Award for IVR Self-Service:

Transcription

1 Call Center FCR Best Practice Award Contact Center FCR Best Practice AwardWinner Winner Award for IVR Self-Service: VSP Vision Care published

2 Best Practice Success Story Company Description VSP Global helps more than 77 million people see better by providing affordable, accessible, and high-quality eye care and eyewear. VSP s complementary businesses combine superior eye care insurance, high-fashion frames, customized lenses, ophthalmic technology, and retail solutions. VSP Global businesses, operating in 100 countries in the U.S., Australia, United Kingdom, Canada, and Ireland, include VSP Vision Care, Marchon Eyewear Inc., Eyefinity, VSP Optics Group, and VSP Retail. As a not-for-profit business, we are committed to bringing vision to those who can t come to us, and to reimagining how eye care and eyewear are delivered globally. To date, through Eyes of Hope programs and partnering organizations that include the American Red Cross, VSP Global companies have invested close to $175 million in no-cost eye care and eyewear for nearly one million adults and children in need. VSP Contact Center Description Locations Rancho Cordova, California, USA Columbus, Ohio, USA Call Types General inquiries, benefit coverage, claims, and enrollment for eye care Customer Types Members (50%) and providers (50%) CSR Headcount Over 600 FTE CSRs Contact Channels Phone, , IVR, website, and social media Operating Hours Monday to Friday, 5:00 am to 8:00 pm PST and weekends

3 Contact Volume Over 13 million calls/ s annually including automation SQM Awards Won by VSP Vision Care Call Center of the Year (California) (2008 & 2009) (California & Ohio) (2015) Call Center World Class Certification (California & Ohio) (2006 to 2015) Highest Customer Satisfaction for Insurance Industry (2004 to 2015) Highest Customer Satisfaction for Business to Business (2010 to 2013, 2015) Highest Employee Satisfaction for Call Center Industry (2008 to 2009, 2015) Highest Employee Satisfaction for Insurance Industry (2004 to 2010, 2015) Most Improved Employee Satisfaction (Ohio) (2005) (California & Ohio) (2015)

4 IVR Self-Service Channel In 2013 we began a journey to redesign our member IVR. At the time, our existing IVR application was a mixture of Speech Recognition and Touch-Tone/DTMF Menu options. Containment rate averaged 7% and our authentication rate averaged 53%. We believed that by implementing a Natural Language application we could increase both containment and authentication rates and by doing so, improve our customer s experience. We partnered with Nuance, the leading Speech and Natural Language IVR vendor, to design and implement a more user friendly self-service application. In order to better understand what our customers needed through self-service, we looked at the top call reasons. We quickly learned that most members were interested in learning about their eligibility and how their benefits worked. The CSRs had a natural flow for explaining eligibility and benefit information, so we decided to mirror their approach in our IVR. Next we needed to determine what we wanted the voice of IVR to convey. VSP prides ourselves on our focus and care for our customers, so we determined the following key attributes were required for our new voice talent: Caring, Confident, Trustworthy, Intelligent, Sincere, Supportive, Respectful. Using these core traits, we identified our top five vendor voice selections and then solicited feedback from our internal and external customers in order to select the final candidate. Finally, we needed to determine what information would be useful to our CSRs if the caller opted out of IVR. We developed logic that would allow us to pop the last spoken request from the member. This would allow the CSR to know what the customer had requested in the IVR before reaching them. With all the requirements and design elements in place, we then built our new application, ran it through acceptance testing including a usability test with members in a behind the mirror lab environment, and then rolled the application out to a small percentage of callers towards the end of By early 2015, we had the new application up and running for all our customers. Results were in, and they looked great. Containment increased to 13%, a 6% point increase. This reflects an 86% growth in containment. We nearly doubled our containment rates! Authentication increased to 54% (up 1%). We receive approximately 475,000 member calls each month, so both of these statistics made a measurable difference in our center. We had implemented a Natural Language system that was easy to interact with in order to obtain eligibility, benefit information, provider

5 listings, and claims instructions. The member no longer needed to listen to a menu and guess the correct option. They could simply speak what they needed assistance with. Once they obtained the information they needed, there was no need to navigate back to a menu if they had further questions. All they need to do is speak their next question. Some of our competitors still use Touch-Tone Menus using DTMF or Speech Recognition versus Natural Language. We also utilize ANI recognition to begin our authentication or ID of the customer. If we recognize the ANI, the caller is prompted for their ID number only. If we do not recognize the ANI, we request ID number and date of birth. During the testing phase of the project we utilized a service from our vendor, Nuance, called Wizard of Oz. It allowed us to observe members using our IVR system to complete predetermined tasks in a test environment. We then took the discoveries and applied them to improving the application. During the tests, we were surprised to see that it was awkward for members to disconnect the call when they were done. With the Natural Language logic, members felt they were talking to a person so social etiquette made it difficult for them to hang up. Based on that finding, we added prompting that told them, If you re done here, feel free to hang up. We also utilize Nuance services to fine tune our IVR at least once a year. Nuance is able to determine key areas where a member may be having issues navigating the system based on containment rates as well as what the member is saying throughout the application. Finally, if a member provides feedback to a CSR, the CSR can complete a form. The IVR designers then analyze the feedback and make changes as appropriate. In one scenario, we found it was too difficult to opt out of the IVR, so changes were made to limit the number of tries before the member was routed to a CSR. When we implemented the Natural Language IVR, we saw a 6% point increase or 86% growth in containment and a 1% point increase in authentication. On average, we receive around 475,000 calls a month. That equates to approximately 28,500 less calls routed to a CSR each month and 4,000 more successful screen pop of the member s information to the CSR each month. This reduced handle time and increased both the customer and CSR experience. Without the success of our IVR, handle times and utilization would be higher, satisfaction would be greatly decreased, and staffing levels would be unsustainable.

6 Our CSRs receive a screen pop that indicates where the member was in the IVR application before they opted out to a CSR. This can help the CSR determine if they were trying to locate a provider, obtain benefit information, have questions on a claim, etc. Our fail out rate is approximately 5% and includes speech as well as back-end system errors. Year over year Call Center CSAT for those surveys where the member said they were repeat callers due to IVR issues, shows a 20% increase in CSAT for this segment. During the 6-month window surrounding the implementation we saw an increase in IVR calls and a decrease in live calls answered, which translates to improved FCR.