1. © 2008 SpeechCycle, Inc. More Than Call Steering Managing Dynamic Contextual Complexity Phillip Hunter VP, Application Design/Development SpeechTek NYC 2008

2. © 2008 SpeechCycle, Inc. Software company established in 2001, based in NYC Natural language, advanced dialogs and enterprise web services Immersive caller experience Processing millions of calls every month Software as a Service (SaaS) Premise-based Managed Services SpeechCycle is the leading provider of Rich Phone Applications: About Us

3. © 2008 SpeechCycle, Inc. Dynamic Contextual Complexity Greater demand for highly complex speech applications –deep (insurance, troubleshooting) –broad (call routing, finance) Customers and callers require even more complexity with ever increased simplicity of access This requires advances in handling data, grammars, and code infrastructures –More of the right effort, not better assembly lines

4. © 2008 SpeechCycle, Inc. Dynamic Contextual Complexity Support robust and flexible interactions which: –allow callers to request dozens of unique tasks in thousands of ways –Involve contexts that vary in real-time –involve potentially dozens of turns –Must preserve knowledge and context across time and applications –Present relevant info at the right time and sometimes unrequested (outage)

5. © 2008 SpeechCycle, Inc. Call Steering Req’ts High degree of complexity Shorter than troubleshooting (~40 secs AHT) Nearly sixty destinations each with multiple unique details –Speech application destinations (ours) –DTMF application destinations –Agent destinations –DTMF menu destinations –Varies by type of subscription and billing system

6. © 2008 SpeechCycle, Inc. Call Steering Req’ts 250+ unique SLM slots identified during requirements –Most based on our own troubleshooting SLM data –Plus billing call reasons, service changes, appointments, sales, etc. –50+ more semantically unique slots that can be arrived at with follow-up questions Many semantic items funneling to many destinations Very carefully defined and controlled requirements

7. © 2008 SpeechCycle, Inc. The Challenges Oh, and… –No SLM data for the non-troubleshooting slots (over 50% of anticipated traffic) not allowed to do data collection –Be better than touch-tone “Our callers know the system” Some recent studies cast doubt on ability of speech to improve efficacy –Very aggressive performance targets Solve the problem of 25% misroutes 75% proper routing off the bat –meaning not sending callers back to a base level DTMF menu and did send callers to correct points 80% proper routing after 30 days of pilot (excludes hang-ups)

8. © 2008 SpeechCycle, Inc. The Challenges Oh, and… –Could ask the caller only 3 questions (excluding confirmation and single level of recovery questions) –Router does not answer the call Up to 10 seconds of silence during transfer Seamless transitions to legs of the speech troubleshooting apps Had to go beyond traditional call flow logic to handle this

9. © 2008 SpeechCycle, Inc. The Approach Guerrilla data collection and data extrapolation –Constructed utterances –Company-wide SLM training calls Dynamic logic engine wrapped in a highly flexible UI –Tight blend of open and directed prompts –Dynamic disambiguation (changes order based on context) –Multiple ways to ask almost every question –Recognize and handle recent callers –New confirmation technique

10. © 2008 SpeechCycle, Inc. The Approach

11. © 2008 SpeechCycle, Inc. The Approach

12. © 2008 SpeechCycle, Inc. The Approach

13. © 2008 SpeechCycle, Inc. The Approach Rich routing application is aware of our troubleshooting applications –Context and data passed (level of ambiguity, specific call reason, etc.) Handles outage detection and queuing callbacks Select calls re-enter from troubleshooting with context sensitivity

14. © 2008 SpeechCycle, Inc. Results = Success! 2nd week we hit 94% proper routing Using transcriptions and annotations, drastic improvements in SLM by 4th week –From low 60%s to mid 70%s –Slight rise in routing percentage

15. © 2008 SpeechCycle, Inc. Results = Success! Call flow adjustments plus improved SLM led to ~96% routing by 6th week –Using automatically generated SLM with less than 20K training utterances –Incorporating other real world behaviors by adding more intelligence and flexibility Adding to SLM and call-flow have us aiming for 98 – 99%

16. © 2008 SpeechCycle, Inc. Summary As always… –Define requirements and success measure clearly –Realize that achieving the goal might take new technology or new uses of it, but you still can’t replace: –Working hard to be creative, ingenious, thorough

17. © 2008 SpeechCycle, Inc. Confidential 17 Questions?