AI and customer service; it’s a hot topic! But when I talk to customers, they say, “I get there’s something to AI and customer service, but how do I deliver business results and value with AI?” If you are wondering how AI can move the needle on the metrics you get measured on every day, below is a short guide on how to get the best business results when considering AI as part of your Customer Service strategy.
Step 1: Focus AI on Metrics that Matter
Implementing technology without strategy makes us do the wrong things faster! Or at the very least, spend a lot of money without getting business results. Studies show while 80% of executives want to use AI in their business, only 20% have an actual strategy. (1) First step? List the strategic metrics you are measured on every day and then think about how AI can help you to:
- Reduce call volume (call deflection via satisfying self-service)
- Increase First Contact Resolution (FCR)
- Reduce Average Handle Time (AHT)
- Increase agent productivity, morale, retention (reduce attrition costs)
- Improve CSAT, NPS, customer lifetime value (CLV)…
With that information, you can begin to strategically decide how to use AI to transform your customer service operations and KPIs, positively impact customer and agent experiences and directly affect your bottom-line.
Step Two: Closely Compare AI Solutions
Artificial Intelligence isn’t new, so what is? Exponential advances in AI capabilities, as well as, integrated and packaged AI solutions. These new capabilities are allowing AI to become a real business asset, but not all AI solutions are created equal. A classical approach to AI requires specialized teams of:
- Data Scientists (to sample data, build the models, tune them for accuracy)
- App Developers (to build it into the customer service application)
- UX Designers (to make the interface to the AI user-friendly)
These dedicated resources are expensive and difficult to find. And AI development is not the core business focus of a contact center. The result? Wasted time and money and longer time-to-value. When choosing an AI solution, look to see how much work is required on your end to implement a solution. To make AI intelligent, all systems require some work. The question to consider is how business/user-friendly is the application? Do you need to hire a team of AI and UX specialists to get benefits in customer service? Or can you deploy the AI quickly and get back to focusing your efforts on delivering amazing agent/customer engagement?
Step 3: Consider an Integrated Solution
Data. Data. Data. AI is all about the data. So, consider where the data in customer service resides. The customer record data lives inside the CRM platform. And the customer interaction history lives inside the customer service application. Since AI is only as good as the data it interacts with, look for an “AI-inside” solution; one where the AI is built into the CRM platform and the customer service application.
And it’s even better if the same AI solution is also integrated into other applications that Sales, Marketing, E-commerce and other parts of your business. The more contextual, historical information about that customer across all your departments, the more intelligent the AI is and the better business results it can provide. With an integrated AI solution that’s built for business users, there is no need for specialized implementation teams because the:
- Data is already prepped
- Models are automatically built and
- AI is already integrated into the CRM platform and the customer service application.
What does this mean to you? Faster time-to-value. With an integrated solution, AI can easily learn from the customer data to deliver contextual customer/agent answers. So, whether you are delivering self-service or agent-assisted service, intelligent AI service is satisfying service.
Step 4: Select an Agile Solution
How many times have you wanted to change something in your customer service application, but don’t because it’s so difficult — even though it would transform the agent/customer experience? This is where using an agile platform and application leads to faster, better business results.
As you are considering adding AI, ask yourself, “How quickly/easy is it to make changes to the AI solution, as well as to the agent and self-service application?” Look for a drag and drop integration layer that allows for easy configuration of process flows to set up customer service AI. This way AI isn’t some futuristic “ideal” that sounds good when you say it fast but in reality, it takes forever to drive business results. Consider choosing an integrated AI customer service platform/application that is agile – so you can make changes on the fly to quickly deliver on the brand promise of great customer experiences.
Step 5: Use a Solution with a Pre-built UI/UX
And while this step is listed last, it may be one of the most important. Why? New technology often becomes “shelfware,” i.e., technology that is owned or licensed but not utilized because it’s difficult to implement, use or change.
A solution with a prebuilt UI/UX interface makes the customer-facing interaction intuitive, which builds trust, so customers use it. The last thing you want is a throwback to “bots of yesteryear” that didn’t have the advantage of AI or a poor user-interface. If customers can get their answers using a bot, call and email volume will be reduced, while delivering a great experience.
And for the agent? Key to great service is empowering agents with the best possible tools. AI integrated into the agent desktop and console classifies cases and identifies key information needed to serve the customer even before the agent gets the case. And then enables the agent with the best possible next actions. AI is not meant to replace agents, it’s meant to empower them to deliver exceptional customer service.
The most important thing to take away? When considering AI for customer service, focus on what you do best, delivering great experiences. Avoid choosing systems that require you to become or hire a bunch of rocket scientists. Choose a solution designed to allow customers to easily get the answers they need on their own, your agents to intelligently engage with customers and for you to deliver business results that matter.
Is Your Business Ready for Artificial Intelligence? MIT Sloan and BCG Study, 2017