How To Incorporate Conversational AI To Improve Customer Experiences
Head of AI innovation initiatives at ABBYY. I write about AI, innovation and how global enterprises can achieve a competitive advantage.
A friend of mine had an accident last year when their vintage car rolled and severely damaged the roof. Fortunately, the vehicle was insured by a classic car insurer marketed to enthusiasts. It was interesting to hear the concierge-like service they received. They initiated the claim online and got a callback, or rather several calls, from the adjustor, and follow-up emails on every step of the process. There was never a question on their claim status, and the auto body shop received payment for its work within weeks. It was a very human-centric customer satisfaction-focused process.
By contrast, a business colleague had the unfortunate need to file an accident claim with their father’s life insurance company. They were surprised to learn that despite filing the claim online, most communications still went through the United States Postal Service, and they were required to send medical records in the form of a hard copy (over 400 pages) through the mail, despite the hospital making the records available digitally. Nearly six months later, they are still not sure if additional documentation will be requested or if the claim will be paid.
This stark contrast in customer experiences became evident for millions of us over the past year, as organizations across all industries struggled to maintain business operations while volumes increased. Think back to your own recent experience with your insurance agency, telecommunications provider to increase internet bandwidth, or healthcare provider to schedule an appointment or get the Covid-19 vaccine, you may recall the varying levels of automation and service.
Simple Automation Is Not Enough
Most organizations have automated phone systems and offer multichannel options, including mobile apps, to improve operational efficiency. However, customer-facing processes rarely meet our expectations, as these systems were created inside-out. In fact, they can be frustrating — the dreaded phone tree, for example, or the mobile app where all you can do is check the status but not conduct new transactions.
Fifty-nine percent of customers care more about customer experience post-Covid than they did before (38%) when deciding where to buy goods and services. In 2019, Gartner suggested 91% of organizations planned to deploy artificial intelligence (AI) within the next three years to enhance customer experiences and meet increasing expectations. However, to be successful, such systems need to be implemented from the outside-in, to act in a way that is logical from the customer’s perspective.
Intelligent Automation Requires AI
Virtual agents or chatbots are a growing AI tool connecting to intelligent automation platforms to drive conversational-driven experiences. But if we’re honest, they have not been very intelligent and have been limited to basic question-and-answer engagements.
Conversation-driven experiences will transform how people interact with companies. But they must do more than simply direct you to a live agent. In fact, 63% of customers would prefer messaging with an online chatbot (Mindshare), while 33% of companies that use virtual agents report an increase in customer satisfaction, plus save 33% per voice engagement (Gartner).
When you pull back the layers of how to incorporate conversational AI into your organization, five factors are necessary:
1. Content transformation: Information needs to be discovered and mined by conversational AI platforms and internet of things (IoT) devices. This requires organizations to transform unstructured and structured data with intelligent document processing platforms that are integrated and repurposed across multiple automation platforms and business applications. The rise in no-code/low-code platforms makes it easy to transform and share content across the enterprise – whether in a back-office repository or consumer-facing virtual assistant.
2. Advanced RPA: Basic robotic process automation as we’ve come to know for automating simple, manual tasks are becoming extinct. More sophisticated RPA is needed to perform more comprehensive operations that converge content and process awareness. This mandates bots having cognitive capabilities such as understanding, reasoning and decisioning to enable them to learn and improve over time without human intervention. More B2B marketplaces are popping up where such digital intelligence skills are easily accessible and deployable.
3. Operational awareness: Conversational-driven experiences rely on the convergence of multiple automation platforms and systems. RPA and low-code tools make this convergence happen but require process mining tools to streamline operations, identify best practices and deploy them across the company. Organizations leverage it to break down silos and gain an aggregated view and full transparency into end-to-end processes. This level of operational awareness should include robots, chatbots, virtual assistants and business intelligence dashboards for cognitive insight into ongoing business operations. It’s important, therefore, to ensure they are all performing and interacting with each other efficiently by observing workflows, flagging bottlenecks and anticipating deviations from consumer-facing processes.
4. Edge computing: Research firm IDC estimates that by 2023, over 50% of new IT infrastructure will be deployed at the edge. With the power of 5G networks and smart devices, the edge is able to process and execute AI and machine vision capabilities at lightning speed. This empowers consumers to have more control of self-service transactions with their service providers, such as submitting claims with their auto insurance provider instantly. Claimants could use their smartphones to take photos or videos of all relevant information, such as driver’s licenses, insurance information, incident reports and damage to a vehicle. The app or virtual assistant would “converse” with the consumer until the entire process is completed.
5. Hybrid approach: Despite promises by software vendors, the holy grail to delivering a comprehensive AI-enabled conversation-driven experience is not available in one platform. Like any new digital transformation initiative, using best-of-breed solutions rather than a single platform is a smart strategy.
Conversational AI leverages the latest technologies, but it requires situational awareness and an overall understanding of what’s going on from a people, process and content standpoint to truly improve the customer experience.
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