What is Interactive Voice Response (IVR)?

Interactive Voice Response (IVR)

An IVR is an automated telephony-based computer system that gathers information about callers, provides self-service and/or routes calls to the right live agent. Traditionally IVRs have interacted with the callers through touch tone interfaces- (aka Dual Tone Multi-Frequency or DTMF). Today, most IVRs still use DTMF interfaces (i.e. Push 1 for marketing, 2 for sales}, while some have been updated with very basic speech interfaces (“press or say 1”). Service departments that still use basic IVR are now trying to understand how they can embrace the latest advancements in Conversational AI to improve the quality of service they offer to callers through their automated systems.

From IVR to Intelligent Virtual Agent

This new technology is so much better than the traditional IVR, where a customer can feel trapped in a press-key or voice-response matrix. Conversational AI, whether through voice or chatbot, allows the customer to ask her question or present his problem immediately and directly in a natural interaction with the system. Where the AI cannot resolve the query, the matter is escalated.

Already almost half of US households own a smart speaker, which is helping drive acceptance of Conversational AI interactions. Nearly all smartphone users now accept driving directions from GPS-controlled navigation bots. It has already been observed that Millennials will abandon a brand rather than make a telephone call because they loathe the time and effort it takes to navigate an IVR or even deal with a front-line person.10 They have already mastered the art of online ordering and are looking to continue the relationship online if possible.

The latest research shows that 67% of respondents in the US, UK, France and Germany have already used AI or social media to engage for customer service. Eighty-nine percent of consumers say that a quick response was a competitive differentiator when making a buying decision. Less than half will wait an hour for a response, and 10% will wait less than five minutes before moving on. Contrary to conventional wisdom, ninety-eight percent would prefer not to have to interactdirectly with a person.

In addition to the above, quick and always-on Tier 1 support will lower customer abandonment rates and interaction complaints. Moreover, every single customer interaction adds to the predictive power of the supporting models and automatically highlights new and recurring problems.

Even in Tier 1 centers manned by people, background Conversational AI that “listens in” to the call or similar activity and can offer the customer service representative (CSR) options and/or solutions they may have missed, do not know, or are trending unbeknownst in other CSR pods. Background Conversational AI can also automatically evaluate CSR performance (including call sentiment) and suggest alternative service solutions. These services would also apply to Tier 2and Tier 3 scenarios.

As far-fetched as Conversational AI might seem, in fact that technology is already here. IBM Watson and Google’s Contact Center AI both provide robust solution sets for customer self-service and automatic interactions. Numerous cloud providers offer pre-configured templates for TensorFlow, MXNet, Cffe, CNTK, and Torchmachine learning environments.

Richard Dumas