Now that customers engage directly with your company on more and more channels, the position of customer service has elevated from "cost center" to marketing tool, competitive differentiator, and linchpin in the quest for exceptional customer experience.
It's no wonder customer service is one of the top priorities for business leaders across the globe. But how do you scale an exceptional experience for today's hyperconnected customer?
That’s where artificial intelligence (AI) can help. According to our “State of Service” report, most service leaders (56%) are exploring ways to use AI, but still, only 24% are actually using it today.
Much of the hesitation lies in understanding which problems AI is best-suited to solve. The best way to build this understanding is to think about how AI can impact your three biggest stakeholders:
Let’s break down what AI can do for each one.
1. The Customer: Use AI-powered chatbots to support common requests
To effectively engage your customers and solve their most common requests, it’s important to think about where they already look for help. Do they search your website? Fill out a support form? Or prefer to text or chat?
AI-powered chatbots are a form of artificial intelligence that can be embedded into websites and channels to instantly streamline the service experience. Beyond answering common questions, AI-powered chatbots can greet your customers, serve up knowledge articles, guide them through common business processes, and triage more complex questions.
However, when you entrust part of the customer service experience to automation, it’s important to approach it thoughtfully. Here are two common pitfalls to watch for:
Don’t try to solve too many things at once
Start with a small set of questions so you can iterate quickly and expand how you engage customers over time — for example, password resets, order status updates, and routine questions like store locations and hours. Here’s our own research on common customer questions by industry to help you get started.
Engage the right internal stakeholders
Customer experience benefits from consistency across marketing, commerce, and service. To deploy chatbots successfully, tech teams need to align with brand and content teams to design the bot experience — down to specific language — to ensure it aligns with larger brand objectives. For a great example, check out adidas and their Adibot.
2. The Agent: Empower teams with AI-driven predictions
AI supports agents to take on more complex questions that require a human touch. To get started, conduct an audit of where your agents spend time on manual tasks. Do they have to read emails or complete fields to determine where a case should be routed? Do they spend a lot of time searching for knowledge articles or copying and pasting between systems?
Here again, AI can go to work. It learns from data you already have to apply information from past cases to current ones in order to help a service agent:
Triage cases and route to the appropriate agent
Quickly search knowledge articles for the most relevant information
Integrate insights from other departments into a smart decision engine
Suggest the best next action (e.g. cross-sell, up-sell, or troubleshoot)
In these ways, AI allows agents to eliminate repetitive, time-consuming work and focus on situations that require creative problem solving, social intelligence, and complex critical thinking — activities that will move the needle on overall customer experience.
3. The Manager: Give them the right tools to take action
AI allows service managers to identify KPIs, predict outcomes, and accurately measure the success of their team. For example, using AI to automate data discovery can help uncover insights that managers can take action on, such as:
Reducing customer churn rates
Prioritizing caseloads with a high probability of escalation
Predicting future trends in key metrics
Managers can also use analytics dashboards to learn how AI is impacting customer and agent experiences. These dashboards offer insight into opportunities to improve AI performance, expand use cases, and increase human touch. Examples include:
Tracking conversations handled by bots, agents, or both
Surfacing drop-off rates
Measuring Customer Satisfaction (CSAT)
Evaluating agent-driven revenue
The great thing about AI is this analysis happens in real-time, making it easier to make adjustments and optimize. It also makes space for managers to train agents on the soft skills they need to handle more complex service issues — like active listening and how to de-escalate tough conversations. This alone can reduce agent turnover and improve overall customer experience. We created a free set of learning modules for managers to take advantage of on Trailhead.
Harnessing AI for the customer, agent, and service manager
By streamlining the resolution of routine issues for customers, automating repetitive tasks for agents, and enabling managers to measure and optimize, both human agents and AI can come together to create an outstanding customer experience.
To get started on your AI journey for customer service, check out this free learning module on Trailhead and read this recent report on how to get started with bots for service. To learn about how to empower your teams with the skills they need to focus on the human side of service, find a Trailblazers for the Future workshop near you.