 ,

wherein the selected search experience option is an advanced search experience option if the system user's search sophistication value exceeds a first value.

10. The method of claim 1 , wherein the selected search experience option is a simple search experience option if the system user's search sophistication value is below a first value.

11. The method of claim 1 , wherein the selecting is further based on a set of

clickstream data associated with the system user.

12. The method of claim 1 , wherein the analysis of the system user's request includes a consideration of at least one of a probabilistic topic model, a spell-checking engine, or a character search algorithm.

13. The method of claim 12 , wherein the probabilistic topic model includes at least one of a Latent Dirichlet Allocation algorithm, a Latent Semantic Indexing (“LSI”) algorithm, a query clustering algorithm, or a query de-duplication algorithm.

14. The method of claim 1 , wherein the customer support content includes at least one of crowd-sourced content, service provider content, one or more acronyms, or one or more definitions.

15. The method of claim 1 , wherein the analysis of the system user's request includes using a predictive model and at least one of a regression, a decision tree, an artificial neural network, a support vector machine, a nearest neighbor method, a distance-based method, naive Bayes, a linear discriminant analysis, or a k-nearest neighbor algorithm.

16. A system comprising:

one or more processors; and

at least one memory coupled to the one or more processors and storing instructions that, when executed by one or more processors, cause the system to perform operations comprising:

providing a system user with access to customer support content;

receiving a request from the system user to display a particular portion of the customer support content;

generating a search sophistication value for the system user based on an analysis of the system user's request;

selecting one of a plurality of search experience options for the system user based on the system user's search sophistication value;

and

presenting the system user with the particular portion of the customer support content via the selected search experience option.

17. The system of claim 16 , wherein the analysis of the system user's request includes analyzing at least one of a set of pronouns within the system user's request, punctuation within the system user's request, a character count of the system user's request, a number of search terms within the system user's request, or one or more misspellings within the system user's request.

18. The system of claim 16 , wherein the analysis of the system user's request includes analyzing at least one of adjacent key misspellings within the system user's request, incorrect letter ordering within the system user's request, phonetical misspelling within the system user's request, or one or more mobile device autocorrections within the system user's request.

19. The system of claim 16 , wherein the selected search experience option is an advanced search experience option if the system user's search sophistication value exceeds a first value.

20. The system of claim 16 , wherein the selected search experience option is a simple search experience option if the system user's search sophistication value is below a first value.

21. The system of claim 16 , wherein the selecting is further based on a set of clickstream data associated with the system user.

22. The system of claim 16 , wherein the analysis of the system user's request includes a consideration of at least one of a probabilistic topic model, a spell-checking engine, or a character search algorithm.

23. The system of claim 16 , wherein the analysis of the system user's request includes using a predictive model and at least one of a regression, a decision tree, an artificial neural network, a support vector machine, a nearest neighbor method, a distance-based method, naive Bayes, a linear discriminant analysis, or a k-nearest neighbor algorithm.

24. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a system, causes the system to perform operations, comprising:

providing a system user with access to customer support content;

receiving a request from the system user to display a particular portion of the customer support content;

generating a search sophistication value for the system user based on an analysis of the system user's request;

selecting one of a plurality of search experience options for the system user based on the system user's search sophistication value; and

presenting the system user with the particular portion of the customer support content via the selected search experience option.

25. The computer-readable medium of claim 24 , wherein the system user's request is received from a third-party search engine.

26. The computer-readable medium of claim 25 , wherein the system user's request is embedded in a Uniform Resource Locator (“URL”) associated with the third-party search engine.

27. The computer-readable medium of claim 24 , wherein the analysis of the system user's request includes a consideration of at least one of a probabilistic topic model, a spell-checking engine, or a character search algorithm.

28. The computer-readable medium of claim 24 , wherein execution of the instructions causes the system to perform operations further comprising:

generating a set of user data for the system user based at least in part on the system user's request; and

personalizing the selected search experience option for the system user based on the generated set of user data.

29. The computer-readable medium of claim 28 , wherein the selected search experience option is an advanced search experience option if the system user's search sophistication value exceeds a first value.

30. The computer-readable medium of claim 29 , wherein the selected search experience option is a simple search experience option if the system user's search sophistication value is below a first value.