Today we've got a real treat for you. In this insightful conversation, our CEO, Sophie Wyne, sat down with Josh McKenty to discuss his impressive journey in tech, from building e-commerce websites to leading customer success functions at large enterprises. With his deep understanding of the evolving tech landscape, Josh shares his thoughts on navigating the rapid rise of AI, the challenges it presents, and how startups can effectively scale their customer experience. Whether you're just starting out or you're running a big team, you're gonna want to hear Josh's take on balancing all that fancy automation with good old-fashioned personal touch. So, let's dive in!

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Video Transcript:

Sophie: Well, thank you, Josh, for hopping on this interview. We're super excited to chat and yeah, just basically learn a little bit more about your journey, your thoughts on the current crazy AI landscape, and then we'd love your tips in the customer experience space since you built out teams before yourself. So yeah, thanks so much for joining.

Josh: Absolutely. So glad to be here. Really, really happy to chat.

Sophie: Yeah. Well, let's just start out with your kind of beginnings and journey in tech. It's very exciting and very comprehensive, so we can start there. Yeah. How did you get started in this phase and what's that journey been like?

Josh: Sure. I was unusually lucky in that there was a computer in my home when I was very young and so I started writing software when I was six and a half and I basically learned to write Apple basic and Apple assembler at about the same time that I was learning to write English. So I have always written code. It's kind of like part of who I am and how I relate to the world.

And it means I was on the internet in high school and before that actually I was on BBSs and sort of dial up early days of dial up BBS. And so I worked in tech basically right out of high school. I built e-commerce websites in Pearl and early government websites in like PHP sort of for municipal government agencies and stuff. 

I ran a DNS reseller and then I went into working on video games in about 2000. I joined a video game startup and went from video games back into enterprise software and worked on billing and financial accounting systems for medical malpractice insurance. And then I was really fortunate to be on the Netscape team for Netscape 8 and 8.1 and spent a few years as the tech lead for the Netscape browser which taught me a lot about the internet and also scale. 

And so from there I just got into the Silicon Valley startup ecosystem, started working at startups, started starting startups, worked at NASA for a little while, sold a startup, worked at Pivotal, was part of the IPO there. I've tried to have every possible job in tech now. Not quite everything. I've done some seed investing and some advising. I've never been a VC. I think that's probably the last one.

Sophie: Yeah, that's it. Amazing. Well, I love that. That was a really quick overview but there's so much to kind of unpack there. I feel like we go in a million directions of your experience but the one I would love to double click on is building out customer experience functions. When you are starting out a startup or when you're more scaled, what are some of the downfalls or common mistakes that teams make? What are some tips? Would love to know your thoughts.

Josh: Yeah, I'm just gonna riff. I didn't prepare any answers and I knew we were gonna talk about this but I didn't think about it at all. So I'd say the starting point is people make the mistake of thinking that customer success or customer support always means the same thing and it really doesn't.

So I worked on the AOL Instant Messenger toolbar for Internet Explorer and at the time AOL Instant Messenger had 98 million users and so we had, when we launched the product, we obviously had zero users and six months later we had 35 million. So when you have 35 million users, it's a very different customer success or customer support job than let's say Pivotal.

When I was at Pivotal as field CTO and we went public, we went public and we were worth kind of six billion dollars and we had 300 customers. So the customer support function between 35 million and 300, it's just very different. So I'd say the starting point is just don't think you're doing the same job.

If you are a small startup and you're building your first customer support function, I think the most important thing to do, if I think about when I've done this well, is to make sure the person leading that function understands the customer and empathizes with them. Not necessarily that they're an expert at scaling your customer success function because that's important later, but earlier, and there's this expression that's a little bit out of favor in the startup world called turning the team.

And it basically acknowledges the fact that often the people you need in a small team, in an early stage startup, are not the people you need in a 3,000 or 5,000 person business. And over time, you're going to have to replace your leaders. They're either going to grow into those roles or they're going to leave and you're going to bring someone else in, or they're going to move sideways and you're going to end up working with them to hire someone who can expand that role. And that's really true in customer success.

The person you need day one is someone who really understands the personality of your customer, can relate to them, can understand their- because they don't know what they don't know. And they don't know how your software is supposed to work or supposed to be used. They're not living inside your head. And so there's this bridging problem with the words they're used to using and the words you're used to using, especially if you don't come from that industry.

We did this really well at Pivotal because we sold to folks in every industry. We sold to banking and we sold to insurance and we sold to automotive manufacturers and aerospace companies and governments. Probably the most stark example was we did a lot of work with the Air Force and the Air Force uses very specific words to talk about what they do and what their job is and the deadlines and who's involved.

And they're the same words as other industries, but they mean different things. And so in a corporate environment, if somebody talks about mission, it doesn't matter. Mission doesn't matter in corporate. It's a mission statement. It goes on the wall. It goes on the website. It's not like, you don't think about mission. You think about profit.

In a government agency and especially in a defense context, mission is everything. That's the tangible thing. That's what you know you're doing. Everything else is bureaucracy. You have bureaucracy and mission. And so you need the customer success folks to really relate to who the customer actually is.

And then later on, you need to hire someone who understands how customer success should work and how to hire and how to support and what tools to use and how to evolve that function so that it can scale. But that day one, you just need someone who gets who your customers are.

Sophie: That makes a ton of sense. I really love that. I really love the difference even just between mission and how that is taken in by different audiences. I think that makes a ton of sense. 

How have you seen, I guess, how have the most successful customer success or service teams you've seen scale? What do they focus on? Are they focusing on automation? Are they focusing on continuing that white glove service where they can? What do they focus on?

Josh: It's a great question. I'd say I'll use two examples. Rackspace by far, I mean, their brand identity is fanatical support. So all they care about is the experience of working with them in their customers. And Rackspace bought a company that I was a part of. And so I got to know the founders pretty well. And then they were a major partner of the OpenStack ecosystem.

And they, I wonder, I don't think this is trade secret. They really care about two things inside Rackspace. The first is net promoter score, NPS. And so if you go into a Rackspace office, especially in sort of customer support functions, the desks are arranged in kind of these pods. So there's a pod of like four or five desks together. And there's a team that's that pod. And there's a flagpole above the pod that has the net promoter score of that team on the flag above the pod.

So they identify and live by how does the customer experience us? And the second thing they really, really like is what's called strengths finder. They really like this idea that every person in the organization has different strengths and weaknesses. And that in a business context, you don't necessarily want to focus on overcoming your weaknesses. You want to focus on doubling down on your strengths, especially in a customer support context. And so each person has a small flag at their desk that has their top three strengths.

And so they really think of like, when we're dealing with customers and when we're in this team and every call we have, are we taking advantage of the strengths of our team? And are we keeping the customer's experience top of mind? Now, in order to scale, because your question was really about scale, it's not about doing the same thing for each customer. You know, it's like in the early days, the Paul Graham do things that don't scale experience. That obviously doesn't scale.

But staying focused on NPS can be about automating, delivering the same experience. So for example, the number one thing that makes people love an interaction is that they feel heard, they feel listened to. So if you create a lot of communication channels, often NPS will go up and then your support burden goes up as well, because now you have all these different places you've got to listen to customers.

If some of those communication channels can point them back towards a great knowledge base, then the cost of running the channel goes down and your NPS stays roughly the same. So as long as people know, and then the other thing you're doing is you can use automation to make your customer support reps more efficient. So like they're still answering a ticket, but they're using a bunch of snippets. They're just like pulling in knowledge-based articles and then I have to write each one of those things from scratch, right?

So then this becomes like, how is your leader of customer success thinking about improving efficiency over time? Well, at every board meeting, I would have our VP of success present on how are we doing in customer support? And the first thing I wanted to know is what's our NPS? And the second thing I want to know is what's our average time to close a ticket? And the third is what are the metrics of productivity, like tickets per rep and et cetera?

The rest of that funnel is about, are we using automation so that we're handling more tickets with the same team instead of having to scale the team up linearly, right? So your customer support team is going to get bigger, but you don't want it to be getting bigger directly in proportion to your number of customers. And you can course correct if you're always looking at like, what's our NPS and what are our metrics?

What's our performance metrics each month or each week you can go, okay, well, we got a little more efficient, but NPS went down. So that was probably the wrong approach. So let's maybe take a step back and change that. We never worked off of one year or two year, five year plans, right? Especially in the customer success space, it was always quarter by quarter.

The other thing we did, which I think was non-traditional at the time, I don't know if it's traditional now or not is the community function was always part of our customer success function as well. And that's because one of the things that really improves NPS is a sense of community. Most organizations think of community as being an external function or a BD function or a hiring function or whatever.

If you treat it as a customer success function, that external support community well articulated and well moderated is a big productivity booster. Everyone loves to be part of a club, right?

Sophie: Oh, I really like that. That makes a ton of sense. I love the NPS for flags. That is awesome. And I think that makes a lot of sense of automation and losing white glove service doesn't have to go hand in hand. It's really just scaling that white glove service. The experience goes with you. That makes a ton of sense.

And stepping back and getting into the AI hot topic, I know you have a ton of experience in the tech space and now kind of learning this new frontier of AI as well. I'm curious what you think about the challenges that are facing smaller startups or teams or kind of like in this vein of topic for customer success, scaling and disruption, I guess blanket statement question. What do you think about AI and its part that it plays there?

Josh: Yeah, fascinating question. I'm actually hosting a salon, a private salon on this topic tomorrow of like, how are people responding to having their industry disrupted by AI? And customer success is one of those and marketing is one of those and programming is one of those and et cetera.

Let me give a preface first, which is that I'm old. I'm not that old like biologically, but I feel old because I've been writing software for so long that I have seen all of these waves. And I think when I was young, I was naturally excited about new tech. And as I've gotten older, I'm naturally skeptical about new tech. And I think both of them are appropriate. Yeah.

Because in the long term, new tech is always both powerful and disappointing. And I think we're definitely in that part of the hype cycle where like AI is maximally exciting and minimally disappointing. And we're descending quickly into the AI is disappointing in all these ways. But that doesn't mean we don't come out of that trough into like AI is a part of how we do everything.

I'd say the closest analog and maybe this is trite or not interesting is perhaps desktop publishing. So my parents both worked in publishing when I was small and so I was around like Letraset. I don't know for those of you who know what Letraset is, it was a thing that looked like a computer, but it was not a computer. And what it was, was a machine that would print out text in a font on a thing that you could then glue down on a paste board.

So typesetting, like laying out words on pages to make books, was still a manual process when I was first exposed to computers. Desktop publishing didn't exist. Right. Letraset was the closest thing and the size of a Letraset machine was like a wall of a room with a screen and a keyboard in it. It looked like a computer, but it wasn't a computer.

And then I watched that whole industry panic as desktop publishing came in because I said, well, what do we do? We have all these skills about getting text nicely laid out on the page. And what about an eye for design and all these desktop publishing tools are going to make everything look terrible and formless and the character of books will, you know, whatever.

And then there was a generation of those people, the creatives in publishing who embraced computers and said, oh, this is how this can be a force multiplier for the work I do and the creativity I bring to it. So I think we're having the same fear that AI takes away all of the job. And as opposed to embracing that AI can automate the drudgery of the job.

If we learn how to be strategic. So in the customer success setting, if you have a customer ask, if you have a thousand customers every day asking the same question and you have agents who are answering those questions by hand, you need a knowledge base. If you have a knowledge base and every month you have agents writing new entries by hand, you need AI, right?

Like this is kind of the problem you're solving at Ariglad is saying, Hey, here's an here's the next iteration of a thing. We have a human doing by hand that isn't adding value. Yeah. But that doesn't mean you don't need a human talking to the customer, understanding the problem they're having, you know, and even it's like Superhuman. I use Superhuman. Now I'm a recent convert. I was very reluctant.

And as I get older, I'm more suspicious of technology things, but their ability to summarize an email is so helpful. I don't want to read the whole thing. I'm going to read it, but I kind of just quickly want to read the summary. You need an expert in place. I mean, it's a lot like pilots, right? Pilots flying planes, pilots don't fly planes. 90% of the time in a commercial aircraft, the autopilot is flying a plane, but you want the pilot there in case it gets tricky.

Sophie: Yeah. That's a really good example. 

Josh: Yeah. So customer success, we need more pilots. And we need everyone involved to become pilots to be like, how would you land this plane? How do you turn this moment with an unhappy customer into a teachable moment, into a recovery opportunity, into something that gives you a chance to defend the brand promise?

Sophie: Yeah. A hundred percent. Yeah. I mean, I think for me, I was in customer success before, you know, becoming a founder. And I remember updating the knowledge base was just the last thing that everyone did. They had absolutely nothing to do. And even then you would just avoid it because it was so tedious and so boring. And you knew you'd have to do it again next month anyway.

And I love the pilot analogy. I think that it's funny. I went through an experience with AI recently where I was definitely like fully disappointed. And it was when we needed new headshots, basically. I needed new headshots. My co-founder Ali needed new headshots. And we tried the AI headshot thing because, you know, it was all the rage and there was all these ones with all these five star reviews. And Ali tried one and it was terrible. It was like kind of scary because it was just like an AI version of Ali that did not look like him at all. And I tried it and it also didn't work. And so now we're getting headshots taken on Monday by an actual photographer. 

And I think that, yeah, there's, I think we're all going through growing pains of figuring out what industries it's going to disrupt more than others. And like you said, I think in almost every situation, it's going to be like, you are going to be the pilot, a human has to be the pilot. AI is going to take care of all the boring stuff, even for copywriting, which is the one that everyone talked about being totally, you know, death to. 

Josh: Slam dunk. Yeah. 

Sophie: Yeah. I mean, like ChatGPT is not a hundred percent reliable. You need someone looking over it, making sure it's the right tone. So no, definitely agree.

Josh: Yeah. I mean, it's a bit like saying, Hey, we should never write in any programming language other than C, right? That's not true. We should use higher level languages. But understanding that they're all machine code by the time they're executed is helpful, important, and knowing when you should pull the escape hatch and go, you know what, let's write some C. 

Yeah. I think we're just, the abstractions are important and they get us to scale, and then we have to know when they're wrong. And, and I think that's true in all domains. You know, even farming, right? You got a tractor and you got giant mechanized automated robotic tractors with satellite footage that doesn't mean the farmer themselves shouldn't go out in the field every once in a while and kind of like actually see how it's going.

Sophie: Yeah. A hundred percent. Yeah. Well, thank you so much, Josh, for your insight. I knew this was going to be such a fun conversation and to not disappoint. This is great. And, you know, and yeah, just thanks so much for joining. 

Josh: My pleasure. It was really fun. Best of luck.

As the conversation wraps up, it's clear that Josh's experience and forward-thinking approach offer a refreshing take on today’s tech challenges, particularly in scaling customer success in an AI-driven world. His insights remind us that while automation is essential for growth, the human touch remains crucial in delivering exceptional customer experiences. Thank again to Josh, for sharing your wisdom and offering practical tips that can help teams of all sizes thrive in this ever-evolving landscape.

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