THE TECHNOLOGY WITHIN REACH FOR MOST COMPANIES IS NATURAL LANGUAGE PROCESSING...
The effectiveness of these existing IVRs, measured by their containment rate( the percentage of calls resolved without human intervention), varies significantly.
Our research across different companies indicates a range from 35 % to as high as 85 %, with financial institutions and telecommunications providers typically achieving the highest levels of IVR containment.
Several factors influence higher containment rates. These include:
• Streamlined, simple, and intuitive processes.
• The demographic makeup, technical proficiency, and comfort of the customer base.
• The volume of simple, straightforward inquiries as a percentage of total inquiries.
• The success of initiatives designed to encourage customers to migrate to digital channels.
To drive higher containment, some companies have installed deep links within the IVR system. This encourages containment within an IVR while simultaneously offering customers a convenient and quick way to obtain information without waiting for a human agent.
In this scenario, customers are given an option to receive secure and encrypted SMS links that takes them to the relevant information online. This approach allows customers to receive faster access to the information they need, and the company subtly encourages the shift towards digital channels.
On the flip side, some organizations send customers to agents immediately after understanding intent as part of their CX strategy as they wish to offer a“ white glove” service experience.
Interestingly, organizations that have already achieved high IVR containment( above 70 %) are cautious to drive higher containment.
There ' s a recognized risk that aggressively pushing for even greater self-service containment could negatively impact the overall CX, highlighting the delicate balance between operational efficiency and customer satisfaction. This is true for all channels.
THE TECHNOLOGY WITHIN REACH FOR MOST COMPANIES IS NATURAL LANGUAGE PROCESSING...
The Future of IVR
So, what ' s the next wave of innovation for the IVR? The technology within reach for most companies is natural language processing( NLP), the core technology driving conversational AI.
Virtual agents( voice bots) are powered by conversational AI. These bots can understand, interpret, and generate human-like responses, significantly improving the CX. This is a huge improvement as it eliminates customer frustration caused by most traditional DTMF(" Press 1 for X ") IVRs.
While some pioneering organizations have invested in conversational AI, the majority acknowledge that its full implementation and optimization within their IVR systems is a future endeavor, not a current priority.
We also noted that most organizations are interested in biometrics and leveraging virtual agents using conversational AI. The integration of biometrics is gaining significant traction, particularly within the banking sector. The primary driver behind the growing adoption is the potential to alleviate customer frustration and reduce the time spent navigating traditional security and validation processes. In this, customers willingly consent to having their unique voiceprints captured and securely linked to their accounts.
Subsequently, when a customer calls, the virtual agent engages them in natural conversation, seamlessly comparing their live voice against the stored voiceprint.
OMNICHANNEL
Upon a successful match, access is granted, bypassing cumbersome security questions and PIN entries. Furthermore, biometric technology incorporates AI-powered recognition to detect and flag potential voice clones used by fraudsters.
Ushering in Proactive and Personalized Interactions
Conversational AI unlocks a range of possibilities for developing advanced self-service capabilities that were simply unattainable with the limitations of older DTMF technology.
Often serving as a crucial first step in a broader organizational AI strategy, companies are proactive in understanding customer intent. A personalized CX is delivered by intelligently analyzing historical customer data and behavioral patterns.
Consider this example: once a customer is identified and authenticated, AI recognizes established patterns. For instance, if the customer history reveals a recurring tendency to call for bill payment around the same time each month, it can proactively address this need with a tailored greeting:
"[ Customer Name ], thank you for reaching out to us. We see that your bill is due on [ Date ]. Would you like to make a payment today, review your current balance, or hear a summary of your recent charges? Please let me know what you would prefer."
The ability to handle complex requests and proactively offer timely assistance based on past interactions or current events represents another significant leap forward.
Conversational AI enables a new level of personalization. By analyzing a customer ' s past purchase history, browsing activity, or explicitly stated interests, the IVR can offer highly relevant product or service recommendations during the interaction.
Imagine leveraging this technology to recognize a recent customer purchase, such as a premium mobile phone. The virtual agent engages with a relevant and timely offering:
" Thank you, [ insert name ], for your recent purchase of our premium phone. We are delighted to share that our new noise-canceling headphones are now on sale. Tell me if you’ re interested, and I’ ll tell you all about them."
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