This publish was co-written with Tony Momenpour and Drew Clark from KYTC.
Authorities departments and companies function contact facilities to attach with their communities, enabling residents and prospects to name to make appointments, request companies, and generally simply ask a query. When there are extra calls than brokers can reply, callers get positioned on maintain with a message corresponding to the next: “We’re experiencing larger than regular name volumes. Your name is essential to us, please keep on the road and your name will probably be answered within the order it was obtained.”
Until the maintain music is especially good, callers don’t usually get pleasure from having to attend—it wastes money and time. Some contact facilities play automated messages to encourage the caller to go away a voicemail, go to the web site, or name again later. These choices are unsatisfying to callers who simply need to ask an agent a query to get a solution rapidly.
One resolution is to have sufficient educated brokers accessible to take all of the calls straight away, even throughout instances of unusually excessive name volumes. This could remove maintain instances and be sure that callers obtain quick responses. The important thing to creating this strategy sensible is to enhance human brokers with scalable, AI-powered digital brokers that may handle callers’ wants for a minimum of a number of the incoming calls. When a digital agent efficiently addresses a caller’s enquiry, the result’s a cheerful caller, decrease common maintain instances for all callers, and decrease prices. Gartner’s Customer Service and Support Leader poll estimates that dwell channels corresponding to telephone and dwell chat value a median of $8.01 per contact, whereas self-service channels value about $0.10 per contact—a digital agent can probably save $7.91 (98%) for each name it efficiently handles.
A digital agent doesn’t should deal with each name, and it most likely shouldn’t attempt—some portion of calls are probably served finest with a human contact, so a very good digital agent ought to know its personal limitations, and rapidly switch the caller to a human agent when wanted.
On this publish, we share how the Kentucky Transportation Cupboard’s (KYTC) Division of Automobile Rules (DVR) lowered name maintain time and improved buyer expertise with self-service digital brokers utilizing Amazon Connect and Amazon Lex.
KYTC DVR’s challenges
The KYTC DVR helps, assists and offers info associated to automobile registration, driver licenses, and business automobile credentials to almost 5 million constituents.
“In a current survey carried out with Kentucky residents, greater than 50% really wished assist with out talking to somebody,” says Drew Clark, Enterprise Analyst and Undertaking Supervisor at KYTC.
There have been a number of challenges the KYTC staff confronted that made it obligatory for them to interchange the prevailing system with Amazon Join and Amazon Lex. The dearth of flexibility within the current customer support system prevented them from offering their prospects the most effective consumer expertise and from innovating additional by introducing options like the power to deal with redundant queries through chat. Additionally, the introduction of federal REAL ID necessities in 2019 resulted in elevated name volumes from drivers with questions. Name volumes elevated additional in 2020 when the COVID-19 pandemic struck and driver licensing regional places of work closed. Callers skilled a median deal with time of 5 minutes or longer—an undesirable scenario for each the callers and the DVR contact heart professionals. As well as, there was an over-reliance on the callback characteristic, leading to a under par buyer expertise.
Answer overview
To deal with these challenges, the KYTC staff reviewed a number of contact heart options and collaborated with the AWS ProServe staff to implement a cloud-based contact heart and a digital agent named Max. At the moment, prospects can work together with the contact heart through voice and chat channels. The contact heart is powered by Amazon Join, and Max, the digital agent, is powered by Amazon Lex and the AWS QnABot solution.
Amazon Join directs some incoming calls to the digital agent (Max) by figuring out the caller quantity. Max makes use of pure language processing (NLP) to seek out the most effective reply to a caller’s query from the DVR’s information base of questions and solutions, and responds to the caller utilizing a pure and human-like synthesized voice (powered by Amazon Polly), supplemented when acceptable with an SMS textual content message containing hyperlinks to webpages that present related detailed info. With Amazon Lex, the division was in a position to automate duties like offering info on REAL IDs, and renewing driver’s licenses or automobile registrations. If the caller can’t discover the specified reply, the decision is transferred to a dwell agent.
The KYTC DVR studies that with the brand new system, they’ll deal with the identical or larger name volumes at a decrease operational value than the earlier system. The decision dealing with time has been lowered by 33%. They constantly see 90% of the QnABot site visitors routing via the self-service possibility on the web site. The QnABot is now dealing with near 35% of the incoming telephone calls with out the necessity for human intervention, throughout common enterprise hours and after hours as properly! As well as, agent coaching time was lowered to 2 weeks from 4 weeks as a result of Amazon Join’s intuitive design and ease of use. Not solely did DVR enhance the shopper and agent expertise, however additionally they averted excessive up-front prices and lowered their total operational value.
Amazon Lex and the AWS QnABot
Amazon Lex is an AWS service for creating conversational interfaces. You need to use Amazon Lex to construct succesful self-service digital brokers in your contact heart to automate all kinds of caller experiences, corresponding to claims, quotes, funds, purchases, appointments, and extra.
The AWS QnABot is an open-source resolution that makes use of Amazon Lex together with different AWS companies to automate query answering use instances.
QnABot permits you to rapidly deploy a conversational AI digital agent into your contact facilities, web sites, and messaging channels, with no coding expertise required. You configure curated solutions to ceaselessly requested questions utilizing an built-in content material administration system that helps wealthy textual content and wealthy voice responses optimized for every channel. You’ll be able to develop the answer’s information base to incorporate looking out current paperwork and webpage content material utilizing Amazon Kendra. QnABot makes use of Amazon Translate to help consumer interplay in lots of languages.
Built-in consumer suggestions and monitoring present visibility into buyer queries, issues, and sentiment. This allows you to tune and enrich your content material, successfully educating your digital agent so it will get smarter on a regular basis.
Conclusion
The KYTC DVR contact heart has achieved spectacular buyer expertise and cost-efficiency enhancements by deploying an Amazon Join cloud-based contact heart, together with a digital agent constructed with Amazon Lex and the open-source AWS QnABot resolution.
Curious to see should you can profit from the identical approaches that labored for the KYTC DVR? Try these quick demo movies:
Strive Amazon Lex or the QnABot for your self in your individual AWS account. You’ll be able to comply with the steps within the implementation information for automated deployment, or discover the AWS QnABot workshop.
We’d love to listen to from you. Tell us what you suppose within the feedback part.
In regards to the Authors
Tony Momenpour is a programs advisor inside the Kentucky Transportation Cupboard. He has labored for the Commonwealth of Kentucky for 19 years in varied roles. His focus is to help the Commonwealth with having the ability to present its residents a fantastic customer support expertise.
Drew Clark is a enterprise analyst/mission supervisor for the Kentucky Transportation Cupboard’s Workplace of Info Expertise. He’s specializing in system structure, software platforms, and modernization for the cupboard. He has been with the Transportation Cupboard since 2016 working in varied IT roles.
Rajiv Sharma is a Area Lead – Contact Middle within the AWS Knowledge and Machine Studying staff. Rajiv works with our prospects to ship engagements utilizing Amazon Join and Amazon Lex.
Thomas Rindfuss is a Sr. Options Architect on the Amazon Lex staff. He invents, develops, prototypes, and evangelizes new technical options and options for Language AI companies that improves the shopper expertise and eases adoption.
Bob Strahan is a Principal Options Architect within the AWS Language AI Providers staff.