With the proliferation of messaging platforms and digital voice assistants has come the rise of conversational AI—better known as bots.
These chatbots, virtual assistants, smart speakers, and communication platforms are powered by machine learning and can be used to build trust between brands and consumers. In fact, by the end of 2020, 25 percent of customer support operations will integrate virtual customer assistants (VCA) or chatbot technology across engagement channels –– up from less than two percent in 2017.
The use of virtual and voice assistants continues to rise, with Google’s Assistant deployed across one billion devices, and Amazon reporting sales of 100 million Alexa-enabled devices in 2019. The use of smart speakers, like Amazon’s Alexa and Google Home, is expected to reach 225 million units in 2020.
Apple’s Siri set the stage for widespread consumer adoption since debuting in 2011. Built on artificial intelligence (AI), voice assistants use automatic speech recognition (ASR) and natural language understanding (NLU) to understand what users ask. Unlike chatbots, conversational AI uses advanced algorithms to train itself from data inputs and subsequently improves at predicting questions.
The commoditization of speech-based assistants like Google Home and Amazon Alexa has paved the way for companies to develop their own speech-based assistants and overlay other conversational systems onto their platforms.
Because customer experience is now the basis of brand differentiation, the area where muchof that experience happens—the contact center—is more important to a business's success than ever before.
Conversational AI is making it possible for companies to better meet customer expectations for omnichannel, personalized, 24/7 service, before, during, and after a purchase, and those improvements translate to better business—in fact, after implementing a virtual customer assistant (VCA), organizations report a reduction of up to 70 percent in call, chat and/or email inquiries and 33 percent savings per voice engagement.
Here are five ways to implement conversational AI into your contact center experience.
- Data collection and entry: Live agents spend an inordinate amount of time gathering information from customers over the phone, but virtual agents can take care of this and without human error. These agents integrate seamlessly with your CRM system or ERP and use Natural Language Understanding to collect any data type—from alphanumeric strings to names and places—in the same way that a live agent does. The solution also should integrate with your contact center platform easily, so if a call needs to be transferred to a live agent, the AI technology can pass along all collected information and reasons for the transfer via a contextual screen-pop.
- Reservation and scheduling services: Certain aspects of scheduling, such as making recommendations for shows in Las Vegas, aren’t ready for automation yet. But you can automate certain call types—making appointments, cancellations, scheduling deliveries, and outbound confirmation—without sacrificing any of the customer experience, and taking nuance into account. For example, if a customer asks, “Do you have anything next Thursday?” AI technology enables automation to know what the customer means and then shares available appointments on the second Thursday from today.
- Order management: For many industries, order placement has moved online. But this broad category also includes low-hanging fruit like order status, returns, reordering and delivery reminders. With integration to the inventory management system, conversational AI voice automation can handle these calls as capably as a live agent. It can manage multi-turn conversations and use advanced speech recognition to capture unique product names and difficult alphanumeric order numbers. Dozens of organizations use virtual agents for reorder calls—inbound and outbound. For inbound, the virtual agent checks the customer record and proactively asks, “Are you calling to reorder your medical supplies?” Outbound typically is treated as a reminder, such as, “Our records show you may be running low on your medical supply, would you like to reorder?”
- Billing: Most billing processes, which generally follow the same routine and expected procedure, should be fully automated. Even more complex situations, like payment plans, have well-defined rules. PCI-compliant automation outperforms live agents in billing processes because AI doesn’t make mistakes or exceptions. The best example of AI-powered virtual agents for billing is an outbound collections call. When coupled with letters and email, automated outbound calls can help a third-party health care agency collect up to three times more money.
- Accounts and memberships: Account and membership maintenance is an important aspect of being a loyal customer. Address updates, new accounts, rewards programs, and password reset requests are just some of the call types that fall under this category. Virtual agents can read from and write to customer records, ensuring that customers don’t need to speak to agents for rudimentary requests associated with their account and membership. If a “save the member” situation comes up, the AI automation escalates to a live agent along with a screen-pop of customer info.
Consumers today expect their interactions with conversational AI to be on par with communicating with another person. Providing a seamless AI experience, at specific, high-value interactions bolsters consumer trust and supports business goals. The growth of conversational AI is just one of five trends covered in our State of Customer Engagement report. Want to explore them all and learn how they will evolve in 2020? Download your copy of the report now.