Reflections on the Rise of AI in Customer Experience
Regardless of whether you’re a Millennial that’s grown up acclimated to Siri ordering your Starbucks for you, or if you’re like me and grew up with some (healthy) suspicion of Skynet, the reality is that AI is busting into the customer experience scene.
What’s more, it is also likely doing so with potentially major impacts on your operations.
Take for example, when Tom (from a Brightmetrics favorite show: Parks and Rec) brings in his DJ Roomba to the workplace.
Of course, he describes DJ Roomba as a mobile robot that plays the hottest tracks when in reality its an iPod played attached to the top of an autonomous vacuum. 😂 Regardless, there’s definitely something to be said about the idea of intelligent machines making their way to our everyday lives.
Bots, AI assistants, predictive routing algorithms: the machine learning enabled movement is swelling.
It’s clear that this becomes even more important as we assess the next generation strategies and investments for how we approach our organizations’ most important engagements across all channels.
Recently, Brightmetrics has been on a journey assessing the customer engagement landscape. In this way, we’ve started determining where we’ll be capable of adding value through our service. As part of getting to know the industry’s leaders more closely, we recently had the pleasure of attending the Genesys G-Summit in San Francisco. It was exciting to hear more about their current customer experience platforms and where they’ve been investing in their technology development talent.
Genesys’s vision of fluid conversation over myriads of channels, on the customer’s preferred cadence, at the highest convenience for the customer is on tone with the expectations of today’s consumers. Machine learning has enabled much of their latest offerings and capabilities to deliver this. You can check out more about what they discussed and have cooking here!
Over the years, I’ve gotten a little carried away with the thoughts of this technology applied to the next-generation platform. I’ve often thought about all the potential around recommender algorithms being applied to interactions (I know I know, nerd 🚨). But the reality is that these solutions are already hitting the streets. This is both exciting and a little bit daunting at the same time.
This brought me to a curious place…
- How many Brightmetrics customers and partners are leaning into this movement?
- How many of them see this as just another “phase-y” technology play that is irrelevant to their business model?
- Do a lot of customers and partners feel like this is still extremely nascent?
- Would customers want to see the technologies mature before deciding how it could change their operations?
What kind of reporting and analytics will become necessary in this “mixed” environment? Do we simply just trust the machines are truly creating efficiency and helping deliver more effective outcomes with your agents? That’s certainly not something I’d be comfortable with…
So here are some of the thoughts I’ve had around insights I’d want:
- Routing: Predictive Scores vs Actual Outcomes
- AI Assist Recommendations: Interventions Suggested vs Agent Activity
- Bots: Summary and Detailed Reports around Bot Engagements
- What are customers looking for???
So… I thought I’d ask you IRL. Right here! I’d love to hear your thoughts:
No matter what your operation that delivers customer experience is called, (Customer Engagement, Contact Center, Call Center, Customer Service department, etc) people are still at the core of how it ticks. But as these technologies find their way into operations, it will be interesting to see how people and the AI (machines) that augment them interact to deliver service.
As this all unfolds, Brightmetrics is looking forward to expanding our services to new platforms. We’re excited about evolving our ability to give you insights across all your channels and operational resources (just maybe not the T1000, though).