AI can change how businesses interact with customers, offering new opportunities to enhance efficiency, personalize experiences, and increase customer satisfaction ratings. However, implementing AI in customer service requires a well-defined, goals-based development strategy. Many companies are leaping onto the AI bandwagon without considering what they want from the technology and, more importantly, what their customers want.
Get it right, and you strengthen the bonds with your customers. Get it wrong, and you can irreparably break customer trust. If you’re trying to ensure your company gets AI customer service right, here’s a blueprint for setting and implementing a winning strategy.
Step 1: Start with Why
Why do you want to add AI to your customer service programs? The answer should have wide-ranging implications on what you build and deploy.
The best way to start is by identifying need gaps that are hurting your company’s overall customer experience. Many companies invest millions to understand customer needs. Insights from these efforts can identify pain points, areas for improvement, and potential use cases for AI. If you don’t have such data, examine your current customer support workflows, paying close attention to factors like wait times, times to issue resolution, and how often customer problems are fully resolved in the first interaction. AI may not offer solutions to every challenge, but by starting with your company’s most acute needs, you can triage priorities and discover where new approaches can do the most good.
Also, consider what additional goals your company may have for AI initiatives. Most organizations place the greatest premium on satisfied customers who stick with the company for the long haul. Companies with large sales teams also want to increase success rates and average order values by delivering better pre-sales experiences. Of course, many businesses are constantly looking for ways to reduce costs. Relying on people-intensive service channels like contact centers and in-person support at company stores or branches leads to a significant financial burden.
Once you know the current landscape, define your customer support goals in specific and measurable ways. Notice I said customer support goals, not AI goals. AI is not an end but one of many potential means to an end.
Step 2. Identify the Options
Identify the best approach for meeting customer and company needs. In many cases, AI may be able to play a role. However, you should also recognize that non-AI solutions may be more effective in filling some need gaps. For example, a simple digital form might be easier for customers than communicating with a chatbot.
To identify when AI is an appropriate choice for customer service investment, you need to understand the full range of ways AI can be used in customer service. The AI landscape is constantly changing. Some popular AI solutions for customer service include:
- Chatbots and Virtual Assistants: These can be useful to automate routine inquiries, provide 24/7 support, and guide customers through self-service options.
- Process Simplification Tools: Research shows that customers are very interested in AI applications that can eliminate some of the drudgery of seeking customer support. AI-powered tools like biometric login, recommendation engines, and question-and-answer solutions enable customers to speed through manual steps to resolve issues.
- Sentiment Analysis: AI can also be leveraged to analyze vast data sets like customer support verbatims and social media sentiment to surface issues that need additional attention.
- Predictive Analytics: Increasingly, companies use AI-powered data analytics to identify potential churn risks and predict customer behavior. This can help a company focus on at-risk customers before they take their business elsewhere.
- Proactive Support: Related to predictive analytics, proactive support tools spot potential issues and opportunities in customer data and automatically alert individuals to address them. In addition to simply identifying the problem, proactive AI can also deliver simple tools to resolve issues immediately.
Carefully evaluate different technologies and select those that best align with your goals and can address the specific pain points you’ve identified. By understanding the strengths and costs of these AI tools, you can define a plan that focuses on the most important issues and makes progress against them in ways your company can manage.
Phase 3: Map the How and Get it Done
Develop a phased implementation plan for gradual adoption, testing, and optimization. Many start with a pilot project to validate and assess the technology’s impact. Once you’ve proven its value, you can gradually scale AI across your customer service operations.
Multiple vendors can provide solutions for customer service use cases for most AI technologies. Customer service needs are often common across companies, so companies can develop solutions with common capabilities that enable customization to meet specific client needs. Some companies prefer to develop technologies in-house. This is a viable option if you have tech resources adept at AI, but many companies don’t have enough tech talent to allocate to customer experience projects. Do your research before you choose this path.
Any implementation plan should include processes for measurement, optimization, and reporting. You must continuously monitor and measure the performance of your AI initiatives to ensure consumers are embracing them. Track the key metrics demonstrating whether you successfully meet customer and company needs.
About the Author
Chris Filly is Vice President of Marketing for CX automation company Callvu, where he is responsible for all aspects of the company’s go-to-market program globally. He has more than a decade of experience in customer experience, workflow automation, brand development, and enterprise technology development. Before joining Callvu, Chris was a senior brand and marketing executive with Adobe, responsible for Adobe Experience Cloud.
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