Swimming With Sharks: Customer Ops Unplugged - S2 Episode 1: Christina Garnett

In this exciting season opener, Kevin Dean sits down with Christina Garnett, a customer service and marketing expert known for her customer-obsessed approach. Christina shares her unique journey and provides deep insights into the evolving landscape of customer operations, emphasizing the critical balance between AI integration and human touch in delivering exceptional customer experiences.

Episode Summary:

Introduction: Kevin Dean introduces the podcast and welcomes Christina Garnett, highlighting her extensive experience and passion for customer service.

Interview Highlights:

• Biggest Challenges in Customer Ops: Christina discusses the challenges of integrating AI into customer operations while maintaining the human element crucial for building strong customer relationships.
• AI and Human Balance: The conversation explores how businesses can effectively use AI for automation and personalization while preserving human touchpoints for high-emotion interactions.
• Game Theory in Customer Journeys: Christina introduces the concept of game theory and how it can be applied to map out and personalize customer journeys.
• Training AI: Emphasizing the importance of detailed prompts, Christina advises treating AI like the smartest intern and providing clear guidelines to achieve the best outcomes.
• New Skill Sets in Customer Service: Christina talks about the evolving skill sets required in customer service, including the critical role of being an editor for AI-generated content.

Real-life Examples:

• Using AI Tools: Christina mentions tools like Magi for integrating various AI functionalities and highlights the importance of detailed prompts for better AI results.
• Successful AI Implementation: She shares examples of how companies can use AI effectively without losing the personal touch that customers value.

Key Takeaways:

1. Balance AI and Human Interaction: Understand when to use AI for efficiency and when to maintain human interaction for empathy and connection.
2. Detailed AI Prompts: Treat AI like an intern, providing detailed and specific prompts to guide its outputs.
3. Evolving Skill Sets: Customer service professionals need to develop new skills to effectively manage and edit AI-generated content.
4. Involve Frontline Workers: Include frontline workers in decision-making processes to ensure technology meets their needs and enhances their productivity.
5. Advocacy and Voice: The importance of customer service professionals finding their voice and advocating for their industry.

Transcript

Kevin Dean (00:00.816)
Hey there and welcome to Swimming with Sharks, a deep dive into customer ops. I'm your host, Kevin Dean of ManoByte, and I'm thrilled to have you join us for an exciting journey into the dynamic world of customer ops. On this podcast, we will explore strategies, tools, and innovations that will drive exceptional customer experiences.

From the industry experts to frontline innovators, we'll dive into the challenges and triumphs of customer ops, uncovering the insights that you, that from seasoned professionals or others. So we're excited to get started. And today we have an amazing guest on our show. Christina, welcome, glad to have you.

Christina Garnett (00:47.174)
Thank you so much for having me. I'm excited to chat.

Kevin Dean (00:49.84)
me too. So maybe can you start by just giving us a little bit of background about yourself and your journey into the world of customer service?

Christina Garnett (00:58.438)
Absolutely. So I started off not very traditional background. I was an English major in college, then taught math for five years. When I found marketing, the kind of the common thread that kind of went through my entire journey, regardless of career path or vertical, was really being customer obsessed. And so I went from being a marketing director for my local SBDC, telling customers and clients and small business owners how to really kind of...

take care of their customers and really improve their marketing abilities. But then I also was doing social listening for a art museum and for ICUC for Fortune 500 brands, really kind of understanding what is customer sentiment and what is looking, what is it looking like across social. And then at HubSpot, I ran HubFans, which was an advocacy program, really kind of tailored to staying close to the customer and understanding what pain points they have and what matters to them. And...

How can we really provide not just a good customer experience, but a great customer experience? And so now, I'm a fractional chief customer officer and I work with startups and agencies doing the same thing, really being customer obsessed and making sure that they feel as close and connected to the customer as possible and they understand what's happening to them good, bad, and indifferent.

Kevin Dean (02:13.072)
That's awesome and you and I first connected at HubSpot so this is really nice that we can have this conversation today. So could you tell me just so that we can get to know you just a little bit better, can you tell us a shared interesting fact that people may not know about you?

Christina Garnett (02:15.302)
Yeah.

Christina Garnett (02:29.286)
Yeah, so probably the most interesting fact is that I come from a long line of anglophiles. And so my dad raised me on classic British television and movies. And so probably the best thing to think about is that I'm obsessed with like hammer films. So Peter Cushing, Christopher Lee, like old school British stuff. If you follow me on Twitter, you'll know that I like Doctor Who and all of these other things.

But I got to meet, because my dad was a nerd and an anglophile, we wound up meeting characters at different conventions and stuff. And so when I was like four years old, I got to meet James Dewan, who was Scotty from the original Star Trek. And I have a picture of him holding my Care Bear. So he probably made my Care Bear a little bit better. I upgraded it. Yeah. Yeah.

Kevin Dean (03:18.896)
is so awesome. That is great. That's an amazing story. That's so cool. So when we think about customer service, customer experience, customer ops, what do you see as one of the biggest challenges facing those people in customer ops today?

Christina Garnett (03:39.366)
I think that probably the biggest challenge right now is the integration of AI into their work. Because it should make it more personal, but right now the way that the economy is working, they know they need to use AI into their jobs, but they're kind of fearful, not kind of they are, they're fearful that they're going to be easily replaced by AI. And so we're seeing a lot of layoffs in the customer touching space.

A lot of the frontline people are the ones that are getting laid off first, which is really sad because that's where the customer relationship actually lives. Those are the people they're used to, that's their point of contact, that's the person that they reach out to when they don't want to talk to a bot. And so as you're integrating AI into what you do, which you absolutely should, you should also be very protective of those frontline people because those are the people who your customers want to talk to when something's good, when something's bad, when they need something.

And when you remove them for AI, you're removing a layer of that relationship, whether you realize it or not. And so that's a huge problem facing them, trying to get resources, trying to showcase that they essentially pay for themselves. A lot of people want to see customer service as a cost center when honestly, it's the moat. It's protecting what you have because they are the ones that are taking care of your customers and making sure that they give them a reason to stay.

Kevin Dean (05:01.552)
Yeah, that's an awesome perspective. AI has a ton of value, but without the customer in the middle, there's going to be challenges that businesses will face if they don't implement it successfully and if they don't do it the right way. So can you share an example of maybe what you have seen that works or people should be thinking about to kind of overcome these types of challenges?

Christina Garnett (05:29.286)
Yeah, I think you need to look at what is the overall customer journey and where are the opportunities for automation, where are the opportunities for personalization, and where do you need to protect what is human? We've all been at a certain situation where we were either like heavily angry or frustrated. And because we got the right person on the phone or we were able to talk face to face with someone, they were able to deescalate us and take us from angry to they actually really heard me and they cared about me.

AI is not going to be able to come up with that empathy. Maybe five, 10, 15, 20 years from now, maybe. But right now, we understand that bot literally does not understand what I'm going through because they've never been in that position. And so what you need to do is you need to be very protective of what should be AI and what should be human. And go through and look at the full customer journey. What are the things that are very vulnerable for humans, for your customers? What are the touch points where they want to feel heard?

When you are really angry, you don't want to talk to a bot. You want someone to yell at because you need to get that anger out, but you also do that with the hopes of they're going to see how escalated I am and they're going to want to move mountains to take care of me. And so in those like really hyper elevated moments, you're going to want a human. You don't like the bot didn't give you a logo onesie when you just had a child. Like,

That's a hyper emotional moment that you want to be like, my CSM sent me that. Isn't that the cutest thing you've ever seen? Shuey does a great job of this. When there's a pet that passes away, they send flowers, they'll send paintings. And the card that comes with it is signed by the person who took that call and talked to that person. I'm sure there's automation that is a part of that entire process, but it is not the full process and it is not what the customer sees. So when you're thinking about it,

what should be automated, what should be human, and if you're not sure what, then look at the emotional tethers that are attached. The more emotional it is, the more human your reaction needs to be.

Kevin Dean (07:39.6)
I love that thought of looking at the emotional tethers and that really is very thought provoking to make sure that that's kind of being your guidepost as you're leveraging AI automation and technology into your workflows and into your streams.

So we understand that AI is big. You've talked about some of the challenges that could come up with it. Do you see any opportunities for leveraging technology to, along with humans, provide a better experience?

Christina Garnett (08:13.766)
Absolutely. One great example is game theory. I'm absolutely obsessed with game theory, but a computer is going to be able to do it better than you. So when you're looking at your customer journey or you're looking at how they're interacting with you, being able to use technology to go through and be like, where are all the different opportunities here? What are all the different ways this could go? If you're building a workflow, classic case of game theory, what are all the different behaviors they could take with this first part?

And then what do I need to build based off of what behavior they choose to do? And then based off of that, what's next? And then what's next? I think game theory is a huge opportunity for us to lean even deeper into tech, even deeper into AI, and then personalize those experiences. You can write prompts to say, all right, I'm building out this workflow based off of this specific initial behavior. Great. How can I personalize these?

to really make it feel like I'm following them on this very, very specific journey, but I'm tailoring it in a way that makes sense to them. And so that's gonna be a huge opportunity for you to use technology to automate, to personalize, but also keeping in mind that there's so many different ways that this could iterate. How many different, like, how many times 10, times nine, times whatever are you gonna have when you're building out these workflows? Because I think a lot of people...

when they're building out their workflows, they're probably thinking in terms of they could do three different things and then we'll build off of that. But they don't really, really focus on the full game theory of it all. There's so many behaviors you probably haven't thought of, but the tech might be able to educate you on that.

Kevin Dean (09:55.824)
You know, this is great. You're talking about a lot of tech that is important nowadays. But a lot of people don't know, they understand GNI, they hear that term, they hear the term game theory. What are some actual applications that are integrating these technologies that our listeners should be thinking about?

Christina Garnett (10:19.398)
I love a tool called Magi, it's Magi .co, and it basically, you buy a license for it and it has like Claude and Mid Journey and it has like GT, it has a ChatGPT 4 in it and it has like all these different pieces. So you're able to kind of go in instead of feeling like you have to have like multiple tech stacks. So I absolutely love Magi. One of the things that I really love is going in and being hyper specific.

A lot of people that are getting really poor quality stuff from their AI, it's because they're thinking one sentence prompt is gonna solve all of their problems. So the best example I can give is, if you're looking at a Magi or you're just looking at ChatGBT, is you need to start treating the AI like an intern, but like the smartest intern you've ever had. They are brilliant, they learn really quickly, but they have no experience in the line of work that you do.

And so what you need to do is you need to talk to them the way that you would an intern. All right, you want a spreadsheet? All right, what are the parameters? What are the columns need to be? What do they need to be thinking about in terms of what that looks like? My prompts are paragraphs. They're not sentences. I'm really thoughtful about like when I'm using AI, what do I want them to do? What are the guidelines? What are the guard rails? What is my objective in doing this? Like, what do I hope to gain? And then I ask it questions.

And so like at the end of this, based off of all of this, please give me a couple of questions that I can answer to make your job more specific or easier for you to be able to get me the right answer. I find that by talking to the AI like a human, it actually gives you better results because you're gonna naturally give it more information instead of just assuming, well, it's gonna scrape the internet and it's gonna have all the answers. You can't make that assumption. That's getting a lot of people into trouble. So talk to it like the smartest.

human who has no idea what you do.

Kevin Dean (12:15.6)
I love that and we see that all the time. You really do have to train AI to understand how to work with your business cases. Can you talk, and I love the concept that you talked about here about, you know, really thinking about it as the smartest intern you've ever had and really prompting it along in order to really get the best results and the best uses out of it. So talk to me a little bit about what you're seeing with

the combination of AI and automation and those two things coming together in the customer space.

Christina Garnett (12:52.166)
I'm seeing that it's a trap for a lot of people. And I can relate this back to what I said previously about a prompt. A lot of people are expecting AI to be this, they're seeing it as this one stop shop. It's gonna fix all of your problems. It's gonna solve your productivity. And then it's always gonna be good in, good out, always. With data, with AI, with all of these things. And so we need to understand that it is learning.

but that means that we as the human get to be the educator. And so what I'm seeing with automation and with AI is they're expecting it to do all of it. They're expecting that if I write one sentence, it's gonna do an entire day's worth of work for me. And then they take it at face value and assume that the AI knew what it was doing, and then they don't edit heavily. If you are gonna be someone who is a prompter, I also need you to be an editor.

Kevin Dean (13:44.784)
Mm. Yeah.

Christina Garnett (13:50.95)
And so you need to have your red pen ready so that when it does give you something, you're able to thoughtfully say, all right, but I need you to rewrite this, but now I want you to remove this or include this, or this tone isn't right, it actually should read more like this, or this isn't applicable for this specific customer. In this case, we need to make sure that we are being hyper -specific and focused on da -da -da. But you need to now be the editor. And I'm seeing a lot of those...

A lot of people skipping that step and that's where we're seeing a lot of the problems with AI. Where we're seeing, like we saw this with Google's AI overview. It's scraping the internet, but the internet has parody sites. The internet has the onion. And so it's asking questions and it's pulling up specific things that are now coming directly from the onion. The onions editor on Twitter was actually showing screenshots of like past onion blogs with.

the AI overview stating, it was like, put glue on your cheese on your pizza to make it stick or like you need to eat like small rocks a day, things like that. That's because someone is not editing. Someone is not babysitting the AI to make sure that it's not finding like, like you're not gonna quote Monty Python and say that this is like more to Arthur. Like yes, there's a King Arthur, but that's not specifically from that. You know what I'm saying?

Kevin Dean (14:58.512)
Mm -hmm.

Christina Garnett (15:16.582)
And so you need to be the editor. And I think we're in such a rush to have AI do all the work that we're not being in a position to realize that that just evolves us into the editor. I need to now go through what the AI has popped out to me to say like, is this accurate? Is this correct? It could be correct, but not be in line with the messaging that you want to offer. That's also something valid that you need to consider.

And so if you're listening to this and you're like, yeah, I've been doing these prompts. How much are you having a red pen with you once it spits out something? Because you need to be like, that's where your new time is, is how can we make sure that we can improve this and then teach the AI to learn better? Not just reject it, what's wrong with it? And that goes back to the intern. You're not just gonna be like, this is trash. How is it trash? How is it not what you were expecting? Why is it wrong? What does good look like?

And I think that's another problem that we have with AI is I think a lot of people don't know what good looks like. So it's very binary of like, this will do, or this isn't good enough. And then AI is broken instead of, you need to be that person that holds their hand, that gets them to good. They don't necessarily know what good looks like if you haven't educated and helped them learn that.

Kevin Dean (16:34.032)
Yeah, this is great stuff. You know, I'm thinking that it sounds like to me that there's a whole new skill set that is entering into the customer service world. Can you talk about what does that skill set really look like?

Christina Garnett (16:50.214)
Yeah, I think that as we are building and as we have more technology, there is this creative destruction, which is obviously like we're already starting to see it happen. And I think that we're so focused on the destruction, we're not seeing and focusing on the creative side. So what parts of CS are now gonna be possible that never would have been possible before because of time limitations, resources, anything like that. And so for customer experience and customer success professionals,

They really need to be looking at AI as how is this gonna be my tool? How is this going to be my weapon of choice that's gonna unlock opportunities for me? It's gonna unlock learnings, things that I probably never would have had the chance to do before. There's a huge opportunity there for people to really kind of step up to be even closer to the customer because they can have AI take care of things, they can automate certain things, and then they can be hyper -focused on what needs to be human. And so,

for the future of that. And I think that we're gonna continue to see this. Whenever we're in a healthy economy, you see a lot of people start kind of stepping away from the customer because it feels like a feeding frenzy. it's okay, we'll have leads tomorrow. It's fine, that person will just be replaced. But in a low economy, when money is scarce, you see people basically go into starvation mode and they start clutching their customers.

like very tightly and they want to be closer than ever before, which is great, but that's how you should always be. You should always want to be close. You should always want to understand. You should always want to be deeper into their understanding of, all right, this is how you behaved, but why did you behave that way? Is that something that we could control? Is it completely a variable that we have no understanding or control of? But you don't know that unless you're doing that. And so I'm hoping that CS professionals,

are using this time to really flex that muscle of what holding on to your customers looks like so that when the economy improves, they can still flex that muscle. They'll have that muscle very, very strong. And I think the AI should be essentially like Monear. How can you Thor's hammer? Like, how can it be the weapon? It's not what makes you special, but it does make you better. How can we utilize it to get our work to the next level?

Kevin Dean (19:10.96)
Yeah, I think it's definitely time right now for companies to power up and maintain that extra that that strength that they're gaining right now for the long term. So when you think about how tech is being used, especially AI in the customer service space, are you seeing it come from more of a top down approach or more of a bottom up?

Christina Garnett (19:15.462)
one.

Christina Garnett (19:36.358)
I'm honestly seeing it more from a bottom up approach. Leadership wants AI used, but I don't think they understand exactly what that tactically looks like. And so they might have ideas, but it's really, it's a huge opportunity for the practitioners and the people in the trenches to utilize that, but to share their learnings up. And so I think it's a huge opportunity if you're in the customer experience space and you're utilizing AI.

to socialize what you're doing, especially if you're managing up, to really kind of educate them on what that actually looks like. Because no matter how low you are on the totem pole, you are in a powerful position because you understand the customer better than anybody else. You know, like face to face, you've talked to them, you know how they feel good, bad, ugly, like you get them. But you need to create more visibility.

and socialize that information and how you're using AI to do that. And so I'm seeing it go up, but I'm not seeing it go up with the purpose that it should have. Like leaders should know exactly how AI is being used, not because they dictated it, but because they saw their people as experts in what they do and was like, our CSM team is amazing. This is how they use AI. And I trust them because I know that they're good at their job. And I know that they're good at the job because look at all these KPIs. Look at our customer retention rate. Things like that I think are really, are,

I think there's a huge opportunity for leadership to really talk to those people. How are you using it? What does it look like? How is it helping you? What are you able to do with the time that that's freeing up for you? Is that more calls? Is that more customer interviews? Like, what does that look like? I think there's a huge opportunity for learnings and then also an opportunity for those, for the bottom level practitioners to be able to really advocate for their work and advocate for, hey, this is what I'm doing currently.

But with a few more resources, look at what else I could do. Look at all the different ways we could really tap into more customer insights.

Kevin Dean (21:36.176)
You know, we're seeing a lot of bottom up usage of AI as well. And we think it's great. It really is. But there is a lot of potential risk when you're taking a bottom up approach. Can you talk about some of the risk that maybe some of the executives maybe aren't aware of that could be out there for them?

Christina Garnett (21:43.846)
Mm -hmm.

Christina Garnett (22:00.038)
Yeah, first off, there needs to be an understanding of what AI and technology is capable of, specifically with IP. So you could have people who are, under good judgment, are using AI tools for their work. But depending on what AI tool they're using, that might be basically putting that information back into the global learning model versus it being kept private.

And so I think there's a huge opportunity for leadership to really have those tough conversations about, here's how, I'm not gonna tell you how to use AI in your daily work, like specifically the tactics of it. What I am gonna do is I'm gonna empower you to be able to make good decisions based off of it. So here's the AI tools that we are interested in using because it's gonna keep our IP information private. Here are the tools that we like because we know that it's gonna be safe if it's there and it's not gonna come out and things like that.

I don't think that practitioners are using AI with the whole extent of, this is gonna do my work and I get to share company secrets and no one will know. Like that's not what's happening. But it does have the potential for it to seep out and they were doing it to just make their job better. They were doing it to help the company and it still had negative consequences. And that is an opportunity for leadership to have those tough conversations about AI to be like, here's the tools we're gonna use then.

Here's the tools that we approve based off of this understanding that if you were to put company information in, it's gonna stay secure. Here's what we need. And really kind of helping them choose their tech stack. Here's the things that we approve. Here's what this looks like. If you have questions or if there's a tool that you like, let us know. And a lot of that goes with the idea of us pushing AI so quickly that we're not using it the way that we would something else. Like there's gonna be, depending on the size of your company, especially if it's enterprise.

you're gonna have an ops team and a legal team that wants to go through any vendor you wanna go through that for tech. But when AI gets involved, it feels like everyone started using ChatGPT at the same time without going through the traditional guardrails of, well, the ops team has to approve and there has to be a vendor approval process. We need to slow down for a second and then go through the channels the way that we did. And that is an opportunity for leadership to step up to say,

Christina Garnett (24:24.262)
Just reminding you, very excited and glad that you want to use AI and all these new tech options, but we still need to go through the processes. We still need to go through our ops team and legal structure and vendor approval process. And then from there, then go crazy. But we need to protect ourselves and then communicate why you're doing that. I'm not trying to slow your job down. I'm trying to protect the company. I'm trying to make sure that you can work in there and you don't have to worry about what you're sharing and you can feel safeguarded.

Kevin Dean (24:53.52)
So that's awesome. We got to think about those risks when it's being used from a bottom -up perspective. But talk a little bit about the challenges that are going to come because executives may not understand AI. And you've got your ops team who doesn't understand it, your legal who doesn't understand it, and all these other places who then end up slowing down the adoption of AI tools within the organization. Talk a little bit about why that's a challenge.

Christina Garnett (25:23.27)
That's a huge challenge and I don't think it's even just an AI challenge. I think it's something that a lot of companies are facing where if someone, how do you set someone up as an expert if they're not in leadership? How do you trust that someone is a subject matter expert and you're going to treat them accordingly, but they don't have a VP plus title attached to them? If you are a company that prides itself on the, on the employees that you hire, then you have to, whether you like it or not, you have to understand that they are the expert in that specific work.

And so I would challenge companies at any level that if you're hiring great people, treat them like you think they're great people, treat them like you trust them and you know that they're great talent and that the oneness of their knowledge is not dictated by their title. You could have someone, you could have someone very low in your organization, but they're incredibly curious. They're very hardworking. They are deep diving into every single AI rabbit hole to learn.

and they want to educate others and they want to help the team grow. The door should not be shut for them simply because the title, it does not have a certain word in it. How can we elevate and empower those employees? But if they want to be seen as subject matter experts or they are subject matter experts, that the company is going to provide them opportunities so that they can educate. That is something that's going to pay dividends for the company because not only is it going to help leadership and legal and all these other teams learn so they're not.

like stifling progress, but that's also going to create employees that love working for your company because they feel empowered and special and they know that their power in the company and how they are perceived is not nearly dictated by their title. It's dictated by what they bring to the table and the impact that they can and want to provide. That's incredibly powerful for companies of all sizes.

Kevin Dean (27:14.544)
Yeah, that's awesome. And that really gets me to this thought of best practices for integrating tech into the customer service workflows. Can you share maybe just one best practice that you think can really help organizations move forward with the way that they're thinking about and adopting tech?

Christina Garnett (27:35.558)
Yeah, depending on who the tech is for, the people who are doing that work and are gonna be using that tech stack, they need to be a part of the decision making process. They absolutely do. How many times have you started a job and you're told, all right, here's the new tech that you're gonna be using, here's how you use it, and you're sitting there thinking, okay, I can do this, I've used this before at a previous job, but this is actually gonna make my job harder because it's clunky, or it doesn't do what we need, or.

you want me to drive revenue, but this isn't going to help me track that. And so whoever is going to be on the front lines using that tech stack, they need to be a part of the process. Even if it's very early on to say like, what does your daily job look like? What are the things that would be really helpful for you to get your job more, make your job more efficient, more productive, more impact driven?

What are the KPIs you're looking at? What are the KPIs your manager is looking at to determine success? And then have that be a thoughtful part of the audit of what tech stack they need instead of saying like, hey, we all signed up for this. It's great. Now you should go ahead and do it. You need those people to be able to tell you how they do their job. That is by far best practice. They need to be a part of the process.

Kevin Dean (28:51.6)
That is awesome. I love that being a part of the process is really going to help companies be much more successful as they move forward. Well, you've shared with us some amazing tips, some amazing thoughts. I know that our listeners are going to eat all of this up. Before we kind of wrap up here, can you tell me...

What is it that's exciting you most other than AI? What are some things that you're seeing that are exciting you most in the world of customer ops?

Christina Garnett (29:22.854)
I'm seeing more and more CS and CX professionals find their voice. They're finding their voice on social, they're finding their voice in blogs, they're finding their voices in podcasts. They're speaking up for themselves and they're speaking up for their customers and I absolutely adore that. I love that they're getting their voice and they're advocating for what they need as an industry because that's honestly how it gets better. That's how you get improvement. One person asking for something, it's not gonna move the needle. But when you have this collective group of voices,

that's starting to chant the same thing, you start seeing movement. And so I'm very excited about that.

Kevin Dean (29:56.848)
that's awesome. So if our leaders wanted to connect with you, how would they do it?

Christina Garnett (30:01.862)
I live on Twitter, for better or for worse. You can find me there at that Christina G. And then you can search for me on LinkedIn and you can check out my website at pocketcco .com.

Kevin Dean (30:11.664)
Love it, love it, love it. Christina, this has been so amazing, so fun. Thank you for sharing all of your insights with our audience today. And we look forward to connecting with you again in the future. Thanks. We'll see you next time.

Christina Garnett (30:24.71)
Absolutely.