AI for Customer Service

The only guide you’ll ever need

The new era of customer service

AI will be as impactful as the steam engine, according to a recent prediction from McKinsey.

In other words, AI will be big, really big. So big, in fact, that by 2020, customers will manage 85% of the relationship with an enterprise without interacting with a human;  by 2021, more than 50% of enterprises will spend more on bots than traditional mobile; and by 2030, 70 percent of companies will have adopted some form of AI and the majority of enterprises will be using a full range of AI technology.

AI will touch nearly every aspect of a business in one way or another, from operations to advertising, and regulatory to HR. Perhaps one of the biggest AI opportunities for companies lies with customer service. Support remains one of the biggest pain points of doing business, and being a customer, today. Companies lose more than $62 billion due to poor customer service because they can’t meet customer expectations for friendly, convenient and accurate support. With over 1 Billion customer service tickets created every single day, even the businesses with the deepest pockets are struggling to scale high-quality support delivered on consumers terms.

What is AI for Customer Support?

AI helps brands scale high-quality resolutions to high-volume, repeatable issues. For many brands, over 50% of the customer service queries they receive span the same 6-8 issues. AI can be used to respond to these high-cost tickets automatically, freeing up human agents to respond to more complex, unique and new customer issues.

AI for customer service works best when it’s part of a human agent + AI agent team. AI shouldn’t respond to every customer need; there are circumstances that will always better be handled by a human agent for instance in highly emotional situations, those that require a level of subjectivity or highly complex situations. Implementing an AI for customer support will backfire if the customer is frustrated with the inability for an AI to understand and resolve quickly, or completely ignores a person’s feelings. On the other hand, human agents don’t need to be bogged down providing shipping status or answering an FAQ. AI should be used to respond to simple questions, freeing up the human agents to focus on more sensitive, higher-impact tickets.

This “human + AI” dream team, as we like to call it, needs to work in unison to  deliver on a single mission: high-quality, friendly and quick resolutions to customer issues and needs.

What are the most important features for a AI-powered customer service strategy?

The pillars of the ultimate AI for customer support strategy are:

  • Deep Learning:  AIs need to learn from real exchanges, like historic emails and call center logs (in addition to FAQs and other explicitly trained scenarios). This will ensure the AI is able to understand the range of which people ask about a single issue or topic, and how an agent has responded in the past. The proper response can even be determined based on various contextual factors, like a person’s loyalty level or size of wallet, to provide the most appropriate response every time.  
  • Business Connectivity: AIs need to connect with any relevant business system in real-time, like CRM, OMS, inventory management, etc. An AI Agent needs to be able to access the accurate information a customer needs without delay.
  • Authority to Resolve:  AIs need to be able to resolve issues like issuing a return, rebooking a missed flight or upgrading a seat. Companies might set parameters around when a ticket needs to get elevated to a human, perhaps a return above $100 or a request by a Gold Star Member, but AI’s need to have the ability to resolve, not just respond.
  • Empowered Human Agents: When a conversation is elevated to a human agent, the AI must pass along the specific information that will help the agent provide fast, accurate support. This involves both picking out the specific content from the AI and customer exchange, as well as the information from a CRM, OMS or other system relevant to this exact need. This results in better agent performance and can lead to less agent turnover, directly impacting the CSAT.  Furthermore, AI Agents can work within the existing Agent Software Desk currently in use by an organization, eliminating the need for agents to change their workflow or have any additional training.
  • Available on the Channels that Matter: Customers have their preferred methods of getting resolutions – email, social, website, phone. Your AI Agents needs to be available wherever your customers are getting support today.
  • Built on a Foundation of Trust: Customers needs to have trust in an AI Agent. Trust that their needs are understood, that the proper resolution is occurring, that their information is safe, and trust that an AI will always elevate to a human agent if necessary.
  • The Right Personality: AIs for customer service need to offer respectful and friendly resolutions. Period. Brands don’t need to try too hard to create a personality for their AI that’s extremely witty or unique, unless that’s speaks directly to your brand’s existing persona.  

What do consumers want and expect with AI?

There have been countless technologies touted as the next big thing over the years, but as much excitement as there was in the media and amongst consumer experience leaders, consumer adoption never took flight, and sometimes it’s because consumer expectations are too high. With AI, this is not the case. We researched over 1,500 consumers and found that what they want from a company is high-quality resolution and respectful interactions. This is not unrealistic.

For the most part, consumers are very excited about the potential of opportunity and have a lot of vision of what AI can do. It’s not a bright shiny object that holds little real value. Businesses need to prioritize the customer voice in the deployment of AI for customer service, and the entire brand relationship will significantly improve: 

  • Consumers want resolution: Today, 86% of people have to contact customer service multiple times for a single issue. AI takes the next best action: managing autonomously or escalating to a human.  
  • Consumers want a fast response time: Today, the average response time is 12h 10m, and 75% of people expect it within 5 minutes.  AI can automate responses to the repeatable issues instantaneously, and help human agents work faster
  • Consumers want friendly service:  Today, 82% of customer service reps are deemed unfriendly or impolite. AI can establish consistency in the tone and treatment of customers.
Learn more about what consumers want from AI in this post

Adopting AI within the enterprise

As you begin to think about AI-powered customer service for your company, there are a few things to consider:

  • What are the most common channels your customers are reaching out on for support?
  • How much volume are you getting with customer service tickets?
  • Do at least 40% of the tickets span repeatable issues?
  • What will success look like for you? What metrics are you trying to improve?
  • Can your business systems used frequently for support tickets be accessed via APIs?
  • What training data is available (past emails, call center logs, FAQs, etc.)
To learn more about how to evaluate whether your company should adopt AO for customer service, read this post. 

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