METHOD AND APPARATUS FOR OPTIMIZING CUSTOMER SERVICE ACROSS MULTIPLE CHANNELS

• US 20140019886A1
• Filed: 09/20/2013
• Published: 01/16/2014
• Est. Priority Date: 12/23/2009
• Status: Active Grant

• Current Assignee: [24]7.ai, Inc.
• Original Assignee: 24/7 Customer Incorporated
• Inventors: KANNAN, Pallipuram V., VIJAYARAGHAVAN, Ravi
• Granted Patent: US 10,200,420 B2
• Time in Patent Office: Days
• US Class Current: 715/758
• CPC Class Codes: H04L 12/1822 Conducting the conference, e.g. admission, detection, selection or grouping of participants, correlating users to one or more conference sessions, prioritising transmission
• CPC Class Codes: H04L 12/1827 Network arrangements for conference optimisation or adaptation
• CPC Class Codes: H04L 51/04 Real-time or near real-time messaging, e.g. instant messaging [IM]
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04M 3/5166 in combination with interactive voice response systems or voice portals, e.g. as front-ends
• CPC Class Codes: H04M 3/5191 interacting with the Internet
• CPC Class Codes: H04M 7/003 Click to dial services

Abstract

A method and apparatus for a computer-implemented technique for maximizing customer satisfaction and first call resolution, including converting telephone calls into online chats, while minimizing cost is provided. Techniques for incorporating analytics as applied to customer data into particular strategies for call deflection, targeting particular individuals to increase chat acceptance rate, and computing a customer'"'"'s wait time are also provided.

Claims

1. A computer-implemented method for user Web containment, comprising:

for a user on a particular Web page in a multi-channel system comprising each of a call channel, a chat channel, a self-service channel, and an assisted self-service channel, providing, by a Web containment processor, a Web containment strategy; and

said Web containment strategy automatically, with or without involving an agent, causing said user on said particular Web page to stay on said Web page and not switch to a call channel when said Web containment strategy is successful;

said causing being effected by any of;

inviting the user to said chat channel;

presenting the user with self-service opportunities on said self-service channel; and

presenting the user with assisted self-service opportunities on said assisted self-service channel.

2. The method of claim 1, said Web containment strategy comprising:

identifying, by said Web containment processor, top call driver pages;

identifying, by said Web containment processor, Web journeys that correspond to each call driver page;

computing, by said Web containment processor, Web traffic on the call driver pages and on the pages of the corresponding Web journey; and

based at least in part on said computed Web traffic, computing by said Web containment processor an estimation of chat volume.

3. The method of claim 1, further comprising:

providing, by a targeting processor, a targeting user strategy, said targeting user strategy applying a derived statistical model to compute a chat acceptance score for a user and when said chat acceptance score exceeds a particular threshold, offering the user to interact on a chat channel.

4. The method of claim 1, wherein said Web containment strategy comprises:

determining, by a processor, voice call drivers based on customer relationship management (CRM) data; and

targeting, by a processor, particular issue types based on said voice call drivers and an amenability of said drivers to be resolved over the Web.

5. The method of claim 4, further comprising:

identifying, by a processor, customer journeys corresponding to the issue types;

determining, by a processor, uniform resource locators (URLs) corresponding to the customer journeys; and

determining, by a processor, a hot lead rate based in part on a hierarchical level of the URL and attributes generated from customer behavioral attributes and customer journey attributes.

6. The method of claim 1, further comprising:

determining, by a processor, an acceptance rate from a multivariate model and using said acceptance rate to determine when to present a user with an invitation to chat.

7. The method of claim 1, further comprising:

identifying, by a processor, and servicing, by a servicing processor, optimal segments of URLs based in part on exit rates and user ratings of said URLs.

8. The method of claim 1, further comprising:

using, by a processor, text mining in part to identify pages to target for chat.

9. An apparatus for effecting user Web containment, comprising:

for a user on a particular Web page in said multi-channel system comprising each of a call channel, a chat channel, a self-service channel, and an assisted self-service channel, a Web containment processor configured for executing a Web containment strategy;

said Web containment strategy automatically, with or without involving an agent, causing said user on said particular Web page to stay on said Web page and not switch to a call channel when said Web containment strategy is successful; and

said Web containment processor configured for executing any of;

inviting the user to said chat channel;

presenting the user with self-service opportunities on said self-service channel; and

presenting the user with assisted self-service opportunities on said assisted self-service channel.

10. The apparatus of claim 9, said Web containment processor further configured for executing said Web containment strategy by:

identifying top call driver pages;

identifying Web journeys that correspond to each call driver page;

determining Web traffic on the call driver pages and on the pages of the corresponding Web journey; and

based in part on said computed Web traffic, determining an estimation of chat volume.

11. The apparatus of claim 9, further comprising:

a targeting processor configured for executing a targeting user strategy, said targeting user strategy applying a derived statistical model to compute a chat acceptance score for a user and when said chat acceptance score exceeds a particular threshold, offering the user to interact on a chat channel.

12. The apparatus of claim 9, said Web containment processor further configured for executing said Web containment strategy by:

determining voice call drivers based on customer relationship management (CRM) data; and

targeting particular issue types based on said voice call drivers and an amenability of said drivers to be resolved over the Web.

13. The apparatus of claim 12, further comprising:

a processor configured for identifying customer journeys corresponding to the issue types;

said processor configured for determining uniform resource locators (URLs) corresponding to the customer journeys; and

said processor configured for determining a hot lead rate based in part on a hierarchical level of the URL and attributes generated from customer behavioral attributes and customer journey attributes.

14. The apparatus of claim 9, further comprising:

a processor configured for determining an acceptance rate from a multivariate model and using said acceptance rate to determine when to present a user with an invitation to chat.

15. The apparatus of claim 9, further comprising:

a processor configured for identifying and servicing optimal segments of URLs based in part on exit rates and user ratings of said URLs.

16. The apparatus of claim 9, further comprising:

a processor configured for using text mining in part to identify pages to target for chat.

17. A computer implemented method for user Web containment, comprising:

gathering call data;

identifying top call drivers;

identifying Web journeys that correspond to each particular call driver;

once unique Web journeys for each call driver are identified, computing Web traffic on call driver pages and on pages of corresponding Web journeys;

using gathered Web analytic data and Web traffic data to identify visitor behavior on call driver-related pages; and

based upon said identified visitor behavior on call driver-related pages, any of;

inviting a user to a chat channel;

presenting the user with self-service opportunities on a self-service channel; and

presenting the user with assisted self-service opportunities on an assisted self-service channel.

18. The method of claim 17, further comprising:

determining a percentage of users who end up chatting for a given number of users for a particular vertical, based upon a percentage of users who are invited to chat and a percentage of said users who are served.

19. The method of claim 17, further comprising:

estimating chat volume; and

once said estimation of chat volume is determined, determining a number of agents required to effect Web containment.

20. The method of claim 17, wherein said call data comprises customer relationship management data (CRM), wherein said CRM comprises transaction data related to a call, including any of call time, date, total call handle time, agent who took the call, call issue type handled, attributes of the user who called, attributes of the agent who took the call, and attributes of prior history of interactions with the user.

21. The method of claim 17, wherein said call drivers comprise issues that users face that drive call volumes;

wherein a top call driver is an issue that drives the most calls.

22. The method of claim 17, wherein Web journeys comprise one or more footprints on a website left by any website visitor, said footprints including any of a visitor'"'"'s referral page, landing page, clickstream of page visited, wait time in each of said pages, number of pages visited, and exit page

23. The method of claim 17, wherein Web traffic comprises a complete distribution of visitors at a page and a distribution of how long visitors spend on the page.