Transforming Customer Products and Services From Cost Centers to Profit Centers with Generative A.I.

[00:00:00] Welcome to the Convergence Podcast. I'm your host, Ashok Sivanand.

[00:00:04] We are the only team that speaks to the customer on their terms.

[00:00:08] Oftentimes, I feel like care is a taxable ear flicker.

[00:00:11] You have to make a product to communicate with our fans so when they have issues, it gets resolved in the product.

[00:00:19] On this show, we'll deconstruct the best practices, principles, and the underlying philosophies behind the most engaged product teams who ship the most successful products.

[00:00:36] This is what teams are made of.

[00:00:38] Hey, folks. Welcome back to part two of our conversation with Doug Cramon, the head of fan support at ESPN.

[00:00:46] In part one last week, we explored Doug's fascinating journey from practicing bedside ethnology, studying Native American cultures,

[00:00:55] to leading one of the most customer-centric teams over at ESPN Disney.

[00:01:01] Today, we're diving even deeper into the strategies and technologies that his team is using to enhance fan support.

[00:01:09] From leveraging generative A.I. to balance efficiency with customer empathy through their proprietary catharsis scoring,

[00:01:16] to transforming their customer care team from a cost center into a profit center by generating revenue through fan loyalty

[00:01:25] and converting customer issues that are challenging into moments of delight that lead to loyalty.

[00:01:31] Now, if you've wondered if your customer service team might benefit from generative A.I.

[00:01:37] or how actionable customer feedback directly shapes product improvements, this conversation is likely for you.

[00:01:46] You've gathered by now that I personally have a strong passion for delightful customer experiences.

[00:01:52] So I love the way that Doug shared how ESPN is redefining what it means to create value for their customers and generate loyalty.

[00:02:00] At the end of the episode, I also speak about my experience working in customer engineering

[00:02:05] and how it helped shape many product decisions and frameworks later in my career,

[00:02:10] especially as the industry shifted from one-time perpetual licenses to subscription licensing that most SaaS companies have now adopted.

[00:02:18] The reflection at the end is especially for folks looking to transition their customer care teams from cost centers to profit centers

[00:02:27] and includes 11 key tactics that are reflected upon based on my experience.

[00:02:34] But first, let's hear from Doug.

[00:02:41] I think technology and automation, even more broadly, is finding its way more and more into customer service.

[00:02:47] And I have noticed maybe an anecdotal trend that I'd love for you to kind of give, you know, point me a thumbs up or a thumbs down on,

[00:02:55] where I find that companies that tend to think of their customer service teams as a profit center in the long term,

[00:03:03] as opposed to think of them as a short-term cost center,

[00:03:07] tend to find more ways to invest in enabling their teams with stuff.

[00:03:11] And the folks who are maybe thinking about it as more of a short-term cost center are looking to replace their human agents with AI agents.

[00:03:20] And in your case, what I'm hearing is that you're using AI to augment your human team and give them superpowers,

[00:03:27] as opposed to replacing them.

[00:03:30] So, tell me if that's right or wrong, and also, what was the thought process behind that?

[00:03:37] You know, we're at a crossroads right now, where AI is moving so quickly and evolving so fast,

[00:03:44] that we need to determine what is it that our customers want.

[00:03:50] I can't answer that question, but my customers can.

[00:03:54] So, by surveying them, we understand the dynamic that they wish to have.

[00:03:58] You know, the fact is that my bots right now are dealing with, you know, haven't left the dynamic of Uncanny Valley.

[00:04:08] They're still kind of weird and kind of creepy, and they're not humanistic.

[00:04:13] And we make sure that when you speak with our chat bots, for example,

[00:04:17] they represent themselves as, I'm just an automated assistant.

[00:04:21] And they're not human, because if they tried to pass themselves as such, that would look weird and would be creepy.

[00:04:29] So, we're at also a point where we know that, in many cases, AI can still make mistakes.

[00:04:37] And so, we need to make sure that those that we've hired and spent a lot of money training

[00:04:45] can, in fact, become even better specialists in what is required to support the fan.

[00:04:52] Now, does that mean in a year or so, I might need fewer of them?

[00:04:56] Yes, because certain things that are very rote can be supported by generative AI and things like RPA,

[00:05:04] where, if it's what we call MACD's moves, adds changes and deletes to an account.

[00:05:09] I wish to cancel.

[00:05:11] You know, a bot with RPA can do that.

[00:05:14] I wish to upgrade to a different plan.

[00:05:16] We'll take care of that for you, and a bot can do that.

[00:05:19] But if it's something that requires conversation and deeper dive discussion,

[00:05:26] a description of an issue that must be troubleshooting, it's going to require air agent.

[00:05:33] Now, I'm a practitioner of customer service.

[00:05:36] I have no background in things like Google Vertex training models,

[00:05:40] Google Cloud Platform, legal indemnification.

[00:05:45] By the way, there's a lot of departments of a company that are involved in everything with generative AI.

[00:05:49] Most people at GCP have no true understanding of legal indemnification.

[00:05:55] And most lawyers don't have an understanding of Vertex, CCAI, and anything like that,

[00:06:01] let alone the basics of a customer service tech stack.

[00:06:05] So, we have to work with, you know, what we do, which is, I am a practitioner and a specialist in customer service.

[00:06:17] So, what can I use to improve upon and augment my agents, make them better?

[00:06:25] It's an easy ask.

[00:06:27] I then interview, I'm again, I am the bedside ethnologist, and I ask my agents,

[00:06:33] what's making you less productive?

[00:06:36] What's making you less efficient?

[00:06:38] What's negatively impacting your image as a care agent, right?

[00:06:42] And what's concerning you with regards to safety, security, and stability?

[00:06:46] We call that model the RIPES model.

[00:06:48] It's also known as the SPIRE model.

[00:06:51] I memorize it as RIPES, revenue, image, productivity, efficiency, safety, security, and stability.

[00:06:57] So, I ask my agents, what is hindering you in regards to any of those elements?

[00:07:03] Well, what would that be in my knowledge base?

[00:07:06] Or I take it back, in my situation where if I were a care agent,

[00:07:10] if you ask me a question, and I'm new to fantasy football, I've just been certified,

[00:07:16] and I ask you, I have a question about, you know, when brackets lock or something like that.

[00:07:24] I probably have to go and type that question in to the knowledge base

[00:07:28] and wait for a macro, an article that might describe it.

[00:07:33] Wouldn't it be easier if Generative AI was just listening and swooped in the answer,

[00:07:38] not just as a macro, but elegantly wrote it out as if I, the care agent, were saying the answer to you?

[00:07:46] That would save a ton of time.

[00:07:48] Efficiency makes me more efficient.

[00:07:50] Also, at the end of the conversation, I should have, I have to summarize the conversation at the end, right?

[00:07:57] That should be something that the AI does, and immediately when I say,

[00:08:01] I appreciate your time, have a great day, boop, it immediately puts in the summarization.

[00:08:07] And then it dispositions it too, because I have to build back to other departments.

[00:08:11] So those things make our agents much more efficient.

[00:08:16] Thus, they can take more contacts, and they result in better CSAT scores, and they're happier.

[00:08:22] That means I need fewer agents.

[00:08:24] That's a positive.

[00:08:26] So am I still a cross-center?

[00:08:28] Yes.

[00:08:29] Yes.

[00:08:30] So can AI be used to make me a profit center?

[00:08:34] Most definitely.

[00:08:35] You mentioned the magic words there of transitioning from that cost center to a profit center.

[00:08:40] As someone who worked in customer engineering early in the day,

[00:08:43] I was able to generate a whole bunch of new revenue based on understanding other things

[00:08:48] that the customer wanted that we could solve, but they didn't know about.

[00:08:51] And also long-term revenue by making sure to be pretty good about transitioning my insights

[00:08:57] that I learned from the customer into our product roadmap so that the customer felt like we got them in the future.

[00:09:03] And so you mentioned transitioning towards a profit center.

[00:09:07] Tell me about what that looks like or what your vision is there.

[00:09:09] Some companies have the ability to cross-sell and upsell.

[00:09:14] They have product sets that Care can constantly do that for, and that's great.

[00:09:18] Some companies don't.

[00:09:20] And if they don't, maybe there's other ways to add value.

[00:09:23] And that also helps move you to a profit center because when it comes to the life cycle of the customer

[00:09:28] and how much they spend, if you're able to quantify how long they are using the service or using it more,

[00:09:35] that quantifies us as a profit.

[00:09:37] So in what we do, for example, our care agents, of course, they can upsell an opportunity.

[00:09:43] So we're using generative AI to analyze the conversation and determine aha moments that are a plus one.

[00:09:53] What does that mean?

[00:09:54] If we're talking about fantasy and you've asked me that question about when do rosters lock and, you know,

[00:10:02] what is my waiver order because I need to pick up a running back because my current running back or quarterback,

[00:10:09] let's say, is injured, like Dak Prescott said, injured, you're going to have to pick up a replacement quarterback.

[00:10:16] Well, wouldn't it be great if I explained to you the answer, but then the generative AI in my CRM system

[00:10:24] swoops in one, two, three articles about who to sit and who to start this week in fantasy

[00:10:32] to make you a better fantasy manager.

[00:10:35] And then I can share those articles with you.

[00:10:38] One might be a free article, but then I can share the other two and say,

[00:10:41] hey, Shulk, if you like that article, that's great.

[00:10:44] Here's some more insight that will make you a better manager.

[00:10:47] And these two sit behind the paywall because they're on ESPN Plus.

[00:10:50] If you're interested, I'd love it if you subscribe to ESPN Plus, if you found this valuable.

[00:10:55] What we do is we're able to floodlight those articles and track all of them.

[00:10:59] So we can see, did the customer click on those articles to read them?

[00:11:03] And did they buy?

[00:11:05] And that's pretty impressive to see click to conversions that air free.

[00:11:09] So now we're using generative AI to offer extras to make you a better player in the game and a better fan of ESPN

[00:11:17] because we're always looking out for you, the fantasy manager.

[00:11:20] So you win your league, you win your week because we're offering you exciting, interesting content.

[00:11:26] And I just didn't solve your issue.

[00:11:29] I actually solved for something else.

[00:11:32] I kept ESPN sticky.

[00:11:33] I made sure you understood how to manage the waiver wire and how to work in waiver order, a selection of a quarterback.

[00:11:43] But then I said, you know what?

[00:11:44] I'm not a prognosticator.

[00:11:46] I don't write articles about who are the best quarterbacks to pick up for this week.

[00:11:50] If I said that to you, I'd be fired.

[00:11:53] That's not what their agents do.

[00:11:54] But I can say, hey, here's some great articles by our award-winning writers that you might benefit from and allow you to win your week.

[00:12:03] How amazing is that?

[00:12:04] I personalized it for you and made the experience better.

[00:12:08] So we're doing a lot of that.

[00:12:10] And suddenly we're seeing those conversions, which quantifies us as trying to make sales and acting as profit center.

[00:12:17] So we're doing a great deal of work to make sure that we enhance the fan experience by giving them tools to be a better thing.

[00:12:31] Fostering an engaged product organization and aligning them with the principles around lean, human-centered design, and agile will more than likely lead to successful business outcomes for your organization.

[00:12:44] But getting started or getting unblocked can be hard.

[00:12:46] This podcast is brought to you by the player coaches over at Integral.

[00:12:51] They help ambitious companies like you build amazing product teams and ship products in artificial intelligence, cloud, web, and mobile.

[00:13:01] Listeners to the podcast can head on over to integral.io slash convergence and get a free product success lab.

[00:13:11] During this session, the Integral team will facilitate a problem-solving exercise that gives you clarity and confidence to solve a product design or engineering problem.

[00:13:22] That's integral.io slash convergence.

[00:13:26] Now, back to the show.

[00:13:32] I imagine when you're having this level of opinion in terms of how you want to take care of your customers, Disney and ESPN, of course, Bleeding Edge, and there's a lot of Bleeding Edge technology like AI you're building in.

[00:13:45] You can't just use off-the-shelf tools.

[00:13:48] You've got to use some integration or customization of the various tools and frameworks available.

[00:13:54] So, there's a number of things that you said earlier that I really liked, like living, eating, sleeping in the community with the customers so you get to really understand them.

[00:14:04] You're segmenting, which is something that's hard for us to do when you mentioned fans in the stands and suits in the suites.

[00:14:12] And I imagine that there's like the product team that works alongside your team probably loves working with you, given that you're already thinking in a way that they are wishing they could think.

[00:14:25] So, what is your interaction with that product team that's building this technology for your agents?

[00:14:30] Yeah.

[00:14:31] The product team is unique.

[00:14:32] And as customer service is often a very lonely group in a company, a lot of executives don't necessarily truly comprehend the value of being able to speak to a customer on their terms.

[00:14:52] No other department does that, by the way.

[00:14:54] I mean, if we send out polls or surveys, we're asking our own questions on our own terms.

[00:15:01] So, we'll get some good customer data and that happens all the time.

[00:15:04] But when you reach out to customer service, it takes effort, which I've said before.

[00:15:11] Effort means you don't want to do it.

[00:15:14] And thus, you have something to say and it matters.

[00:15:18] And it likely impacts one of our products that you're not happy with, you're confused with.

[00:15:23] So, we're a very precious organization to a company because we are the only team that speaks to the customer on their terms.

[00:15:33] And so, oftentimes, I feel like care is a tactful ear flicker.

[00:15:38] We have to make sure product doesn't build a product.

[00:15:42] The product in engineering team, oftentimes, I feel like they build a head with no ears, right?

[00:15:47] Here is customer service.

[00:15:49] You have to make a product and a model in a way to communicate with our fans.

[00:15:56] So, when they have issues, it gets resolved in the product, something like that.

[00:16:01] So, oftentimes, with the product teams, we're making sure that they are helping us from the beginning

[00:16:08] create bespoke tooling that allows us to get the information we need, like catharsis scoring,

[00:16:17] so then we can deliver wonderfully actionable data for them to act on to make the product better,

[00:16:26] the pricing better, improve promotions, streamline interactions, and overall happiness with the application.

[00:16:34] Product price promotion interaction.

[00:16:36] Oh, limitation and application.

[00:16:38] Remove limitations.

[00:16:39] It's the PILA model.

[00:16:40] Another acronym, I can't help myself, PILA, product price promotion interaction limitation application.

[00:16:47] We make sure that whatever we do when we track the conversation, we are making sure that elements

[00:16:54] that impact one of those attributes are identified, and we can bring it back to the product team

[00:17:00] and say, hey, did you know that, for example, during a UFC fight between the early prelims,

[00:17:08] and the prelims, or between the prelims and the main event, because in UFC there are pre-fighting

[00:17:13] events, so to speak, in a UFC pay-per-view fight night, that there is a slate that says,

[00:17:21] your event has ended.

[00:17:23] Well, if you paid $30 plus for the event, right, and suddenly it says, midway through, and you haven't reached the main event yet,

[00:17:31] your event has ended?

[00:17:33] It's going to make you kind of sad.

[00:17:35] And, wait, I paid for the main event, and it ended?

[00:17:39] No, the slate was unclear.

[00:17:42] The slate said, your event has ended, meaning the prelims.

[00:17:47] What it should say is, the prelims have ended, now do this to go to the main event.

[00:17:55] Well, Pear sees the feedback, because suddenly we're inundated with contacts with confused fans,

[00:18:01] and they all say the same thing.

[00:18:04] So we track.

[00:18:06] Recency, frequency, sentiment, and velocity.

[00:18:09] The words that are used over and over again, in the moment they're said, they're all said at the same time,

[00:18:15] because it's a live event, hey, I'm having this problem, everyone's having this problem,

[00:18:20] because it's transitioning at this very moment from the prelims to the main event.

[00:18:25] They're not happy, sentiment is bad.

[00:18:28] Velocity, everything came in at once, because it's a moment of confusion.

[00:18:33] We immediately bring back that to the product team, we say, change the slate,

[00:18:37] and they have all the data they need, and they change the slate,

[00:18:41] because they heard it directly from the customer's mem, not anecdotally from customer service.

[00:18:48] So I can't just say that.

[00:18:51] I have to execute by garnering all the accurate data I can from the concept conversations,

[00:18:57] bring it back to product, and say, this isn't from Diamond.

[00:19:00] This is from Fansmen.

[00:19:02] This is exactly how many people experienced it.

[00:19:05] This is exactly what they said.

[00:19:06] And if you fixed it, it would remove my number of contacts by this amount,

[00:19:11] and thus saving me this amount of money and care, benefiting the company,

[00:19:16] because I will no longer receive this contact,

[00:19:18] because fans will know where to go when they want to watch the main event.

[00:19:23] We do a lot.

[00:19:24] Doug, one of the things that I love to ask all the guests to help me keep up with just delightful products and services out there is find out what some of the things are that have delighted you recently at home or at work.

[00:19:38] So what comes to mind?

[00:19:40] So I work in New York City, and I live in New Jersey.

[00:19:45] And like individuals who, let's say, live in Vancouver, LA, Toronto, any large city, commuting is a bear.

[00:19:53] Now, I don't work every single day at the office.

[00:19:56] But what I do, it's the final mile.

[00:19:58] That is a big pain in the butt.

[00:20:01] So I'm constantly looking in my life to make my life more enjoyable.

[00:20:06] And that commute is sadly not.

[00:20:08] It never has been.

[00:20:10] So it's that final mile where I'm constantly trying to find what can get me to work quicker with less effort.

[00:20:18] So I'm a huge fan, and I obsess over e-scooters.

[00:20:23] I used to use kick scooters, but my knee is giving out, and so I have to use an e-scooter.

[00:20:29] However, there's a lot of problems with e-scooters.

[00:20:32] Some of them catch fire.

[00:20:34] Businesses don't want them in their room because if the battery explodes, that's a huge problem.

[00:20:40] So I've found what matters to me is a product that I call when something's elegant.

[00:20:48] When something is elegant, it means something to me.

[00:20:52] There's a value in it.

[00:20:53] I appreciate it.

[00:20:54] You found something or something that's elegant in your mind.

[00:20:56] It's something that you appreciate, you value, and you can relate to it and it has meaning.

[00:21:03] For me, what is a scooter that's easy to use, easy to charge, low risk, not a fire hazard,

[00:21:11] and it gets me to and from.

[00:21:13] It's light.

[00:21:14] It's foldable, and it makes my life easy.

[00:21:17] And so I found there's a company called Pure that's making one, and they're linked to an F1, a Formula One constructor.

[00:21:29] So there's a driver, Lando Norris.

[00:21:31] His father owns a company that makes these scooters.

[00:21:34] And the studies they do are rooted in so much of aerodynamics, weight, efficiency, range, comfortability.

[00:21:46] And so they have a product that is just so amazing that I live for because it works, and it works well, and it makes my life better.

[00:21:56] Sure.

[00:21:57] That's all it is.

[00:21:58] I love that.

[00:21:59] We will make sure to check it out and put a link in the shoutouts for everyone listening.

[00:22:04] Doug, thank you so much for taking time out of your busy schedule to share so much with us about how you run your team,

[00:22:11] how you use technology, and how you interact with the technology teams.

[00:22:15] Thank you, Rochelle.

[00:22:16] The pleasure is all mine.

[00:22:17] I appreciate it.

[00:22:23] This question around customer engineering and whether it's a cost center or a profit center is one that I think we've heard a lot of more recently,

[00:22:35] and I think it's going to continue as a trend.

[00:22:38] With the rise of product-led growth, care teams and account management teams who maintain customer loyalty,

[00:22:48] help the customer derive more value more seamlessly from the product,

[00:22:52] are emerging as the growth leaders of your business.

[00:22:55] And this is as opposed to the traditional marketing and sales functions that used to be the growth heroes.

[00:23:03] So if you're asking whether your care team is a cross center or a profit center,

[00:23:09] I think despite whatever your CFO or strategists might say,

[00:23:14] the simple answer is based on just two data points,

[00:23:17] and one of them is a lot easier to calculate than the other.

[00:23:21] The harder of the two, depending on how you allocate your revenue,

[00:23:25] is how much of your revenue can you attribute to being generated by your customer care team?

[00:23:32] And the second one is, what does it cost to run that team?

[00:23:36] And depending on whether you're net positive or negative on the profitability there,

[00:23:40] I think determines whether it's a cost center or a profit center.

[00:23:44] Of course, that transition requires a lot of hard work and maybe some luck.

[00:23:49] Otherwise, it wouldn't be a debate anymore.

[00:23:52] Now, back in the mid-2000s and early 2010s,

[00:23:56] I got to work in customer engineering at a company called ShopLogix

[00:24:00] when I was on their software team.

[00:24:02] Over there, I later went on to work in product management and sales engineering and sales,

[00:24:08] and eventually opened up their Europe, Middle East, and Africa distribution.

[00:24:14] I was there for six full years.

[00:24:17] And during that time, I feel like I was really lucky to experience

[00:24:22] how some of the seeds that we planted in the early days

[00:24:25] ended up growing into either major problems or things that we were majorly thankful for.

[00:24:33] As an aside, for folks who are curious about working in roles around strategy

[00:24:39] or things that are more future thinking like architecture,

[00:24:42] I believe that working at the same place for six years helped me a lot.

[00:24:48] At the time, my friends were switching jobs every two to three years,

[00:24:52] and every time they switched, they got paid more.

[00:24:55] Whereas I didn't necessarily get the same pay bumps initially,

[00:24:59] but I found that having six years of firsthand experience at the same startup

[00:25:04] really helped me later on in my career

[00:25:07] with having a framework and calibrated instincts

[00:25:11] around what six years of life cycle looks like.

[00:25:15] This helped me a lot during the visioning and strategy phases

[00:25:18] of new businesses, including Integral,

[00:25:21] as well as products that I helped my clients build.

[00:25:25] And it really helps me look around corners for opportunities and risks

[00:25:29] that could arise over the next few years,

[00:25:32] maybe up to the next six years.

[00:25:33] So I think that's something to consider

[00:25:36] if you're debating between sticking to one company

[00:25:39] or switching your jobs more frequently.

[00:25:44] That all being said, going back to my original point

[00:25:47] around customer care and whether it's a cost center or profit center,

[00:25:52] I thought about some of the ways that helped transition

[00:25:55] our care engineering team from a cost center to a profit center.

[00:26:00] And I've come up with 11 ways to do that.

[00:26:05] Broadly, it's either by increasing the value generated by that team

[00:26:09] or reducing the cost that it takes to run the team, right?

[00:26:15] So reason number one or thing number one to do

[00:26:18] is the obvious of reducing churn.

[00:26:21] Keep your customers where they are and help them renew.

[00:26:24] This is finding ways to reduce customer attrition.

[00:26:29] And it's already likely the number one priority

[00:26:31] of your customer care team, so I won't speak as much to it.

[00:26:35] The second one is similar but different

[00:26:38] in terms of increasing loyalty.

[00:26:40] This is a little bit more long-term and not quite as tactical

[00:26:43] and really generates fans or followers from your customers

[00:26:49] and transitions them from maybe skeptics that they were in the early days

[00:26:53] or when they incurred an issue.

[00:26:54] This really increases the stickiness in the long term

[00:26:57] and your high-quality care can act as a competitive differentiator

[00:27:02] for your customers.

[00:27:05] The next one is increasing revenue.

[00:27:08] And there are two ways in which I did it or my team did it.

[00:27:13] The first one is highlighting other parts of our solution

[00:27:16] that the customer wasn't using yet.

[00:27:18] They may or may not be paying for those features,

[00:27:20] but generally creating more value

[00:27:22] by understanding what they use today and don't

[00:27:25] and having a patient conversation is one way to do that.

[00:27:29] Doing it in a language that they're familiar with

[00:27:31] in their business and the problems that they have

[00:27:35] is another way to keep that trust level really high.

[00:27:40] This is as opposed to reading off your marketing brochures

[00:27:43] that were likely written in the lens of your own company

[00:27:45] rather than in the customer's lens.

[00:27:48] The second way of increasing revenue is by identifying other folks

[00:27:53] or departments within that company

[00:27:55] that could benefit from the products that you're servicing them with.

[00:27:59] The way I did that was by starting by earning the trust

[00:28:04] of the customer that we're working with,

[00:28:05] making sure it works well, going the extra mile,

[00:28:08] and also understanding how they function compared

[00:28:11] to the rest of their organization

[00:28:12] to understand a little bit more of that layout.

[00:28:15] And then even though it may have taken one or two follow-ups,

[00:28:19] which may seem uncomfortable,

[00:28:21] most of those customers that I'd built a rapport with

[00:28:23] were eventually happy to make an introduction,

[00:28:26] maybe with a kind word to some of their peers.

[00:28:28] The next place is customer empathy.

[00:28:30] This startup that I worked at didn't have a formal product function originally.

[00:28:36] Roadmapping was generally done by the technology teams and leadership

[00:28:40] and somewhat blessed as an afterthought by marketing and sales.

[00:28:45] And my time helping our customers through problems

[00:28:49] and understanding how their businesses ran

[00:28:53] and what they were using our solution for

[00:28:54] gave me a firsthand perspective into the true nature of the problem

[00:28:59] that we were helping solve.

[00:29:01] And also watching them helped me understand

[00:29:03] some of the friction points that existed in our solution

[00:29:06] and we were providing them.

[00:29:08] I would write these up and some of the documentation

[00:29:11] that I provided to our CTO and other technology leadership

[00:29:15] ended up making its way directly into new features

[00:29:19] or sometimes refactoring and consolidating

[00:29:22] different or disparate parts of the product

[00:29:25] into something that seemed a lot more seamless

[00:29:28] and cohesive to the customer.

[00:29:31] So I think it's key to arm your customer care,

[00:29:35] customer service teams with some of the key context

[00:29:38] and the assumptions that went into your product in the first place.

[00:29:43] Things like which roles at your customer is this intended for?

[00:29:48] Who's the target audience?

[00:29:49] What is the problem in their lens that this is intended to solve?

[00:29:54] Why is it that we think our approach to this solution

[00:29:57] is the best approach?

[00:30:00] I think this context around the assumptions

[00:30:03] plus a really trusted relationship

[00:30:05] between the product team and the customer care teams

[00:30:07] will most likely invite your customer care team

[00:30:11] to validate or invalidate your product assumptions

[00:30:14] and poke holes in them or give you high fives

[00:30:16] and also provide super valuable context

[00:30:19] as you're thinking about next versions of your product

[00:30:23] and iterating on your roadmap.

[00:30:25] I've also found that the customer team

[00:30:29] is also super helpful in identifying

[00:30:31] who the early adopters likely are at your clients

[00:30:37] and which new features they are most likely to find super valuable.

[00:30:42] I use this information to figure out

[00:30:44] who to conduct further research with

[00:30:46] or invite people to do a beta testing program

[00:30:49] and the customer care team can be really helpful

[00:30:52] in finding folks who are really engaged.

[00:30:54] Another thing is using the customer care team

[00:30:56] for usability testing.

[00:30:57] So having a designer just walk up to the care team

[00:31:00] and have them click through a prototype

[00:31:03] or look through a mock-up

[00:31:04] can be really quick and cheap ways to get feedback

[00:31:08] on your UI UX

[00:31:10] before you even involve your customers in doing the testing,

[00:31:13] which I also hope you're doing.

[00:31:16] Now, the next one is,

[00:31:19] since your care team likely has the highest amount of trust

[00:31:21] amongst the various folks at your organization,

[00:31:25] amongst your customers,

[00:31:26] they get to talk to your customers

[00:31:28] when they have their metaphorical guard down

[00:31:30] from being sold on something.

[00:31:32] And I've personally found it easiest

[00:31:34] to ask tiny little favors of customers

[00:31:37] when I'm wearing that customer care hat

[00:31:40] compared to my sales hat or even my product hat.

[00:31:44] These little favors could include things

[00:31:46] like a written audio or video testimonies

[00:31:49] that could go on our website

[00:31:50] or we could share with prospective customers.

[00:31:52] They could be referrals to folks within their network

[00:31:56] or even advice on industry groups

[00:32:00] and other distribution channels

[00:32:02] where your product would be really favored

[00:32:05] by the other members.

[00:32:06] This tends to be really key intel

[00:32:08] that can help prioritize

[00:32:10] and guide your expensive marketing

[00:32:11] and product budgets.

[00:32:14] We've spoken a lot about ways to add more value

[00:32:16] and here's a few on how you can reduce the cost

[00:32:20] or increase the efficiencies of your team.

[00:32:25] And ultimately, you're looking to kind of

[00:32:27] either increase the value

[00:32:28] or reduce the cost, right?

[00:32:30] So in terms of reducing the cost,

[00:32:32] the first one, maybe the most obvious one,

[00:32:35] especially given this conversation

[00:32:36] and the flavor of the month

[00:32:37] around generative AI agents,

[00:32:41] automation like this is obvious.

[00:32:44] I think there's an importance

[00:32:45] to be careful around how you use it

[00:32:47] and I feel like Doug provided

[00:32:49] some really key insights on this episode

[00:32:51] about when the automated agents are useful

[00:32:55] and also when there may be more risky

[00:32:58] and he'd rather have his human agents

[00:33:00] take care of those customers.

[00:33:02] I think typical product management approaches

[00:33:04] of lean delivery and user segmentation

[00:33:07] are really key here.

[00:33:09] Things like starting small,

[00:33:11] maybe providing your own care team

[00:33:14] with your AI agent

[00:33:16] to augment their work like Doug's team has

[00:33:19] before exposing it to your customers

[00:33:21] is a way to get feedback early,

[00:33:24] get benefits and understand

[00:33:26] the potential of AI early.

[00:33:27] And this is all without taking on the risk

[00:33:30] of upsetting one of your customers, maybe.

[00:33:32] Another way is by identifying

[00:33:35] the target users and target problems

[00:33:37] like Doug mentioned

[00:33:38] and deciding what you're willing to delegate

[00:33:41] to your AI agents

[00:33:42] and what kind of problems

[00:33:44] you're not quite ready to delegate yet

[00:33:46] and want the added assurance

[00:33:48] and benefits that come with a human agent.

[00:33:51] The next one is

[00:33:52] call it automating the fixes

[00:33:54] that your care team

[00:33:56] seems to repeatedly carry out

[00:33:59] as a way to resolve customer problems.

[00:34:02] Automating may be a little bit

[00:34:04] of a catch-all term here

[00:34:05] and it could be either software automation

[00:34:07] or process automation.

[00:34:08] But overall, I think it's making sure

[00:34:10] that both the product and design folks

[00:34:12] on your product teams

[00:34:13] are spending ample time

[00:34:15] amongst customer care agents.

[00:34:17] I like product folks

[00:34:19] moonlighting as care agents

[00:34:20] and then also analyzing the data,

[00:34:23] looking at the transcripts

[00:34:24] and from the calls.

[00:34:26] One thing as a caution here

[00:34:28] is that I've seen some teams

[00:34:30] try to be super efficient

[00:34:31] where they share only the summaries

[00:34:33] and dashboards and synthesis

[00:34:35] from customer care

[00:34:36] to the product team.

[00:34:37] I don't personally like this very much,

[00:34:41] especially in the early days

[00:34:42] of bridging that relationship

[00:34:44] between customer care and product.

[00:34:46] And when I have my product hat on,

[00:34:49] I would much rather get,

[00:34:50] of course, the summary and synthesis,

[00:34:52] but also the raw data

[00:34:54] so that there aren't any

[00:34:56] internal company limitations

[00:34:58] as far as quenching my own curiosity

[00:35:00] about undressing and addressing

[00:35:03] the problem space better.

[00:35:05] The next one is around

[00:35:07] building more resilient systems

[00:35:09] and avoiding a lot

[00:35:11] of the technical challenges

[00:35:12] that take up the time

[00:35:14] your customer care teams spend on it.

[00:35:18] At Integral,

[00:35:19] we would often help teams

[00:35:21] with things like test automation

[00:35:23] in their code,

[00:35:23] especially using test-driven development.

[00:35:26] Things like continuous integration,

[00:35:28] continuous delivery

[00:35:29] that really help de-risk

[00:35:32] faulty software

[00:35:33] from going out to prod.

[00:35:35] On the product side,

[00:35:36] we'd also help with things

[00:35:37] like creating beta tests

[00:35:38] or other product experiments

[00:35:40] to try and minimize the errors

[00:35:42] and catch them at the source

[00:35:44] and reduce the need

[00:35:45] for care agents

[00:35:46] to come in and rescue.

[00:35:49] This means you can increase

[00:35:50] the size of your customers

[00:35:51] without increasing the size

[00:35:53] of your care teams a lot.

[00:35:55] Another way,

[00:35:56] I think,

[00:35:57] is career development,

[00:35:59] believe it or not,

[00:36:00] and something that you're recruiting

[00:36:01] and HR teams would benefit from.

[00:36:04] As you heard,

[00:36:05] I benefited a lot

[00:36:07] from working in customer engineering

[00:36:08] when I was on a software team.

[00:36:10] It helped me understand

[00:36:12] the business value

[00:36:13] and the customer value

[00:36:14] of the code

[00:36:15] that we were writing.

[00:36:17] It also, of course,

[00:36:18] set me up really well

[00:36:19] to transition

[00:36:20] into product management

[00:36:22] and sales engineering roles,

[00:36:24] especially at this company.

[00:36:27] Product management

[00:36:28] and sales engineering

[00:36:29] or solution engineering

[00:36:32] are still extremely hard

[00:36:35] as far as hiring goes.

[00:36:37] These candidates

[00:36:38] that are great for your company

[00:36:40] are hard to find

[00:36:40] in that they require

[00:36:41] a combination of both technical

[00:36:43] and business acumen.

[00:36:45] All this in addition

[00:36:46] to domain knowledge

[00:36:48] to whatever industry vertical

[00:36:50] that your company is in.

[00:36:52] I would be willing

[00:36:53] to bet $20

[00:36:54] that some of your care agents

[00:36:56] today possess a combination

[00:36:57] of enough business

[00:36:59] and technical acumen

[00:37:00] and can provide you

[00:37:02] with a very low cost,

[00:37:04] low risk

[00:37:05] to testing,

[00:37:06] hiring the best talent

[00:37:07] onto your product

[00:37:09] and sales engineering teams.

[00:37:12] Those are the 11 tips

[00:37:13] that I have

[00:37:14] in terms of converting

[00:37:15] your care team

[00:37:16] from a cost center

[00:37:17] to a profit center.

[00:37:19] Let me know

[00:37:20] what you think of those

[00:37:20] or if you're hitting up

[00:37:21] any friction points

[00:37:23] on any of those

[00:37:23] specific ones

[00:37:24] and you want to chat

[00:37:25] about it more,

[00:37:25] hit me up on DMs

[00:37:27] or any of our socials

[00:37:29] or go to the contact page

[00:37:31] on convergence.fm.

[00:37:33] Thanks a lot for listening

[00:37:35] and sticking with me, folks.

[00:37:37] We will be back

[00:37:38] next Tuesday

[00:37:39] with another episode

[00:37:40] with one of our guests

[00:37:42] talking about principles

[00:37:43] that help build

[00:37:44] the best product teams

[00:37:46] that ship the best products.

[00:37:53] Thank you for joining me

[00:37:55] on the Convergence podcast today.

[00:37:57] Subscribe to the Convergence podcast

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