It's time to rethink conversational AI

Intent-level intelligence

[caption id="attachment_56984" align="aligncenter" width="812"] Source: ALITICAL research. n= 10,000 intents mapped out for a tier-1 bank[/caption]

It's clear that only once you connect the silos can you deliver seamless customer journeys. But there's an even more important step, one that requires more than just technology investments.

2. Define the single best way for contact resolution

The tech-vendor-led rhetoric of "meet the customer in their channel of choice" is well-intentioned but misguided. You see, meeting the customer on Twitter, within the Facebook comments section or even on Live Chat offers zero benefits if the customer is forced to phone for resolution. This is pushing the burden of resolution back to the customer. And it's a serious and significant failing, often euphemistically termed 'channel shift'. As we saw previously, ineffective contact strategy design led to 35.5% of detractors being unable to have their intent resolved via Live Chat.

The pivotal change we see here is that some enterprise firms are scrapping the old mantra and determining where the customer should have that intent resolved. They are pulling together cross-functional teams to figure out what is the single best, optimal way to resolve each specific customer intent. It's not the technology. It's the application of the technology that matters. Of course, meet the customer in their channel of choice; but resolve it in your place of preference. Or perhaps, the mindset shift required here is to meet the customer in their channel of choice and triage /route to the single best place for resolution.

...meet the customer in their channel of choice and triage to the single best place for resolution.

Experiencing a breakdown on a highway or interstate can be a traumatic experience. In this situation, customers need certainty. They require precise timescales and continual reassurance that the recovery is on track. As you may imagine, this leads to multiple repeat contact within the call centre from distressed customers. As a cross-functional team, the CX leadership, operations and digital teams at an Emergency Roadside Services Provider decided that there had to be a better way; both in delivering a better experience and reducing impact on the contact center.

They replaced the legacy IVR system with an interactive voice assistant and the entire conversation is automated with conversational voice AI.

Customers then receive a SMS to pinpoint and confirm their location using GPS intelligence. Via an Uber-style app, the customer can track the progress of the recovery truck. Subsequent follow-up is via SMS, keeping the customer informed of progress. Most customers phone when they breakdown, but some do send a message. A select few even use FB messenger. But, irrespective of what channel the customer request originated from, the resolution is the same.

[caption id="attachment_56985" align="aligncenter" width="320"] Source: Andrew Moorhouse[/caption]

Irrespective of what channel the customer request originated from, the resolution is the same.

Within the first month, call containment (resolution without a human agent) achieved 48% and is now at 70% one-year following implementation. What's essential to note, the breakdown assistance provider did not attempt to automate all intents. They chose one use case and executed it brilliantly.

The key message is that not one size fits all. Each intent requires a different solution. The most important point to glean is that irrespective of where the intent started; resolution occurs in one single defined place. Some other examples that we've seen:

[caption id="attachment_56986" align="aligncenter" width="996"] Source: Andrew Moorhouse[/caption]

Understanding the intent and then routing it to the best place for resolution is the fundamental activity here. During the intent clustering activity, there will be clusters that the intent classification tool didn't understand. The approach is to get very granular and disambiguate what customers want. These may be termed 'edge cases'.

In this instance, it's vital for the cross-functional team to decide with these topics where to send the call. Deflecting initial voice traffic to pre-existing self-serve menus can deliver results quickly, often within month one. The final element required to transform performance on containment is the application of intent-level orchestration.

3. Apply intent-level triage and routing

Once the intent resolution rules above are determined, then this is where the 'intent-level orchestration layer' comes in. Its sole purpose is to drive the intent to the single best place for resolution. It's worth explicitly stating this is not customer journey orchestration; it's quite different:

[caption id="attachment_56987" align="aligncenter" width="834"] Source: Andrew Moorhouse[/caption]

The current contact centre model is to stack customers up in a call queue. Perhaps the necessary agent skill has been identified, but today, there is no prioritisation given to any customers based on their call intent.

Imagine you are involved in a traumatic accident. You broke your femur and shattered your pelvis in a motorcycle crash. However, Clive, who visits the hospital A&E weekly, has stubbed his toe and currently sits in the queue in front of you. This is how almost all contact centres operate today, and it's ridiculous (sorry, Clive). Curiously, many UK hospitals are lambasted for the fact that 24% of patients leave A&E without ever seeing a doctor. I think that's a phenomenal achievement and shows that the 4- or 5-stage triage principles are being applied and working.

Triage is the most under-discussed element of contact centre strategy; because, until now, it has been incredibly difficult to understand the minutiae of customer intents across all voice and text channels to take decisive and determined automation decisions. Here's a great example of Triage in action today:

[caption id="attachment_56988" align="aligncenter" width="845"] Source: Sentisum[/caption]

Triage is the most under-discussed element of contact center strategy.

Intent-level orchestration (triage) tools are emerging that plug into existing CCaaS platforms, vastly improving performance. The evolution of intelligent triage allows leaders to intelligently prioritise support based on urgency, risk and customer effort and reduce response time to important conversations. The new breed of intelligent AI triage works as a contact orchestration tool across voice, email, chat, and all available channels.

One global insurance company achieved a 17% reduction in inbound volume from a base of 120 million phone calls. But it took a methodical and data-driven approach. Across 12 different countries, they started with intent identification within its IVR to determine the possibility for end-to-end voice AI resolution.

The company initially collected intent data from the conversational IVR from 18 million customers and simply then routed the customer to the main agent queue. Only once they had this depth of insight did they run the intent clustering and identify what intents could be resolved by "one shot" self-service. That is, what basic intents could be resolved by looking up a simple database or API lookup request.

One specific use case is handling customers that repeatedly call in to check if their funds have been processed. If the customer already called one hour previously to check the payment status, just via the phone number identification, the insurance company now routes the customer to a payment status portal, showing them the required details. But this was not the starting point. Their advice is not to start with automation but to collect the data. And focus on the one-shot use cases coupled with deflection to pre-existing self-serve journeys.

The amount of unstructured data within voice and text is so vast and so valuable, yet few organisations are using it today to drive call containment efforts. The following image depicts a fictitious, authenticated banking live-chat session. This is the future evolution of conversational AI. To achieve this, you need the right intent-level intelligence coupled with the best available AI triage and intent-level orchestration. Advising on ISA (401k) consolidation is a messy affair. Chatbot resolution rates are zero, and curiously, human live-chat resolution is less than 10%. Now armed with the right data, the intelligent triage system understands that resolution rates for ISA consolidation conversations are extremely poor, even via live chat. So, a trained ISA specialist is offered for the conversation via a co-browsing session.

[caption id="attachment_56989" align="aligncenter" width="406"] Source: Andrew Moorhouse[/caption]

*An ISA (individual savings account) is a UK individual tax-free savings account. The Canadian equivalent is a Tax-Free Savings Account (TFSA) and in the USA, the closest is a Roth 401K.

Recommendations

Brand new AI technologies and contact strategy approaches are emerging that bolster existing installations. To ensure initiatives succeed, leaders should:

Unify the customer contact taxonomy across voice, live chat, bots and socials using a new breed of AI-driven Intent classification tool. Only once you connect the silos can you deliver seamless customer journeys.

Define the single best way for intent resolution. This needs to be done as a cross-functional team. Irrespective of the starting point, leading organisations are shifting to a new mindset: "What is the single best way to have this interaction?"

Apply AI-powered intent-level conversation orchestration to drive the intent to the single best place for resolution. This is not mere journey orchestration but a new approach using Intelligent AI Triage to deliver on automation /deflection /self-serve decisions.

In summary

We are about to witness the rise and subsequent failure of conversational Voice AI over the next 3 to 5 years. It's not an AI - artificial intelligence problem. It's a human intelligence issue.

Intent-level orchestration is the most significant missing strategy piece. Contact orchestration isn't owned by voice; digital; CX leaders; the contact centre operation; social media teams, or marketing. Today's stakeholders have zero bandwidth or time for the right cross-functional strategy decisions on what intent should be resolved. The narrative about "meeting customers in their channel of choice" is a horrific idea for intent resolution propagated by legacy tech vendors selling omnichannel consolidation platforms. Customers should be triaged in their channel of choice, and their intent routed to the single best place for resolution.

Customers should be triaged in their channel of choice, and their intent routed to the single best place for resolution.

The biggest risk is charging ahead on Voice AI without defining the correct intent-level orchestration. Without effective triage, prioritisation and deflection rules defined at the intent level, any Voice AI attempts will fail. The intelligent orchestration layer needs to sit across all digital, voice and self-serve options.

Before companies can effectively implement Voice AI as a channel, they must unify their customer contact taxonomy, align all silos and define the single best place for that intent to be resolved.

The most advanced enterprise firms will apply AI triage and intent-level orchestration to revolutionise their call containment and digital deflection performance. The technology exists; the challenge is the bandwidth, in-house capabilities and desire to make this happen. Understanding the nuances of resolution and satisfaction at the intent level is critical for future self-serve and automation roadmaps.

The evolution of intent-level conversation intelligence and triage tools offers unrivalled opportunities for leaders to fuel action and drive improvements. Rather than usurping existing providers with new vendors, leaders should augment and bolster existing investments. Tuning and honing the existing platform performance.

Leaders must objectively discuss all customer intents and consider, "What conversations do we want to have, with which customers, when, and in what channel? What's the optimal, single best channel for resolution?" Your automation strategy isn't a post-it note exercise. In a data-driven enterprise, it's time to trust the data.