Building a Churn-Proof Relationship Network

How can you take a scientific approach to ensuring that client churn becomes far less frequent?

Churn proof may be an impossible bar to reach, but how about churn resistant?

Are there some tangible steps you can take today to make your company less prone to client churn?

Only one way to find out, and that would be listening to this episode.

Hi, I’m Courtney Baker, and this is AI Knowhow from Knownwell, helping you reimagine your business in the AI era.

As always, I’m joined by Knownwell CEO, David DeWolf, Chief Product and Technology Officer, Mohan Rao, and NordLite CEO, Pete Buer.

We also have a discussion with Matt Stauffer, the CEO of Titan, about why he thinks the mad rush towards AI, everything is getting a little out of hand.

But first, what does LinkedIn CEO, Ryan Roslansky think about how AI will impact the future of work?

Let’s find out from Pete Buer.

Pete Buer joins us as always to break down the business impact of some of the latest and greatest AI news.

Hey Pete, how are you?

I’m good Courtney, how are you doing?

I’m doing great.

In a recent interview with Bloomberg, LinkedIn CEO, Ryan Roslansky, shared some advice to help AI proof your career.

So Pete, what’s the big takeaway from this advice?

So LinkedIn’s CEO is probably the right person to be opining on such topics, given the domain.

Advising workers to AI proof their careers by emphasizing uniquely human skills.

LinkedIn data suggests AI-related job posts increased 6x year over year.

But interestingly, Roslansky stresses skills of communication, creativity, leadership and emotional intelligence as distinguishing.

Takeaways for business professionals at large in the world.

We’ve been talking about this for some time now, and I think we agree with LinkedIn’s CEO, but we would strike it up as a do both.

Dial up what distinguishes you on the human capabilities front, and be sure you have your bases covered at a sufficient depth on AI competencies and acumen, right?

Takeaways for business leaders.

At the same time that teams need to distill what makes them special and compelling on human dimensions, we need to bring the same distinction to the roles and their definitions as they populate our workflows and organizations.

So from a hiring perspective, as you separate out what AI can do versus what the human can do, be super, super clear in a technical way about exactly what level of human skill proficiency you need from candidates.

We may find we need entirely new language for this.

From a development perspective, it’s probably time to rewrite the syllabus for your corporate university, get rid of the stuff that AI is going to be doing for people anyhow, and bring a real edge to the stuff that we’ve been lazily referring for 50 years to as soft skills.

By the way, there’s tons more than that.

Work design, job definitions, promotion criteria, team composition, budgeting for talent.

Budgeting is going to be a completely different game going forward as we build in assumptions about how technology can increasingly enable the human to greater levels of productivity.

All of those scripts are going to need to be rewritten from the ground up.

Pete, doesn’t it just remind you, it’s almost like just a good reminder of how these the pendulum swings.

I mean, 10 years ago, everybody would have advised hard skills, hard skills, hard skills.

And now we are at soft skills, soft skills, soft skills.

It’s a crazy world that we live in.

But I think in this case, a really good opportunity to highlight kind of what makes us all human in the workplace.

And so very interesting time we live in.

Won’t it be reaffirming to go to work each day knowing that you’re getting paid for who you really are?

I love that.

Pete, thank you as always.

Thank you, Courtney.

I sat down with David and Mohan recently to talk about the idea of building a churn proof relationship network.

How would you do it?

Why would you do it?

Let’s find out.

David, Mohan, I want to take a little bit of, I don’t know, the prescription that Mohan gives us quite frequently on this podcast.

He’s going to get me later for saying that.

But when we talk about AI and how you deploy AI in your business, so many times, Mohan, your advice is find the problem, find the squeak you will and figure out, can you solve this with AI?

So the problem I want to take today is obviously, everybody wants to have customer relationships that last.

Nobody wants churn, period, begin.

True statement.

Thank you.

I thought you do fire a client every now and then.

That’s usually if they’re bad actors.

That’s true.

We don’t want to waste time on people.

One of the problems is when you have a single-threaded account, you have a single relationship, which obviously makes it a pretty risky scenario for the company.

So let’s just start with that.

That is the problem statement.

David, why don’t you set up for us why that is a problem, and then let’s see if we can solve it together.

Courtney, maybe the best way for me to explain this, I used to have a Chief Revenue Officer who used to talk all the time about surrounding the account, and I think that’s a common phrase in professional services companies, especially in all organizations.

But the idea is that a single person, knowing a single person at the client is a very, very weak relationship.

If you think about the strongest rope that you’ve ever used, right, large ropes that are really, really strong, it is multiple cords woven together.

And that is the fabric versus the string that we want to create in a professional services organization.

We want to have strong fabric that ties together the organizations, so that we can withstand different things that happen.

And those different things that happen are very, very diverse, right?

It could be executive turnover.

Well, what happens if that’s the one person you’re single threaded to?

It could be the turnover of somebody on your own team.

Well, what happens if that’s the only person that is single threaded to the client?

But it could be more than that.

It can be shifts of strategy where all of a sudden, the organization is going in a different direction, there are new investments that need to be made, and all of a sudden, the thing that we’re working on and the person that we’re working with is not the most important person at the organization anymore, maybe even getting budget taken away, right?

What happens then?

We could go on and on and we could brainstorm.

Everybody knows the different factors that go into not just churn, right?

I think a lot of times we talk about churn.

I was talking to a professional services organization last week and I was saying, hey, we’re actually great.

Our clients love us.

Our problem right now is not churn, it’s lack of expansion and growth.

And so we’re seeing a decline of our account sizes.

Well, that’s just as impactful for an organization.

If you have 10 different clients that have all reduced spend by $10, that’s $100 of decline.

That could be identical to losing one client and $100, right?

And so I think really thinking holistically about how do we build this interpersonal relationship that spans not just the executive layer, not just the stakeholders, not just the influencers, the people on the ground, all of the above because you need champions in the organization that are thinking about you, that will vouch for you, that say this is a productive, helpful relationship and they deliver value on a continual basis.

And you want as many people as possible thinking about that, knowing that, living that, breathing that, that is the definition of a real partnership.

And that’s what we’re seeking.

And way too often that does not happen within professional service organizations or any B2B services organization, frankly, that is relationship driven and not just purely transactional.

I feel like we have like actually passionately described this problem.

So now, I actually want to challenge us on, okay, we, I think everybody listening, if you’re in a professional service firm, you’re like probably shaking your head like, yeah, this is, it’s hard.

So I would love to take this problem and let’s just think about, okay, how does AI change this formula?

It brings in a different set of capabilities that we haven’t had before.

How can we think about this differently?

And how would we deploy it?

You know, what AI is really uniquely suited for is not to think of this relationship as less, but to think of them as a connected graph.

Right?

So that’s what AI does well quite naturally, because the best people who do this, the unicorns that we’ve been talking about, kind of do it something along these lines, right?

So they kind of intuitively know who the champion is, who the executive sponsor is, who the users are, in quotes, who the finance person is.

They know all of this, and they treat them differently, all professionally, but differently.

Right?

And then the question is, how can you drive value that’s appropriate for each of these categories?

Now, suddenly, you start thinking of now systems, right?

So because now you’ve taken what these unicorns do and start breaking them into steps.

In a way, kind of, we had to think of this as a marketing problem because now you’ve categorized it.

You’re thinking about driving value to each of these personas, if you will, right?

Whether the champion or the executive sponsor or whoever it is.

And then the key thing, I think, to systematize this is to create multiple entry points, right?

It could be QBRs, it could be roadmap discussions, it could be user feedback sessions, right?

And be able to take all of this and put it back into a system that hopefully is powered by AI, that allows you to get this information in and be able to analyze it.

And then the last thing I’d say is, there are core metrics and there are behavioral metrics.

They’re both very important in these types of, because you’re talking about relationship.

But some elements of getting this thinking of this graph, thinking about who is who, driving proactive value periodically.

It can be like every six to nine months.

Periodic value to these parties, and multiple entry points.

These are the things that people do naturally.

I think they can be systematized, and you can use AI to solve the problems that I’ve been describing.

So let me just push into one of those things that you said, Mohan.

You said periodically delivering value.

Well, the question is, how do you deliver value?

How do these unicorns come up with that?

And I would go back to, here’s what I think AI does better than we’ll ever be able to do as human beings because it can do it reliably over volumes and volumes and volumes of information that we can’t.

It collects dots and it connects dots, right?

So it can pick up all sorts of signals.

It can parse through more information, more communication, more data than you and I ever could get our heads around in infinitely less time.

And it can take all of that information and it can find the signal from the noise and it can connect the dots to figure out what the inferred signal is.

And then it can surface that up.

So as human beings, we connect upon it.

That is to me what the best unicorns do.

How do they deliver value?

They’re able to see all these data points and say, oh my gosh, if I connect these four dots, all of a sudden that’s value for my client and I’m going to periodically deliver that, right?

And so we’re able to, to your point, systematize not just, hey, periodically I need to deliver value, but oh, periodically, before I even think to ask, right?

I may not be the consultant that naturally asks for that, but AI can not only remind me that that’s what great consultants can do, it can actually give me the tidbit that I need to reach out and say, hey, here’s value for you.

That’s so well said.

I mean, you know, it could be about something that’s happening in the industry or something that is happening with the client themselves or a competitor.

All of these are useful tidbits.

Can I back up just a little bit with this problem?

And actually, I wonder if the starting point is figuring out where the problem is.

Like, do you have a list of where you’re single threaded?

Do you have any idea?

I would challenge that.

They probably a lot of times don’t because I don’t know for everybody listening, but as somebody that talks to lots of companies, people CRMs, not really great.

Anything else you two would add to this solution?

You know, it needs to be a core part of account planning.

Too often, account planning is done in a very superficial way, right?

And this is a very hard problem to solve, especially in a complex account.

And this has to be the core of account planning, along with how well you’re serving, how, you know, what does the client think of you, so on and so forth.

It has to be a core part of your account planning.

Yeah, I’d end with two things, Courtney.

I think number one, I think it’s important to back up and see the big picture.

We’ve done a lot of research on what actually drives retention and growth, and it actually comes down to three things.

Service quality perception, the perception of service quality we’ve talked about before.

The strength of interpersonal relationships is what we’re talking about today, right?

That is absolutely essential, major, major factor.

And then finally, commercial alignment, which I’m sure, you know, we’ve talked about a little bit and can’t even more.

It’s being that trusted advisor and helping your client really obtain their objectives and their strategic goals, not just deliver on an S&W, right?

That’s the essence of what we’re talking about there.

So it’s one of the three core drivers.

This is not just the saying of the industry.

It’s not just an anecdote.

Hey, you have to surround your accounts.

This is the heart and soul of your net revenue retention, which is how you drive predictable growth and professional services.

90% of your revenue every single year should be coming from existing accounts and you should be growing those, not only retaining them, but growing them.

This is how you do it.

So I think it’s important to contextualize it and understand how important it is.

The second piece that I would say is candidly a little bit of a selfish plug, that I’ll just throw out there.

This is precisely a big part of what we’re building at Knownwell.

This has been really, really hard to manage, to measure, and to really get your hands around for a long time.

And we have a social map that we analyze based on the real time communications.

And we are advancing it every single day to take it to the next level in terms of providing some of these insights that are so powerful and helping practitioners to become unicorns and deliver this type of value and build this type of fabric.

And if you’re interested in partnering with us and being a co-development partner in our beta program in order to take this to the next level and to really start to put some of these practices in play, we’d love to work with you.

So, you know, reach out and we’d be happy to chat about whether or not you’re a fit for the beta program.

David, Mohan, thank you for diving into this problem and talking through kind of how AI can help us think about it differently than we have before.

Thank you as always.

Thanks, Court.

Thank you.

We talk a lot on this show about how you can use AI in your professional services business.

Do you want the playbook for scaling and growing your service company in this AI era?

Good news.

You can download our brand new white paper for AI powered strategies for scaling professional services.

Grab it now at knownwell.com/scalingwhitepaper.

Matt Stauffer is the CEO of Titan, a software development company that specializes in building the world’s best web and mobile apps.

He’s also an author, podcaster and frequent speaker at conferences and industry events.

He sat down with Pete Buer recently for a robust discussion.

Here’s part one, stay tuned for part two, coming your way next week.

Matt, welcome, it’s so nice to have you on the program.

Thank you so much, Pete, it’s great to be here.

I wonder if for the sake of our listeners, you might give a little context to get us started, your role in the business and kind of where it fits into the AI meets professional services space?

Yeah, absolutely, so my name is Matt Stauffer, I am the CEO and co-founder, originally CTO.

I don’t do CTO work anymore, but I’m still kind of technical lead at Titan, which is a consultancy, we’re building custom web applications.

And so AI is in our space in a lot of ways.

I mean, the most prominent one is everyone saying, hey, is AI gonna replace your job?

And then there’s also the aspect of clients come to us saying, hey, we feel like we should be using AI, but we don’t actually know how, so can you help us build it?

Even to the point where some clients are coming to us saying, you need to prove to us that you’re using AI effectively, so we know that our spend with you is gonna be worth it compared to other teams that are working quickly using AI.

So I’m very actively involved in the business development process, so that’s where those conversations are happening, but I’m still kind of like the technical lead of the company as well, so I’m also talking with my team about how are we using AI, how are we helping our clients use AI and all that.

So that’s cool right out of the gates.

When you are requested to demonstrate proficiency in AI use, how do you do that in the sales process?

It’s usually pretty cursory.

It’s usually, hey, are you using AI?

And we say yes.

And then if they are really technical, they’ll ask questions like, okay, well, which model are you using?

And are you using IDE or using the CLI?

It’s super technical stuff.

And the fact that I’m capable of proving that I can is enough.

One of the things, so for the first almost 12 years of the company, my business partner, who was a former developer, did all of our business development, but I was the one who was actively developing.

And as he stepped away from the company over the last few years, I’ve taken on all of his calls, and I’m still actively developing.

We find it’s really valuable because I can speak the language.

So when we get these highly technical people on calls who would kind of poke holes in a CEO level schmooze guy’s ability, they’ll poke at me and I’ll just start talking tech to them for five minutes.

They’re satisfied.

I know what I’m talking about, and then we get back to the business.

Awesome.

Well, I cruised around on your website for a while, and I love it, and I especially love the language that you use.

We sweat the hell out of the details.

It’s kind of cool.

As your philosophy or ethic that you bring to helping companies figure out how to remove roadblocks to growth, that got me to wondering, as you’re working, especially with professional services companies, but also in general, are you seeing patterns in the roadblocks to growth that folks are looking for help with?

That’s a really good question.

Historically, roadblocks to growth when you’re talking to a development company is we have an existing tech-based application.

There’s one of two.

We have an existing tech-based application that we realized is holding us back.

It’s 10 years old, we wrote it internally, we learned as we were going, or whatever else it could be where it’s basically, we know it was enough and it’s not enough for our next stage of growth.

So either it’s a specifically planned stage of growth, like we’re going to take some funding or whatever else, or maybe even it’s just we’re just seeing an uptick.

We need our technology to be set up to take us the next 10 years.

That is usually modernization, technical debt removal, often moving to a more modern framework from something that was hand-rolled.

The other thing is the block to growth is we have internal processes that are not using technology the way it should be.

At best, it’s going to be an access, but usually it’s more like we’ve cobbled together three different Excel spreadsheets.

And again, we just know that we can’t make it where we need to get it.

Or the end users can’t use this, so it takes five people manning these spreadsheets.

And we know if we built a tool, there could be, you know, we could move them on to more important things and the tool could be doing all that work.

So at some point, at some level of the technology we have is not going to serve the scale.

Almost always it’s scale related that we know is coming or we hope is coming.

How can you help us build technology that kind of just removes friction from our workflows?

Nice, and I suppose AI is an occasion for every company to ask both of those questions about themselves?

Yeah.

Yeah, and most folks, AI is less an opportunity to say, how can you remove friction and AI is more a stress point that they feel like they’re going to get left behind.

I would say the ideal and the aspiration is that people are looking at AI as an opportunity to remove friction, but the reality is the vast majority of times is it’s the pressure that the message they’re hearing over and over and over again is, if you don’t catch up on AI, you’re going to get left behind.

They feel fear and anxiety, and they say, how can I not get left behind?

These are questions asked by their PE, their board, their customer.

Customers don’t care about AI.

Customers are more likely to be annoyed when you introduce AI when you shouldn’t.

That’s the funny story.

Everybody’s introducing AI and the customers go, wow, it was cheaper because of course, you’re going to charge us for your LLM costs.

And it was easier the way it was.

Very few customers have said, you introduce AI, thank God.

But yes, it’s the PE, it’s the board, it’s the people who are supposed to be making sure things are good.

And then they talk to the people on the ground, they say, well, you’ve got to get AI in there somewhere.

And then they come to us and they say, help us with AI.

Yeah, good.

It’s a good time to be in a business where you can answer those kinds of questions.

That’s awesome.

In professional services, your objective typically, beyond simply serving the customer’s need, is to retain the customer over time and build long-term relationships.

Is there anything about AI projects that changes the approach to long-term customer retention?

So in the end, we have this weird conflict where we want to build tools where they don’t need us anymore, and we also want to build a long-term relationship with them.

And AI is just like anything else in that you can do it in such a way where they’re less likely to have to call you later.

But unlike many other tools, AI is really, really fast moving.

So at Titan, the technical tooling that we built is intentionally tooling that doesn’t shift a lot from year to year.

Like, you know, for the technical folks in the audience, if we were in the JavaScript world, we would have to be there every six months because everything changes in the JavaScript world every six months.

So we don’t live in that world.

We live in a world that is much more stable.

You know, you could take an app that you built five years ago, and as long as you’re just checking for security updates, it’s still going to work fine.

And so building AI into that world necessarily forces us to stay more actively invested with our clients because whatever we build on may not even exist in two years.

And so I don’t want to like I don’t like putting my clients in situations where they have to call us every time they want to make a change.

But AI does put us in a situation where they have to call us just because we have to be in touch every six months to make sure everything’s actually still working.

Outside of that constraint, I feel like in the end, we’re still building tools and we’re building tools with external dependencies and our clients need us to make sure that those tools keep using or keep working.

And so we will with any client, with any tool, with any dependency say, hey, let’s check in every six months to make sure everything’s still going well.

And with those clients, we’re also checking in every six months to say, hey, are there other projects we can work on for you?

I don’t think AI has a huge impact on that.

How about from the client side?

As I’m, you know, if I’m running a business and I’m asking myself the questions that you’ve posed, should I be building build capability myself?

Should I be buying?

Should I be renting?

Especially as you described what the ongoing sort of service and communication and contact needs to look like after the initial build is done, just to stay in touch on the fact that technology is changing.

Like, how should I think about the trade-offs?

Yeah.

I would say if you can hold off on AI, hold off on AI.

It is turbulent.

Everything is different every three months, every six months, every nine months.

The large majority of companies that are choosing to integrate AI or choosing to use it through a third-party vendor, because if you’re doing the work yourself to build the AI, then you’re more to the metal, which means it’s going to change more quickly and you’re going to more to be kind of like, your app will be changed more every single time the technology changes.

If you’re instead using a third-party AI vendor, then you’re a little bit more safe.

But those vendors are coming and going because they’ll build this entire tool around some crazy idea that they had, build the whole thing with VC funding, and then three months later, OpenAI adds that same feature and then the company shuts down.

It is an extremely turbulent world and if you can stay out of it, it’s wise from a dependency perspective.

But I also think it’s wise because like I said, the vast majority of AI uses for customer-facing applications are actually harmful to the customer experience and your relationship with your customers because we haven’t quite figured out where it makes sense in a lot of industries yet.

Hold off, give it a couple years, the vendors will normalize, the LLMs will normalize, the providers, some of them will win out and some of them will disappear and we’ll have a better understanding from a development, product management and UX experience of where AI actually fits, such that when you come to it in a year or two or even just six months, the question of where you should integrate AI is going to be much better.

Right now, the vast majority of people doing a lot of AI work are what I call AI maximalists.

AI is going to take over the world, you should use AI for everything, slap it all over it.

And we’ve all got three or four subscriptions that have emailed us and said, we added an AI tool everywhere, it’s clippy all over again, and all of a sudden your prices are 2X, but our lives are no better.

Right?

Don’t be those people.

That’s my answer for most people.

That’s awesome.

Well, and so if, can you share an example maybe of company that has come to you with a question, I’m getting pressure, I need AI somewhere in my customer-facing offerings or in my operations, where you’ve then said, nope, now’s not the time.

Yeah.

Yeah.

I mean, there’s so many examples.

I would say, for example, we have a medical services firm that we work for.

I can’t name, but they provide services to doctors primarily who are doing cancer research.

They’ve got pressure from the PE to bring in some AI type thing.

It’s just one of these, there’s no way to do it, and the ways that we could possibly do it are touching PII.

We’ve got to be very, very careful, and they were aware of that.

We’ve got to be very careful about that.

They just asked the question of like, hey, should we be using AI here?

I said, I can’t see any way in which there’s a functional benefit here.

They did end up building one of their own internal AI-based chat bot things, where it’s entirely internally owned.

They found a way to make that work in that very narrow context.

It was the right decision, but the first question was just like, hey, how do we slap AI in the user interface?

The answer was, you don’t.

It does not make sense here.

We have other clients who come and said, can you add some AI?

It has been the clearest thing in the world.

We have one client who does scheduling for bus lines.

We found a software as a service that does scheduling with this really great intelligence to figure out your pricing on your schedules and says, given all the availability and which driver is available, and what time of year it is and previous history, it scoops it all up and says, here’s how much you should charge for this particular bus rental or this particular bus rental.

It was brilliant, it was easy, it was obvious.

But that was a practical need.

For a lot of people, it’s not this practical need.

It’s just, you know, hey, we feel it.

If someone just says there should be AI somewhere, that’s usually the example, you know.

Do you have a process for working with the company to walk through their pain points and opportunities and try to figure out where and how AI does or doesn’t belong in their strategy and operations?

Yeah, I mean, usually when we’re working with a new client, the business development process kind of hands off into some sort of a mild discovery.

And sometimes it’s like a full paid discovery over the span of weeks and months, but sometimes it’s like a series of a couple of conversations.

And with AI or without AI, we’re having the conversation to figure out what is the best way we can serve the need that you have as quickly as possible and then iterate from there.

We’re super, you know, not agile and scrum and all that, but agile in that we want to identify the narrowest need, the MVP.

We want to launch that to your eternal team or to your clients and then we want to say, what’s the next best thing to be doing after that?

And in that process, we have to work, nobody comes ready to define MVP on day one.

So we’re already doing discovery.

We’re already doing kind of product management with them.

And so during that process, either we are saying, hey, you know what, you have this need that is best met by AI, but it’s almost always called by the client first.

They almost always are eager and anxious to do it.

And before it was AI, it was machine learning or a natural language processing or whatever else.

Somebody has a desire to do some magic.

And the question becomes, is this magic, A, sustainable and providable affordably with the current state of AI?

And then B, is that actually a part of your initial offering or is that kind of like a magic dream down the road?

Whenever we hit the point where it’s right, whether it’s the very beginning or towards the very end, then it’s a process of figuring out, well, what is the simplest, you know, kind of this is something we do in code a lot.

You know, we, it’s very tempting to think through solutions at the beginning.

But what we should do at the very beginning is ask, what’s the problem?

You know, what are we actually trying to solve for our clients?

What problem are we trying to solve for them?

And then from there, we say, okay, now we can start imagining what’s the solution, what’s the tool.

But we don’t want to start with AI ideas or LLM ideas or whatever else it is, because then it’s a solution looking for a problem, right?

So with AI, as with everything else, we always want to start with, what are we actually trying to do here?

And then if AI is the right tool, then we say, okay, well, which implementation of AI?

And it’s just a natural kind of outflow from there.

Yeah, nice start with the business problem.

It’s always the answer, isn’t it?

Yeah, really.

Thanks as always for listening and watching.

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At the end of every episode, we like to ask one of our AI friends to weigh in on the topic at hand.

It’s only fair, you know.

Hey, ChatGPT.

Hey, ChatGPT, how you been?

Today, we’re talking about how to build a churn-proof client relationship network.

So, what do you think?

Honestly, it’s all about knowing your clients’ goals better than they do and hitting them with solutions before the pain even surfaces.

Keep that proactive groove going and they’ll never feel the urge to bail.

And now, you’re in the know.

Thanks as always for listening.

We’ll see you next week with more AI applications, discussions and experts.