“Please don’t let this be another boring, hype-filled talk track on AI and Machine Learning,” I thought to myself as I stepped into the Renaissance Atlanta for the Execs In The Know’s AI Briefing. While eager to connect with several forward thinking customer experience leaders at brands like Porsche and FedEx, I was wary of the fact that AI talks tend to devolve into hype and platitudes. I wanted actionable ideas I could bring back to the Guru team -- and what I got was that and more.
Coffee in hand, my anxiety quickly evaporated as I sat down and chatted with a few folks at my table. Leading brand executives candidly shared their vision for demystifying AI's potential to support omni-channel CX. Some were just dipping their toe into AI, and other were knee-deep into multiple projects.
Before we knew it, the event kicked off with UPS's Gil Pongetti walking us through their recent implementation of an AI-powered chatbot, followed by a lively, open-format panel discussion featuring industry experts, including Guru's own Steve Mayernick. After round table discussions, the day wrapped up in an Innovation Lab, where brand executives met one-on-one with AI solution providers over cocktails.
The day was filled with concrete stories about real challenges, measurable wins, and ideas for tangible next steps. After furiously jotting down notes and insights throughout the day, here are my 5 key take-aways:
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When it comes to AI support solutions, the classic IBM adage, "garbage in, garbage out" is apropos. For AI to deliver customer experience results - whether as a chatbot, workflow solution, or agent assist - the data it relies on needs to be high quality and reliable. You also need a mechanism by which the AI solution is constantly learning and improving, which requires thoughtful oversight and ongoing tuning.
Customers should expect a consistent experience across your support channels. This best practice was echoed several times throughout the day. With this in mind, any AI solution should improve the customer and/or agent experience while maintaining consistency across your channels. For example, this can translate into the voice and tone used when interacting with customers, the workflow experience for your agents, or the case escalation process.
Don't try to fool your customers and pretend that your new chatbot is a human support agent. Your customers are smart enough to figure it out, and this will just frustrate them and hurt your CSAT scores. Instead, explicitly call out that it's a bot or virtual assistant, and give customers an easy way to reach a live agent or otherwise bypass the bot. UPS shared how every chat interaction starts with their new self-identified virtual assistant, and if a customer is escalated to a live agent, all of the bot interactions are carried over seamlessly, in turn mitigating repeat questions.
There are so many ways you can potentially leverage AI to improve your service operations and customer experience. Do yourself a favor and don't try to boil the ocean. It's important to start small and learn from your early wins and challenges before you invest substantial resources. The best approach is to identify a discrete challenge or area for improvement that AI can potentially address, and start there.
Once you've decided on a specific project, examine your current KPI benchmark metrics for the channel, define success metrics and goals, and evaluate solutions that can best achieve them. This approach works particularly well when you do not have an executive sponsor in the C-Suite, as you can more easily build the business case for AI through a de-risked initial project and expand as you gain buy-in.
Here's an example Guru's Steve Mayernick shared about reducing handle time by 20%:
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Curious to learn more about the AI for support landscape? Check out our recent Elevate Live webinar, "How AI Can Give Your Support Team "White Gloves," Not Pink Slips."