IP Library Granted Patent US 50,696
Granted Patent E1
US 50,696 · App. 18/107,682 · Granted Dec 9, 2025

System and method for tracking web interactions with real time analytics

Inventors: Hadas Liberman Ben-Ami (Kadima, IL); Leon Portman (Rishon Lezion, IL); Yuval Marco (Kadima, IL); Yosef Golan (Askhelon, IL); Shlomi Haba (Petah Tiqva, IL); Iftach Smith (Hod Hasharon, IL); Yizhar Ronen (Hod HaSharon, IL); Yohay Etsion (Tel Aviv, IL); Igor Cher (Rehovot, IL); Naama Damti (Zichron-Yackov, IL); Assaf Frenkel (Ramat HaSharon, IL); Uzi Baruch (Maale Adumim, IL)
Assignee: Nice Ltd.
H04M3/5191
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 50,696
App. No.
18/107,682
Granted
Dec 9, 2025
Kind
E1
Abstract

A device, system and method is provided for monitoring a user's interactions with Internet-based programs or documents. Content may be extracted from Internet server traffic according to predefined rules. Extracted content may be associated with a user's Internet interaction. The user's Internet interaction may be stored and indexed. The user's Internet interaction may be analyzed to generate a recommendation provided to a contact center agent while the contact center agent is communicating with said user for guiding the user's interaction, for example, in real-time. Traffic other than Internet server traffic may also be used.

Claims (88)

1 . A method for monitoring a user's interactions with Internet-based programs or documents, the method comprising:

extracting content from Internet server traffic according to predefined rules;

associating the extracted content with one or more of a user's Internet interaction sessions;

storing and indexing the user's Internet interaction sessions;

automatically comparing, by a web analyzer using a processor, one or more of the user's Internet interaction sessions to one or more modeled sessions to generate a recommendation of one or more future session paths from the modeled sessions for guiding the user's Internet interactions; and

providing the recommendation of the future session paths from the modeled sessions on screen to a contact center agent while the contact center agent is communicating with said user during a telephone call initiated by the user between the agent and the user.

2 . The method of claim 1 comprising identifying the user by text captured on a screen element of a webpage used in the one or more of the user's Internet interaction sessions.

3 . The method of claim 1 , wherein the predefined rules define content to be extracted according to parameters selected from the group consisting of: a title of webpage(s), date/time webpage(s) created, product(s) viewed, prices offered, product categories (used vs. new, wholesale vs. retail, etc.), customer search words, customer highlighting or selection of products, a type of web object, the presence or frequency of certain key-words, how long ago a webpage was viewed, the amount of time a webpage is viewed, a number of times or which different items are selected on a webpage, and the order in which the webpage was viewed.

4 . The method of claim 1 comprising generating a summary of the user's past or current Internet interaction sessions and providing said summary to the contact center agent while the contact center agent is communicating with said user for guiding the user's Internet interaction.

5 . The method of claim 4 , wherein the summary comprises data selected from the group consisting of: a description of the user's interaction sessions, product viewed, and prices offered.

6 . The method of claim 1 comprising, using a web player, providing the agent with a playback of the user's past or current Internet interaction sessions during the telephone call between the agent and the user.

7 . The method of claim 1 comprising capturing the Internet server traffic using a passive sniffing device.

8 . The method of claim 1 , wherein the Internet server traffic is captured over one media channel and the agent and user communicate over another media channel.

9 . The method of claim 1 , wherein the information analyzed in the user's Internet interaction sessions includes key-words the user used for searching.

10 . The method of claim 1 , wherein the recommendation includes information for technical support, selling, “up-selling,” “cross-selling,” or filling in surveys.

11 . The method of claim 1 , wherein the recommendation is provided to the contact center agent in real-time.

12 . A system for monitoring a user's interactions with Internet-based programs or documents, the system comprising:

a processor to extract content from Internet server traffic according to predefined rules, associate the extracted content with one or more of a user's Internet interaction sessions, index the user's Internet interaction sessions, automatically compare one or more of the user's Internet interaction sessions to one or more modeled sessions by executing a web analyzer to generate a recommendation of one or more future session paths from the modeled sessions for guiding the user's Internet interactions and to provide the recommendation of the future session paths from the modeled sessions on screen to a contact center agent while the contact center agent is communicating with said user during a telephone call initiated by the user between the agent and the user; and

a storage device to store the one or more of the user's Internet interaction sessions.

13 . The system of claim 12 comprising a passive sniffing device to capture the Internet server traffic.

14 . The system of claim 12 comprising a first media channel over which the Internet server traffic is captured and a second different media channel over which the agent and user communicate.

15 . The system of claim 12 comprising a computer and telephone operated by the user, wherein an Internet connection at the user's computer is monitored for Internet server traffic and the telephone call between the contact center agent and the user telephone triggers the processor to send the contact center agent the recommendation.

16 . The system of claim 12 comprising a text capturing module, wherein the text capturing module identifies the user by capturing text on a screen element of a webpage used in the one or more of the user's Internet interaction sessions.

17 . The system of claim 12 , wherein the processor generates a summary of the user's past or current Internet interaction sessions provided to the contact center agent while the contact center agent is communicating with said user for guiding the user's Internet interaction.

18 . The system of claim 12 comprising a workstation operated by the contact center agent, the workstation having a display and a web player, wherein the display uses the web player displays a playback of the user's past or current Internet interaction sessions during the telephone call between the agent and the user.

19 . The system of claim 12 comprising a semi-automated and semi-live contact center agent.

20 . The method of claim 1 , wherein the one or more modeled sessions are real-life sessions generated by interactions of one or more other users.

21 . The method of claim 1 , wherein the one or more modeled sessions are generated in a computer-training environment by a trainer.

22 . The method of claim 1 , wherein the one or more modeled sessions are retrieved from a pool of sessions that most closely matches features used in the user's current Internet interaction session.

23 . The method of claim 1 , wherein the one or more modeled sessions include a fixed linear path of webpages to browse.

24 . The method of claim 1 , wherein the one or more modeled sessions include a dynamic tree-structure of paths, where each chosen webpage path leads to a different predicted modeled future session path.

25 . The method of claim 1 , wherein the information analyzed in the user's Internet interaction sessions includes product details viewed.

26 . The method of claim 1 comprising automatically and passively determining the user identity of the extracted content, by the web analyzer using the processor, by passively sniffing the Internet server traffic.

27 . The method of claim 1 comprising displaying to the agent, during the telephone call between the agent and the user, a key-value summary of the extracted content associated with one or more of the user's Internet interaction sessions.

28 . The method of claim 1 comprising receiving the predefined rules from a user which determines the web elements to be extracted on a web page.

29 . A method for monitoring a user's interactions with Internet-based programs or documents, the method comprising:

extracting a webpage screen element, by a web analyzer using a processor, from Internet server traffic according to predefined rules;

associating the extracted webpage screen element with one of a plurality of a user's Internet interaction sessions;

storing and indexing the plurality of the user's Internet interaction sessions;

automatically analyzing, by the web analyzer using the processor, the plurality of the user's Internet interaction sessions to generate a recommendation for guiding the user's Internet interactions; and

providing the recommendation, which is generated based on said automatically analyzing the user's plurality of Internet interaction sessions, on screen to a contact center agent while the contact center agent is communicating with said user during a telephone call initiated by the user between the agent and the user.

30. A method for monitoring a user's interactions with Internet-based programs or documents, the method comprising:

extracting content from Internet server traffic according to predefined rules;

associating the extracted content with one or more of a user's Internet interaction sessions;

storing and indexing the user's Internet interaction sessions;

automatically comparing, by a web analyzer using a processor, one or more of the user's Internet interaction sessions to one or more modeled sessions to generate a recommendation of one or more future session paths from the modeled sessions for guiding the user's Internet interactions and to offer up-sell or cross-sell options according to an analysis of an Internet interaction and business rules in a recommendations database;

providing the recommendation of the future session paths from the modeled sessions on screen to a contact center agent while the contact center agent is communicating with said user during a telephone call initiated by the user between the agent and the user.

31. The method of claim 30 , comprising identifying the user by text captured on a screen element of a webpage used in the one or more of the user's Internet interaction sessions.

32. The method of claim 30 , wherein the predefined rules define content to be extracted according to parameters selected from the group consisting of:

a title of webpage(s), date/time webpage(s) created, product(s) viewed, prices offered, product categories (used vs. new, wholesale vs. retail, etc.), customer search words, customer highlighting or selection of products, a type of web object, the presence or frequency of certain key-words, how long ago a webpage was viewed, the amount of time a webpage is viewed, a number of times or which different items are selected on a webpage, and the order in which the webpage was viewed.

33. The method of claim 30 , comprising generating a summary of the user's past or current Internet interaction sessions and providing said summary to the contact center agent while the contact center agent is communicating with said user for guiding the user's Internet interaction.

34. The method of claim 33 , wherein the summary comprises data selected from the group consisting of:

a description of the user's interaction sessions, product viewed, and prices offered.

35. The method of claim 30 , comprising, using a web player, providing the agent with a playback of the user's past or current Internet interaction sessions during the telephone call between the agent and the user.

36. The method of claim 30 , comprising capturing the Internet server traffic using a passive sniffing device.

37. The method of claim 30 , wherein the Internet server traffic is captured over one media channel and the agent and user communicate over another media channel.

38. The method of claim 30 , wherein the information analyzed in the user's Internet interaction sessions includes key-words the user used for searching.

39. The method of claim 30 , wherein the recommendation includes information for technical support, selling, “up-selling”, “cross-selling”, or filling in surveys.

40. The method of claim 30 , wherein the recommendation is provided to the contact center agent in real-time.

41. The method of claim 30 , wherein the one or more modeled sessions are real-life sessions generated by interactions of one or more other users.

42. The method of claim 30 , wherein the one or more modeled sessions are generated in a computer-training environment by a trainer.

43. The method of claim 30 , wherein the one or more modeled sessions are retrieved from a pool of sessions that most closely matches features used in the user's current Internet interaction session.

44. The method of claim 30 , wherein the one or more modeled sessions include a fixed linear path of webpages to browse.

45. The method of claim 30 , wherein the one or more modeled sessions include a dynamic tree-structure of paths, where each chosen webpage path leads to a different predicted modeled future session path.

46. The method of claim 30 , wherein the information analyzed in the user's Internet interaction sessions includes product details viewed.

47. The method of claim 30 , comprising automatically and passively determining the user identity of the extracted content, by the web analyzer using the processor, by passively sniffing the Internet server traffic.

48. The method of claim 30 , comprising displaying to the agent, during the telephone call between the agent and the user, a key-value summary of the extracted content associated with one or more of the user's Internet interaction sessions.

49. The method of claim 30 , comprising receiving the predefined rules from a user which determines the web elements to be extracted on a web page.

50. The method of claim 30 , comprising indexing interactions across multiple different channels of communication to create a uniform database of interactions.

51. The method of claim 30 , comprising identifying a probable cause of a user switching from one communication channel to another.

52. A system for monitoring a user's interactions with Internet-based programs or documents, the system comprising:

a processor to extract content from Internet server traffic according to predefined rules, associate the extracted content with one or more of a user's Internet interaction sessions, index the user's Internet interaction sessions, automatically compare one or more of the user's Internet interaction sessions to one or more modeled sessions by executing a web analyzer to generate a recommendation of one or more future session paths from the modeled sessions for guiding the user's Internet interactions and to offer up-sell or cross-sell options according to an analysis of an Internet interaction and business rules in a recommendations database and to provide the recommendation of the future session paths from the modeled sessions on screen to a contact center agent while the contact center agent is communicating with said user during a telephone call initiated by the user between the agent and the user; and

a storage device to store the one or more of the user's Internet interaction sessions.

53. The system of claim 52 , comprising a passive sniffing device to capture the Internet server traffic.

54. The system of claim 52 , comprising a first media channel over which the Internet server traffic is captured and a second different media channel over which the agent and user communicate.

55. The system of claim 52 , comprising a computer and telephone operated by the user, wherein an Internet connection at the user's computer is monitored for Internet server traffic and the telephone call between the contact center agent and the user telephone triggers the processor to send the contact center agent the recommendation.

56. The system of claim 52 , comprising a text capturing module, wherein the text capturing module identifies the user by capturing text on a screen element of a webpage used in the one or more of the user's Internet interaction sessions.

57. The system of claim 52 , wherein the processor is configured to generate a summary of the user's past or current Internet interaction sessions provided to the contact center agent while the contact center agent is communicating with said user for guiding the user's Internet interaction.

58. The system of claim 52 , comprising a workstation operated by the contact center agent, the workstation having a display and a web player, wherein the display uses the web player to display a playback of the user's past or current Internet interaction sessions during the telephone call between the agent and the user.

59. The system of claim 52 , comprising a semi-automated and semi-live contact center agent.

60. The system of claim 52 , wherein the processor is to index interactions across multiple different channels of communication to create a uniform database of interactions.

61. The system of claim 52 , wherein the processor is to identify a probable cause of a user switching from one communication channel to another.

62. A method for monitoring a user's interactions with Internet-based programs or documents, the method comprising:

extracting a webpage screen element, by a web analyzer using a processor, from Internet server traffic according to predefined rules;

associating the extracted webpage screen element with one of a plurality of a user's Internet interaction sessions;

storing and indexing the plurality of the user's Internet interaction sessions;

automatically analyzing, by the web analyzer using the processor, the plurality of the user's Internet interaction sessions to generate a recommendation for guiding the user's Internet interactions and to offer up-sell or cross-sell options according to an analysis of an Internet interaction and business rules in a recommendations database; and

providing the recommendation, which is generated based on said automatically analyzing the user's plurality of Internet interaction sessions, on screen to a contact center agent while the contact center agent is communicating with said user during a telephone call initiated by the user between the agent and the user.

Assignments (3)
SECURITY INTEREST Recorded Feb 26, 2026
From: NICE LTD; NICE SYSTEMS INC.; NICE SYSTEMS TECHNOLOGIES INC.; INCONTACT, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 074986/0208 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 27, 2023
From: LIBERMAN BEN-AMI, HADAS; PORTMAN, LEON; MARCO, YUVAL; GOLAN, YOSEF; HABA, SHLOMI; SMITH, IFTACH; RONEN, YIZHAR; ETSION, YOHAY; CHER, IGOR; DAMTY, NAAMA; FRENKEL, ASSAF; BARUCH, UZI
To: NICE SYSTEMS LTD.
Reel/Frame 064086/0114 →
CHANGE OF NAME Recorded Jun 27, 2023
From: NICE-SYSTEMS LTD.
To: NICE LTD.
Reel/Frame 064144/0688 →
Continuity (5)
Continuation 17337725 · Jun 3, 2021
Continuation 16708769 · Dec 10, 2019
Continuation 16049319 · Jul 30, 2018
Reissue 13305279 · Nov 28, 2011
Reissue 13305279 · Nov 28, 2011
References Cited (71)
US 5535256A · Maloney et al. · 1996 [cited by applicant]
US 6346952B1 · Shtivelman · 2002 [cited by applicant]
US 6721416B1 · Farrell · 2004 [cited by applicant]
US 6741697B2 · Benson et al. · 2004 [cited by applicant]
US 6748072B1 · McGraw et al. · 2004 [cited by applicant]
US 6904143B1 · Peterson et al. · 2005 [cited by applicant]
US 6922466B1 · Peterson et al. · 2005 [cited by applicant]
US 6922689B2 · Shtivelman · 2005 [cited by applicant]
US 6959078B1 · Eilbacher et al. · 2005 [cited by applicant]
US 6970554B1 · Peterson et al. · 2005 [cited by applicant]
US 6981040B1 · Konig et al. · 2005 [cited by applicant]
US 7035926B1 · Cohen et al. · 2006 [cited by examiner]
US 7165105B2 · Reiner et al. · 2007 [cited by applicant]
US 7200614B2 · Reid et al. · 2007 [cited by applicant]
US 7246078B2 · Vincent · 2007 [cited by applicant]
US 7370004B1 · Patel et al. · 2008 [cited by applicant]
US 7616756B2 · Blackwood et al. · 2009 [cited by applicant]
US 7644134B2 · Cohen et al. · 2010 [cited by applicant]
US 7844504B1 · Flockhart et al. · 2010 [cited by applicant]
US 7853800B2 · Watson et al. · 2010 [cited by applicant]
US 7885820B1 · Mancisidor · 2011 [cited by examiner]
US 7949574B2 · Patel et al. · 2011 [cited by applicant]
US 7958234B2 · Thomas et al. · 2011 [cited by examiner]
US 7962551B2 · Mukundan et al. · 2011 [cited by applicant]
US 7962616B2 · Kupferman et al. · 2011 [cited by applicant]
US 8271332B2 · Mesaros · 2012 [cited by applicant]
US 8326694B2 · Patel et al. · 2012 [cited by applicant]
US 8352396B2 · Forman et al. · 2013 [cited by applicant]
US 8396834B2 · Bahadori et al. · 2013 [cited by applicant]
US 8408061B2 · Thomas · 2013 [cited by applicant]
US 8676895B1 · Roy et al. · 2014 [cited by applicant]
US 20020083167A1 · Costigan et al. · 2002 [cited by examiner]
US 20020087385A1 · Vincent · 2002 [cited by examiner]
US 20070208682A1 · Mancisidor et al. · 2007 [cited by examiner]
US 20080195665A1 · Mason et al. · 2008 [cited by applicant]
US 20080279353A1 · Schambach · 2008 [cited by examiner]
US 20110184905A1 · Phillips et al. · 2011 [cited by applicant]
US 20120195422A1 · Famous · 2012 [cited by applicant]
US 20120303598A1 · Newnham et al. · 2012 [cited by applicant]
US 20120303621A1 · Newnham et al. · 2012 [cited by applicant]
US 20130024405A1 · Newnham et al. · 2013 [cited by applicant]
US 20130080358A1 · Newnham et al. · 2013 [cited by applicant]
US 20130080377A1 · Newnham et al. · 2013 [cited by applicant]
US 20130110750A1 · Newnham et al. · 2013 [cited by applicant]
Robert Bagley, “Uncovering Customer Anonymity When People Want to be Found,” Journey Science, https://blog.clickfox.com/blog/uncovering-customer-anonymity-people-want-found/, printed Jul. 25, 2018, Denver Headquarters, … [cited by applicant]
Dan Woods, “Leveraging Analytics Stackks: How the ClickFox Platform Supports All Levels of Productization,” Forbes Magazine, https://www.forbes.com/sites/danwoods/2017/10/31/leveraging-analytics-stacks-how-the-clickfox-… [cited by applicant]
“Amended Complaint for Patent Infringement,” Nov. 16, 2015, [cited by applicant]
“ClickFox, Inc.'s Motion to Dismiss for Failure to State a Claim as to Patentable Subject Matter,” Dec. 16, 2015, [cited by applicant]
“Defendant ClickFox, Inc.'s Memorandum of Law in Support of Its Motion to Dismiss for Failure to State a Claim as to Patentable Subject Matter,” Dec. 16, 2015, [cited by applicant]
“Declaration of Puja Patel Lea, Esq.,” Dec. 16, 2015, Dec. 16, 2015, [cited by applicant]
“ClickFox, Inc.'s Motion to Dismiss for Failure to State a Claim as to Induced Infringement,” Dec. 16, 2015, [cited by applicant]
“Defendant ClickFox, Inc.'s Memorandum of Law in Support of Its Motion to Dismiss for Failure to State a Claim as to Induced Infringement,” Dec. 16, 2015, [cited by applicant]
“Plaintiffs Nice Systems Ltd's and Nice Systems, Inc.s' Answering Brief in Opposition to Defendant ClickFox, Inc.'s Motion to Dismiss for Failure to State a Claim as to Patentable Subject Matter,” Feb. 1, 2016, [cited by applicant]
“Declaration of Guy Yonay in Opposition to Defendant ClickFox, Inc.'s Motion to Dismiss for Failure to State a Claim as to Patentable Subject Matter,” Feb. 1, 2016, [cited by applicant]
“Plaintiffs Nice Systems Ltd's and Nice Systems, Inc.s' Answering Brief in Opposition to Defendant ClickFox, Inc.'s Motion to Dismissfor Failure to State a Claim as to Induced Infringement,” Feb. 1, 2016, [cited by applicant]
“Defendant ClickFox, Inc.'s Reply Memorandum of Law in Support of Its Motion to Dismiss for Failure to State a Claim as to Patentable Subject Matter,” Feb. 22, 2016, [cited by applicant]
“Defendant ClickFox, Inc.'s Reply in Support of Its Motion to Dismiss for Failure to State a Claim as to Inducement of Infringement and Direct Infringement,” Feb. 22, 2016, [cited by applicant]
“Transcript of Section 101 Motion to Dismiss Before the Honorable Richard G. Andrews United States District Judge,” Apr. 26, 2016, [cited by applicant]
“Memorandum Opinion,” Sep. 15, 2016, [cited by applicant]
“Order Granting Motion to Dismiss,” Sep. 15, 2016, [cited by applicant]
“Plaintiffs' Notice of Appeal,” Oct. 13, 2016, [cited by applicant]
“Brief for Plantiffs-Appellants Nice Ltd. and Nice Systems Inc.,” Jan. 12, 2017, Federal Circuit appeal No. 2017-1041, [cited by applicant]
“Brief for Plaintiffs-Appellants Nice Ltd. and Nice Systems Inc.,” Jan. 12, 2017, Federal Circuit apeal No. 2017-1041, [cited by applicant]
“Brief for Appellee ClickFox Inc.,” Mar. 23, 2017, Federal Circuit appeal No. 2017-1041, [cited by applicant]
“Reply Brief for Plaintiffs-Appellants Nice Ltd. and Nice Systems Inc.,” Apr. 20, 2017, Federal Circuit appeal No. 2017-1041. [cited by applicant]
“Joint Appendix (APPX1-APPX602),” Apr. 27, 2017, Federal Circuit appeal No. 2017-1041. [cited by applicant]
“Citation of Supplemental Authority,” Aug. 18, 2017, [cited by applicant]
“Notice of Supplemental Authority,” Aug. 25, 2017, [cited by applicant]
“Notice of Entry of Judgment Without Opinion,” Oct. 11, 2017, Civ No. 2017-1041, Federal Circuit appeal No. 2017-1041. [cited by applicant]
Federal Circuit Oral Argument Transcript, Case 17-1041, Oct. 5, 2017. [cited by applicant]
Shinde et al., “A New Approach for On Line Recommender System in Web Usage Mining”, 2008 International Conference on Advanced Computer Theory and Engineering. [cited by applicant]