The Future of AI Driven Customer Service

Introduction

Hello and welcome to our webinar on "The Future of AI-Driven Customer Service." I'm Allison Ryder, Senior Project Editor here at MIT Sloan Management Review, and I'll be your moderator today. This session is sponsored by Five9. I just want to inform everyone that this event will be recorded. The recording and slides will be available to all attendees approximately three to five business days after the end of the live event.

We welcome your questions for the speaker today, so if you have any, please enter them at any time into the questions module of the GoToWebinar control panel. We will answer as many questions as time permits. If you are experiencing any audio or other difficulties, please also follow the instructions in the questions module.

Our speaker today is PV Kannan, Co-founder and CEO of [24]7.ai. PV, I'll now hand things over to you as I know you have quite a bit of interesting content to share with us today. We will open it up for questions in about 45 minutes, but let's get started.

Introduction

Thank you, Allison. Today, we are going to talk about the virtual agent future. I am sure many of you have visited websites and interacted with bots. Based on surveys by Gartner and Forrester, these interactions usually yield mixed results. Most bot conversations have been disappointing, and today I will discuss where the technology is today, where it is headed, why some bot implementations fail, and what constitutes a great bot experience. Whether you are building a bot or improving an existing one, I hope this session has some key takeaways for you.

Understanding Customer Queries

Why do customers reach out to brands? A good way to classify the types of queries is into two categories: Quick Answers to Questions and Completing a Task. The first category involves frequently asked questions such as "When will I get my order?" or "What is the interest rate on my car?" A virtual agent can shine in these categories because it can provide quick answers.

Completing a task, however, involves multiple turns and complexity. Examples include disputing a charge, making a payment, or applying for a refund. Many current bots fail when they claim to handle these complex queries but actually cannot. Bots today often exist as a standalone channel with no context or understanding of what a customer has already tried.

Customer Expectations

Today's consumers are used to on-demand everything, thanks to services like Uber, Netflix, and Kindle Direct. Customer service, however, has not kept pace, leading to fragmented channels with different capabilities. Customers often end up with incomplete solutions, moving from channel to channel in a fragmented experience. The result is increased costs for companies and customer dissatisfaction.

A Combined Approach

The solution lies in a combination of automated systems and human agents. Simple to medium complexity tasks can be automated, but a seamless transition to human agents must be in place for more complex issues. For example, Dish and American Express have implemented bots that handle FAQs while seamlessly escalating to human agents for complex tasks.

Example of Bad Bot Design

Consider a travel website bot that fails to comprehend simple inquiries and continuously asks for the same information. This kind of implementation disappoints users and reflects poorly on the brand.

Future Trends

The future will be driven by consumer convenience. Bots have the potential to offer seamless, on-demand service, reducing the customer effort required to get resolutions. Technology giants like Amazon, Apple, Google, and Samsung are influencing this space heavily, each driving the adoption of messaging and conversational AI in their ecosystems.

Challenges and Opportunities

As voice search and commands become more prevalent through devices like Alexa and Google Home, customers will expect the same seamless interaction from all brands. This transition requires rethinking call center strategies and channel capabilities.

Best Practices

Effective bot design must include quick escalation to human agents and seamless integration across all consumer touchpoints. Monitoring and iterating on bot interactions can help maintain high standards and adapt to new customer intents, such as those driven by external crises like Covid-19.

Summary

Ultimately, the future of AI in customer service is bright but hinges on both good bot design and effective integration of human agents. Efficiency, customer satisfaction, and maintaining brand integrity are achievable through thoughtful implementation.

Keywords

• AI-Driven Customer Service
• Virtual Agents
• Conversation Design
• On-Demand Services
• Customer Experience
• Messaging Channels
• Human-Agent Interaction
• Natural Language Processing
• Business Continuity

FAQ

Q: Why do AI-powered bots often fail in customer service?

AI-powered bots often fail because they are designed as standalone channels without considering the complete context of customer queries or integrating seamlessly with human agents.

Q: How do bots improve customer service?

Well-designed bots handle simple to medium complexity tasks by offering quick, consistent solutions, and can escalate unresolved issues to human agents efficiently, thus improving overall customer satisfaction.

Q: What is the impact of voice search and commands on customer service?

Voice search and commands are increasingly becoming customer-preferred interaction means. This shift requires brands to rethink call center strategies to integrate voice-based AI effectively.

Q: How can AI bots handle emotional cues in customer interactions?

Although challenging, bots can help agents by providing emotional cues from conversations. This includes recognizing expressions of excitement or frustration which agents can address in real-time.

Q: What metrics are essential for measuring the effectiveness of AI bots in customer service?

Customer effort and the time spent to resolve queries across multiple channels are crucial metrics. Reducing these metrics leads to higher customer satisfaction and lower costs for companies.