Why wait? JetBlue’s blueprint for leading AI-driven CX transformation
What if the biggest obstacle to improving customer service isn’t technology, but the fear of jumping in before you're fully ready? In this final installment of our three-part series on JetBlue’s approach to generative AI in its contact center, Shelly Griessel, VP of Customer Support, shares her team's forward-thinking strategy for customer support and explores the realities of deploying ASAPP’s GenerativeAgent (JetBlue’s Amelia 2.0). Her message is clear: don’t wait for the perfect conditions to start — the time to act is now, or risk falling behind, especially from a cost perspective.
You can also watch the full discussion. [link to full Wistia video].
Read Part 1, JetBlue’s CX journey: tackling challenges in an evolving industry.
Read Part 2, How JetBlue aligns costs, culture, and AI for CX success.
* Minor edits have been made to the transcript for clarity and readability.
Embracing generative AI to boost resolution and satisfaction
Dan: The way ASAPP thinks about it is that we're trying to build is something that helps improve the performance of agents, but also candidly to reduce the number of agents or labor hours or tier one interactions, whatever term you're using.
When you and I were speaking, you put it into a similar construct. And when you're thinking about AI, you're thinking about tech. You're looking at how I can improve and accelerate the performance of my crew members (JetBlue’s contact center agents), and how to reduce the pizza pie, so to speak, of the number of agents.
So take us through that. Because you are partnered with ASAPP, you’re using us for digital, for chat essentially, and live agent interactions all through digital. And then you've just recently deployed GenerativeAgent, or Amelia.
Take us through that journey of how you're improving the performance of an agent or accelerating the performance. And then you've introduced GenerativeAgent, or Amelia 2.0 recently.
Shelly: So the plan has been all along that we have to make the pizza pie smaller because that's how you bring costs down. We have to bring volume down. You have one shot at getting it right because if you don't get it right, then the customer will call back again and again. I mean, I don't know about your industries, but when a customer is not happy in an airline situation, they will call you back six, seven, eight, nine, ten times.
And that wastes money. So, the idea has always been that first contact resolution is a big deal for us, followed by CSAT.
I will never say we don't care about handle time, but we manage handle time as a separate entity altogether. If we are able to just shrink the pie by making the crew members more effective, we can push more of the really simple stuff to Amelia, and she will deal with it. I think now that we've got generative AI going, we really want to accelerate what she's able to do, and to have more of the bigger conversations with customers.
Understanding customer intents to optimize support
Shelly: I don't believe that Amelia should have the personality of being super empathetic because everybody knows she's a bot. So you have to be very careful that it still remains authentic, and she's not gonna ever be super authentic.
I think that the customer wants to get the job done as fast as possible, and get the right resolution that they're looking for. So we have to just keep on looking at understanding why customers are contacting us, and ASAPP has done an amazing job for us to explain the intent of our customers.
Once you understand that better, you can actually start looking at your product and say we need to make changes in the product. Why do they keep on calling about baggage? They don't like the baggage policy? Or checking in? They don't like that policy?
ASAPP has helped us a lot to understand the intents of why customers are contacting us. But that's all technology that is helping us shrink the pie.
Nobody, no company, wants to pay tens of or hundreds of millions for customer support. They don't. They want to invest the money in brand-new aircraft, and so they should.
We have an obligation to get a whole lot smarter about it. So our strategy is very much constantly evaluating our tech stack. Is it what it's what it's still needed? Do we provide them with enough information to be able to do the job? Like guided call flows. And making sure that crew members understand this is how it's going to help you versus anything else.
From proof of concept to progress: Teaching GenerativeAgent
Dan: I was thinking about this as you were speaking. I saw some great research. Shout out to Brian and Brooke from CMP on the research. I saw in a session yesterday around chatbots and voice bots just some dissatisfaction with customers and etcetera.
Everybody's familiar with that. When you dipped your toe into GenerativeAgent, or Amelia 2.0, what were concerns that you had going in? Because chatbots and voice bots promised a lot of the same things that you're hearing from a generative AI agent. And so what we hear a lot of is skepticism because we promised a lot, and it didn't necessarily happen.
So when you approached generative AI, how did you approach that to go, I'm going to see if GenerativeAgent, or Amelia 2.0, can actually work? And then tell us about the journey, trepidation, results, anything that you would wanna share about that.
Shelly: So we started in May when we said, okay, let's do a POC (proof of concept), and let's see how it goes.
And we had a team watching it and course correcting. I think you're familiar with the term hallucination. So she comes up with things that you go, why did you say that, Amelia? That's not true.
And then it's a matter of, okay, let's pull her back. Let's teach her how to do this differently. And I think that we've got enough – so this started in May. At that time, our containment with her was at about 9%. And then by August, she went up to as high as 21%.
And that's amazing in a very, very short period of time, and it's just a proof of concept. So it's very little volume that we're giving her, but I think that we now need to double down on this. I want to fast-track teaching her. I think that this has to come from taking some of our best crew members in the company and watching her and saying, “No, take that option away.” So there are certain things, for instance, that we learned that we don't want her to do.
There’s so much pressure on airlines at the moment to get your refund policies right. So the DOT is all over us. We can't let her make decisions on refunds. So we say, okay. Put that out of scope. What else is a hot topic? Like ADA, hot topic. Wheelchairs, hot topic. You have to keep that stuff out.
And I think that it's just going to take a little bit of time blending humans with teaching her on the areas that she can absolutely start knocking out of the park, and we'll get there. I think it just has to be this relationship made between humans and Amelia to learn.
I think that some of the companies that are getting some good success with it are taking a bot, whatever bot they have, and let the bot learn from a human. So I think that matching what great crewmembers can do with the bot is for us looking like that's going to be the future.
Start now even if you are not ready – or risk being left behind
Dan: A lot of the questions that we hear at ASAPP are, “I'm not ready for a GenerativeAgent experience because I've got knowledge base issues or technical debt” or any of those things.
If you were to give any advice to this audience about a place to start this journey – for people who are wanting to start on this AI journey but aren't ready to, like, deploy some sort of GenerativeAgent, where could they start? How do you evaluate?
Shelly: Your environment is never going to be right and ready. It's never. I mean, come on. For all of us that have been in customer support areas forever, every year we plan all the things that I'm going to do. And before you know, it's the end of the year. And I didn't do 50% of it because why? Because we come in and there's a new drama.
I think that the time is never right. I think that for this, in my mind, you have to jump in because I think if you don't, you're going to be left so far behind, especially from a cost perspective.
I don't think it's just airlines that are under the pressure for forecasts at the moment. We're going through budgets right now, and it's tough. Everybody wants customer support to cost nothing, and please make sure the customer is really happy still.
Don't spend any money, but don't you dare let that NPS go down.
I think we all know that, and that's why I say you've got to jump in and say, what have you got to lose? If you put the boundaries around it, what have you got to lose? You really don't.
So I don't think that you have the luxury of waiting for everything to be ready and perfect. You have to go, okay, I'm ready now. Now I can do it.
I think you're gonna be left behind if you do.
Read Part 1, JetBlue’s CX journey: tackling challenges in an evolving industry.
Read Part 2, How JetBlue aligns costs, culture, and AI for CX success.