The Digital Customer Success Podcast

Data Analysis and Service Recovery Philosophy with Lane Hart of Contentsquare | Episode 041

February 27, 2024 Alex Turkovic, Lane Hart Episode 41
The Digital Customer Success Podcast
Data Analysis and Service Recovery Philosophy with Lane Hart of Contentsquare | Episode 041
Show Notes Transcript

Lane Hart of Contentsquare brings to CS a no nonesense approach to ensuring the renewal via strong data analysis combined with a very human approach of customer engagement. He has taken lessons learned from his years in management consulting at IBM forward into a rocketship trajectory in CS at Heap - now Contentsquare. 

Be sure to grab a pen and paper for this one as we talk about:

  • Scaling the Heap CS team and starting a CS Ops function
  • The importance of knowing what Data is available and how it all correlates to drive customer outcomes
  • Advice: Don’t get stuck because the data is not perfect
  • Use data in change management by ‘showing your work’ and telling a story of how you got there.
  • Service recovery philosophy: So much of CS is gracefully falling on our sword - and owning up to that can lead to some incredibly real and human moments.
  • Effective interventions on negative sentiment customers can turn these situations into extremely healthy relationships
  • Contact-level data is so often in very poor shape, not just in formatting but also in whether that contact is still at the company or what role they have
  • Implementing in-app prompts for new users for them to self-identify what role they play
  • Using bounced emails to adjust customer contact data - flagging contacts that have left - then reaching out to company to get updated contacts via active users
  • Surveys are annoying and you have to be very careful not to bombard people
  • Standardizing metrics, both product and commercial,  across departments and then putting them front and center in front of the whole company to drive alignment
  • Tracking champions after they leave a company - they can be incredibly valuable CSQLs to land new accounts with minimal effort


Lane's LinkedIn: https://www.linkedin.com/in/lanehart/

Resources:

Shoutouts:

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The Digital Customer Success Podcast is hosted by Alex Turkovic

Speaker 1:

I mean, I will often submit people submit NPS on products that I use, just to see what happens afterward, and me too, like majority of them, there's no follow up, there's no closed loop. They're just collecting the data for data's sake, and I think that a huge missed opportunity for a digital CS or a scaled CS motion. That's what I think I mean. In order to be successful in digital CS, you have to have people who are just innately super curious and willing to try and fail a lot. You'll find those breakthroughs, but you know they're always diamonds in the rock.

Speaker 2:

And, once again, welcome to the digital customer success podcast with me, alex Trokovich. So glad you could join us here today and every week as I seek out and interview leaders and practitioners who are innovating and building great scaled CS programs. My goal is to share what I've learned and to bring you along with me for the ride so that you get the insights that you need to build and evolve your own digital CS program. If you'd like more info, want to get in touch or sign up for the latest updates, go to digitalcustomersuccesscom. For now, let's get started. Hello, it's the digital customer success podcast. You've reached episode 41. That sounded like an answering machine message. For those of you who know what answering machines are, I'm dating myself. Anyway, welcome to episode 41. Great to have you back.

Speaker 2:

As always, today we have a fantastic conversation with Lane Hart. If you don't know who that is, he serves as VP of customer success at content square, formerly heap, and has just an insane amount of really good insight into building and scaling digital programs or CS programs in general. He has a background in data data science and, as he made that transition into customer success a few years back, he brings a lot of that philosophy into what he does on a day-to-day basis but brings a lot of just common sense smarts into his programs and shares a lot of that advice. On this episode, where we do talk about data, we also talk about service recovery philosophy, where you turn a negative experience into an overly positive one. We talk about metrics. We talk about the annoyance of surveys, in-app prompts, contact level data. We go all over the place, but get your note pad out, because there's a lot of really great insight in this conversation with Lane Hart.

Speaker 2:

Mr Lane Hart, I'm so happy to have you on the podcast. Welcome, welcome, welcome. Thanks for having me. Alex Been, looking forward to this for a few weeks. Yeah, it's good to have you. I typically like to start off with kind of an origin story type question, but we'll be kind of pointed with this one, because I do a little bit of LinkedIn stalking for all of my guests, as you should if you run a podcast. One of the things that intrigued me about your past is your time as Speaker of the Student Senate at University of Cincinnati. I want to know more about that. What was that all about and how did you get into that?

Speaker 1:

You really went below the fold on the scroll there. Yeah For sure we were chatting about Cincinnati. That was definitely a really good time. It was our student government at the University of Cincinnati and the role was basically just organizing like 30 or 40 senators from all of the colleges. Each college would send two senators and it was intended to be a quote-unquote legislative body. As much as any legislation that you could pass in a university would matter, but a couple of things that we did were basically pass funding legislation to give funding to student organizations and just help out with visibility.

Speaker 1:

It was definitely one of those things. I feel like it set me up well to wrangle a lot of people, because you literally need to keep order in a meeting with 40 people who all have their own agenda or sometimes after three hours of meeting are just totally checked out. It was a lot of fun. You get to kind of banter back and forth and people get to test their arguments and reasoning skills. It was fun. Then I moved on from that to do some other student leadership stuff at the university, which also was a lot of fun. Made a lot of lifelong friends.

Speaker 2:

That's cool. Did you have a gavel?

Speaker 1:

I did. I actually have a ceremonial gavel that's sitting at my parents' house in Ohio that it has my name engraved on it. Surprise possession.

Speaker 2:

That's awesome. The gap between your time as Speaker of the Senate is that correct? Yeah, speaker of the Student Senate to now you're in San Diego. You've been at Heap for four years, I think, recently into a VP of CS role there. Fill in the gap a little bit. What's the story of you getting into CS and that role specifically?

Speaker 1:

Wow, yeah, it hasn't been that long, but it seems like it's been a super long time. I've been around 10 or 12 years. After I graduated from the University of Cincinnati, I went into management consulting at IBM. In that role, I was doing a bunch of really interesting work all over the world. My focus was in data and data science. All of the problems I was working on solving were somehow related to how can we use data to make better decisions. Through that, I get to work on really interesting stuff, ranging from how do you use Twitter data to predict what people are going to buy, or use location data to understand how much revenue a store is going to do, or how to advertise the right things at the right time. We built a whole bunch of mobile apps that were the Uber for concrete and cement delivery for a really large cement and concrete company Wow.

Speaker 1:

You have to do really interesting things all over the place Again made lifelong friends. I did that for around eight or so years. That led me to wonder what else is out there. I was working with a lot of consumer-focused companies, people that were either working direct to consumer or B2B2C-type business models. I always was intrigued by software. Of course IBM also made software. It was mostly B2B software.

Speaker 1:

I started looking around at this customer success role. I didn't really know what it was at the time but I reached out to a friend of mine, michelle, who's actually still at Heap. She and I had worked together. I just thought, hey, I'm looking to potentially leave. Tell me more about customer success. She said, hey, we're actually looking for somebody to scale up the team in New York. Why don't you consider this? I'm like, well, I don't even know anything about this company. It was like a 100% company at the time. She and Veronica, who is running customer success at Heap at the time, sold me on the idea of building the team from a team of just a couple of people to a pretty large team over the last few years. It turned out to be honestly a career-defining experience Met so many interesting people, worked on a lot of interesting problems.

Speaker 1:

Our software Heap is customer analytics, product analytics. What we're doing is trying to help digital builders understand how users are traversing through their flows. It could be to buy something online. It could be to do a transaction inside of B2B software. It could be to do a financial transaction Then understand where the friction is so that those digital builders can go in and fix and remove the friction so their users have an easier time doing what they're trying to do. It actually brings together the aspects of consulting that I loved, which are around the change management, as well as the people side of things like how do you actually compel people to make decisions using data instead of just using their gut, which turns out to be the hardest problem that we're always faced with.

Speaker 1:

I've been doing a couple of different things at Heap over the years Scaled up the customer success team in New York, built a team in Europe. Then I moved actually into a role that I was doing on the side. You end up with these roles where it's a passion project and then it turns into an actual job. I created our customer success ops team, which is just a huge passion of mine because I love getting hands on with data and then hire somebody else to run that team and then came back to run the customer success team that I'm running now. That has been a lot of fun. We've announced a definitive agreement to be acquired by another company called Content Square in the near future.

Speaker 1:

Really excited to join Content Square because there's a lot of complementarity between our products. We're doing a lot of the quantitative side of analytics and getting the structured data and the funnels. They're doing a lot on the qualitative side of analytics. I'm really excited to blend the quant and call together as we join forces.

Speaker 2:

That brings me to today.

Speaker 1:

If that was an elevator, we would have gone up and down the World Trade Center like four times maybe more.

Speaker 2:

Yeah, no, it's all good. It's a cool story. It's fun to hear how folks end up in these roles, because everybody's path is so different. It's not as cut and dry as a sales leadership role or something like that. It's always circuitous, which is a word I'm still working on.

Speaker 1:

Yeah, I'm always trying to hire people too. I'm always trying to find people that are the interesting unicorns who have done enough to understand what we do and be curious about it, but they don't have to come from a traditional CSM background or a traditional management background. It just needs to be somebody who's curious about data and human behavior and how to frankly, just how to make things happen, because a lot of CS is just getting things done and building a coalition of people to care about your customer and help them out.

Speaker 2:

Yeah, and I would imagine you building that ops function. You probably saw a lot of that. Obviously, we're talking about digital CS on this podcast, but I kind of view the ops function and digital CS can be interchangeable, can be separate, can be one, you know, because there's a lot of kind of overlap in terms of, like, wrangling data, wrangling systems to, you know, accomplish kind of a task. So so I guess in that, in that vein, you know, one of the questions that I do like to ask all of my guests is essentially, you know what, what their definition of digital CS is, because it does vary, right. So I'd be curious to get your, your take on it, especially given your background and you know data and all that kind of fun stuff.

Speaker 1:

Yeah, I mean it's definitely a blurred line and that is how I got into. Like you know, at the time we weren't even calling it digital CS, but it's how I got into what we would now call digital CS and we've gone, as probably everybody has gone, through several different you know sort of like revamps of it over the past couple years. Even it's still always changing every quarter. But I guess I mean one. It's to drive more impact with our human resources which, incidentally, in a software company are pretty much always our largest cost. So it's not to replace humans, really to assist them. It's not exactly ops, because ops is more for internal purposes.

Speaker 1:

As I see it, of course, there are a lot of things that we do in ops that our customer facing. If it's done right, it improves customer satisfaction because you're giving them the resources they want and need at the moment when they need them, even if they didn't know exactly what they needed at the time. So just having that, that's where you really marry the ops and data with the execution side of things. So if I had to think about, like, digital CS is the execution, the ops and analytics side is understanding what we should try to execute to improve customers lives and I think the biggest thing is just like a lot of testing and learning. So in the in that one, our product is always changing to our customers. Needs are always changing, the competitive landscape is changing. We have to be really flexible to use the data that we have like that I call it the digital exhaust that's coming off of our platform to understand like what are some unmet needs that we might be able to help with to delight our users.

Speaker 2:

I love that and I love that you blended kind of the that enablement factor of you know enabling the team and making sure the team is running efficiently with, obviously, you know why CS is here is to drive customer outcomes and make customers successful and you know, I think that my my hunch anyway, after speaking with you and, and you know, chatting with you a little bit, but also looking into your background a little bit is that your history and passion around data and data science has, has, has probably benefited you throughout kind of the roles that you've had, but then specifically in CS, because I mean, if you ask me, one of one of the most valuable and probably looked over products of a healthy CS organization is like the data, into the data insights that we can glean from various data sources and things like that. So my hunch is and I'm putting words in your mouth that that you probably had a kind of a kind of advantage going into setting up a CS org, coming at it from that angle.

Speaker 1:

Yeah, I mean it's definitely it has helped a lot. I think it's you don't have to have a background in data or data science, but definitely a curiosity to know what's possible. I think one of your guests, whose name was also Lane, which I was really fascinated by, from Gainsight she was she kind of talked about how data relates to data and I loved that term because it really is just knowing, like, what data is out there, how might you tie it together to tell you to one to come with a story of what it, what can you, what are the 20% of things that you can do to drive the 80% impact Right, and a lot of that like just comfort in working with data and working with messy data definitely came from my time. Like dealing with you know tweets and social media data, or dealing with you know trying to join together data sets from different back end systems and that kind of stuff. In a growing company like ours or, like you know, probably most of the people listening to this podcast large companies or growing companies Most of the data is messy. You have to get super comfortable with it being mostly accurate or directionally accurate and then having some backup plans in place. So I think that comfort with things not being perfect probably went a long way.

Speaker 1:

I see a lot of people or talk to a lot of people are trying to start a digital CS program and they're you know, they basically get stuck because they the data is not perfect and they're stressed out that they're going to mess something up. Or, you know, like the ever dreaded thing where you know you send the wrong email to the wrong person, or for a long time we were worried about our you know, entitlements database being like slightly inaccurate, and then we would send messages to people saying, hey, you're not using this thing or you're not entitled to this thing, why don't you go check it out? And then they respond back and they're like wait a second, we already have this. But I mean, ultimately you are going to make some mistakes like that, and when that happens, I usually just reach out to the customers and just say, hey, like you know, we're trying to improve right now, we're trying to do things at scale, and everyone I've never had someone who is not understanding about it creates a nice human moment.

Speaker 1:

So yeah, I think that that piece of it probably helped in terms of starting out in CS and starting out in digital CS. I would say the other piece that really helped is most people and I mean I work like run a customer success organization for a company that is all about data Most of the people that we work with are not comfortable working with data, it's their first time doing it or they're making really consequential decisions, and so a lot of the job is how do you compel people to care about using data? And that's really like a change management exercise. So what I found in my career working in data science is that you really need to explain how you got to the answer like that. You know that when you're your math test gets graded and you get like bad marks for not not showing how you showing your work on how you got there.

Speaker 1:

If you can show your work and you bring everybody along, it goes a really long way to the change management and getting people to use data and, more than just using it, get curious about what more could we do, because everybody has some great idea. They just may not know exactly how to execute on it. So if they see what's possible, they see the work that you did to get there, then you know, all the time I have people come to ask you some ideas. Like somebody said hey, can we pull in our community data and then use that to ping people when questions don't get answered by one of their peers, and then how can we build that into our health score? So it's, you know, different. Three different people came with three different ideas, all relating to the same data, that all make our customers lives better.

Speaker 2:

Yeah, and that kind of stuff is lurking everywhere. You just got to kind of go look for it and think about it creatively. And I really like what you said you know about just not being able, not being afraid to jump in, because so much of kind of what we do in CS is gracefully falling on our heart a little bit not being afraid to do so, because like.

Speaker 2:

Honestly, it is those human moments that actually make a huge difference versus you know, if everything's kind of hunky dory and by the book and by the recipe or whatever, you're probably missing some great opportunities to connect, you know, with your customers organically and and it also shows that you know you're you're, you're trying to do things and and you know to improve, improve upon the experiences. It's not like we're purposely going out of our way to like send extra emails, but yeah, I mean I think there's like the.

Speaker 1:

I'm sure a lot of people have heard of the service recovery philosophy. It's basically like you know, you have, you have enough. If something is broken, you actually have an opportunity to not only fix it and do the right thing but dramatically improve the relationship. And this is like one of my favorite things. With digital CS. This is actually one of the first now that I think about it like one of the first things. Before even add digital CS as a function, one of the first things that I did at he was really use our NPS program as a way of driving those service recovery moments. So I mean, yes, we definitely care about having a high NPS score, but what I care a lot more about is finding the specific people who are struggling and then turning their moment of frustration because usually they most people as an in product survey they'll, like rage, submit a negative.

Speaker 1:

So you see the ones that are, like you know, under, like their two or three or four.

Speaker 1:

Those are people who are really struggling right now and if we can figure out exactly what they're struggling with and reach out with some help and then just offer, you know, an olive branch, say, okay, come talk to us, we truly want to help you, that often turns things around and I, and then we measure how did they respond to the next time they responded, and if we're able to close those loops live, our response rate goes, you know, more than like or sorry, our.

Speaker 1:

Our NPS for those people who responded negatively goes up, like typically people will become, you know, go from being a detractor to being a passive or promoter over time if we've done effective interventions and that's kind of like really. I mean, that's been done for a long time since NPS has been a thing. But I mean I will often submit people submit NPS on products that I use, just to see what happens afterward, and me too, majority of them. There's no follow up, there's no close to what. They're just collecting the data for data's sake, and I think that a huge missed opportunity for a digital CS or a scaled CS motion.

Speaker 2:

I was going to say exactly the same thing massive missed opportunity and NPS comes up quite a bit on the show.

Speaker 1:

I mean because most of the people love to hate NPS.

Speaker 2:

And exactly, I think for me, the two most valuable bits of NPS are what we were talking about the score, okay, fine, but the goal is in the comments. The goal is in the comments that you can then distribute internally and try to make some improvements. The real goal is when you actually respond and actually engage on the back of those responses, because, a it shows that you're listening, but, b it drives engagement down the road. It's one of those touch points that can really help secure a renewal, quite frankly, or make a customer, even if things aren't hunky-dory, they know you're listening, they know they've got a window into the organization and so, even though they may be evaluating some other solutions or whatnot, at the end that could be one of the things that makes them stick around, because, oh yeah, I mean just knowing ahead of time and just getting a lay, especially in our primary.

Speaker 1:

We have a traditional CS motion which is pretty high-touch to very high-touch, and then we have a pooled motion.

Speaker 1:

That digital is an overlay across all of these, but within the pooled accounts we're often pushing out content as you would from a digital standpoint, trying to get users to come in and say, hey, this is the thing that I care about. Or, based on our signals, here's something that we see it looks like you're struggling with or you haven't done yet that you should have done by now. And within that base, these interventions are super important because it gives people a chance to just raise their hand and say, hey, something is not quite right. It doesn't matter what the thing is, but if we can just talk to them or just even exchange email messages with them, it goes a really long way to understanding more about their context, diffusing any potential risk or frustration for that person and the account and many times often leads to an upsell because they're frustrated that they can't do something that they could do if they had one of our products that they didn't even know that we sold.

Speaker 2:

Yeah right, exactly what. On that topic, what are some of the, I guess, your favorite motions that you have in place that are either particularly effective or things that are just cool, like from a CS nerd perspective?

Speaker 1:

Yeah, one of the challenges I think on your podcast and on all such podcasts this is often discussed just the lack of data, cleanliness on contact level data. So you have all the issues that I'm sure have been talked about ad nauseam, where people put in the wrong name. They combine their names together and then all of a sudden you're saying hi lane heart, instead of just saying hi lane, or the caps was on, and so it's all.

Speaker 2:

Yeah, caps on, or they put it in all lower cases.

Speaker 1:

Obviously, everything is messed up in our systems, or I mean that's like you know. That's pretty recoverable and we have algorithms that you know, scripts that will run to try to fix that. But the other thing that is most difficult actually is see right there, with that statement, you're already above.

Speaker 2:

Above, where a lot of people are like you're fixing the casing. Yeah, totally. Because I think a lot of folks you know they'll have these, they'll have user databases or whatever, and it's just like whatever it was put in by so and so and that's just what it is. And then you know it's like a manual or an outsourced type of situation to go fix it. So that right there is actually quite interesting, because I think a lot of people struggle with that exact thing.

Speaker 1:

Yeah, I wonder if there's like a Salesforce mini app idea, or maybe this already exists and somebody should write it to us and tell us where. You just plug this thing in and it just fixes the bad contact data that's coming into your CRM.

Speaker 2:

Yeah, if you have, if you out there, if you, the listener, have something like that, like an app or something that automatically goes through and cleanses your Salesforce contact data? Comment down below.

Speaker 1:

Yeah, that will be your next guest, and definitely call me as well, because then we won't have to do all this stuff manually. But so that one of the things like that is one of the challenges that we have. That and just knowing who's still at the company, who's a decision maker at the company, how are people related to departments within the company? Because I could go on a little bit of a tangent here about the departments and the breadth of adoption. So one of the things that we care a lot about is that multiple teams, different departments, are using heap to make decisions. Reason why is that it reduces confusion within their organization, ultimately reduces cost of people using different data sets to try to make decisions, and of course it makes our platform stickier, because now you're making decisions using the data that you collected from heap and using charts and heap.

Speaker 1:

So we actually started. This is kind of like a crawl, walk, run thing. So I started off with just an app queue in our product that would just ask people when they were signing in for the first time, which department are you a part of?

Speaker 2:

What do you use?

Speaker 1:

Yeah, like what do you do and what are your goals Like? Why did you come here today and you had to keep it really short? Because we were afraid of adding undue friction in our sign up process and in fact this is actually why we ended up with kind of shallow data in the first place, because we wanted to make it very frictionless to sign up. Remember, our company is all about removing friction and we looked at OK, if you ask too many questions, people will drop off in the beginning of the flow. There's a really interesting Lenny's podcast from a few months back about someone talking about PLG and how they were actually saying it's fine to ask the questions you need to ask, because if people drop off, they weren't very high intent anyway and B2B software is the expectation. Is you're going to give up that kind of information?

Speaker 1:

Anyway back to the thing. So we collected that information just using an app queue, fed it into Salesforce using Zapier and then use that to basically say, ok, how are we doing from a breadth standpoint across accounts? Do we have people in product, in marketing, in customer success, in data and engineering all using Heap? And if not, how do we get more people across those teams using it? Or how do we get people to identify themselves?

Speaker 1:

So, then what we did is we created just basically a feedback loop where we look at we use Marketo to send emails, so we look at when we send out emails, are those emails being delivered or are they bouncing With all the turnover that you have in companies today, people stick around, for there's some different numbers out there, but it's under two years on average.

Speaker 1:

So people are leaving and we need to know are these people dormant or did they just leave the company? Oftentimes their email balance is, like you know, probably 70% accurate at saying they left the company. So that was one of the cool things is just flagging contacts that had left and then using that to flag accounts where we don't have any relationship contacts or we don't have any contacts in a certain department, and then just team up a message that goes out to those accounts through Catalyst, which is our customer success platform, to say, hey, it looks like this person left and they were in such role at your company. Did this person actually leave? If they did, who is the new person that's taking over? One of the challenges that we had was OK, we you know if you're trying to reach out to people by email, and they're no longer there obviously you're not going to get a response.

Speaker 1:

So, there's different levels to it. We just send this message to some of the top users in the account, based on who's logged in most recently, and it actually is very effective at getting those people who are top users care a lot about the platform continuing to exist at their company and you know us being able to reach out to the right people there, so usually they give us the information we're able to update things so that when we send out messages we're sending them out to the right decision makers in each department, and that has really helped us with the dormancy problem where you know, if we don't have that top level alignment, the account will over time just sort of erode because no one is administering the account.

Speaker 2:

Yeah, it's so interesting because I feel like I don't feel like I know that a lot of times we're just afraid to send those kinds of messages, you know, because we're like hey, we don't know you that well, can you help us out?

Speaker 2:

But I think that is where, whereas that can be viewed as something that is negative, I think also, on the flip side, it's a point of engagement and you're asking your most avid users to say hey, help us out, keep us up to date so that we can serve you better. I think it's all in the semantics and it's in how you message that. Going back to something that you said earlier which I thought was interesting was almost this notion of, in PLG, using survey completion like the amount of completion of a survey as almost like an engagement metric, which I think is interesting. If somebody goes through and completes five out of the 10 questions in your survey versus somebody who completes the 10 out of the 10 questions, you could almost say that, hey, this person is a little bit more engaged with your company much less the software, but maybe the company and therefore is somebody that you could use as an advocate or something like that. I thought that was very interesting and one of the side benefits of surveying perhaps.

Speaker 1:

Yeah, and I think you have to be careful. The big thing with surveys is they're so annoying. You know when it's the end of the quarter because people have some goal in their company goals to send out a survey or get a certain response rate or just a certain score. I will always see it at the end of a month just a bunch of messages piling up. You have to be really careful not to bombard people. We have a bunch of pretty sophisticated logic that keeps us from over surveying or asking too much of too much feedback without a direct benefit. We do a lot of surveying. Our product team does a lot of surveying, especially our long tail of customers to get customer interviews of people that are doing specific things in our product. Usually people are really willing to participate in those. Sometimes they'll be compensated, Sometimes it's just product people love talking to other product people and those are our users or user researchers, UX people.

Speaker 2:

Yeah, interesting. How do you coordinate that? Because one of the epic problems is like, hey, marketing wants some information and sales wants some information and CS wants some information, and product is like do you write exactly? Okay, question answer.

Speaker 1:

Yeah, I think the good thing is, if you have a small enough team or a team that is cohesive enough, you can strike that balance between someone is the human router or traffic cop to make sure that you're not inundating a specific base of people, but you also want to just leave it open and let people tell you if it's too much. So we're more laissez-faire about it than other places. I've seen where, if somebody wants to reach out to customers, we're not going to say, go send this to 1,000 users at once, but if you have a list of 100 people you want to reach out to, maybe five or 10 of them will end up responding. We've been pretty much willing to do that. We haven't seen any major repercussions.

Speaker 1:

Where we do have issues is it's not an issue, it's just a thing that happens. We have multiple different teams that are all. They all have the same goal, which is to engage our user base. That comes from sales, it comes from customer success. It comes from product, it comes from product-slash-product marketing, it comes from marketing and from our scaled adoption team. So we do have a process where we just say, hey, these are the sends that are happening and this is the relative size of those sends to make sure that we don't send two messages per day about totally different topics. Then the metrics that we look at to monitor that are really the unsubscribe rate, to make sure that we're not overlapping too many sends and then annoying people because they got three messages that didn't seem coordinated at all.

Speaker 2:

Totally, yeah, absolutely.

Speaker 1:

I had probably-. I think there should be an app to solve that problem as well, just like there probably is also, we're just not using it. Put all of your campaigns and then prioritize them smartly, so that the ones that are going to drive the highest impact will get sent first and the rest just go into a backlog Exactly like a Q kind of deal. Yeah.

Speaker 2:

Obviously, there's some folks who use different systems to send different emails too, and that exacerbates the problem because there's no communication between the two. I had a horrid experience with this kind of stuff recently. I won't mention the company, but it was like pre-sale they were very aggressive in their emails and calls to drive the close. Then post-sale, they were incredibly aggressive. I probably heard from six or seven different people like texting, calling, emailing multiple times.

Speaker 1:

Texting is pretty amazing To drive an upsell Totally.

Speaker 2:

I didn't respond to any of them and then they start sending me experience surveys and I gave it to them. I was just like this is not cool, no, Stop, because it was. Obviously it was very obvious that it was like an outsource type situation. It wasn't a coordinated outsource situation, it was like 20 different people got a lead. For hey, if you can upsell these people, it's just so stupid. Anyway, it was like the epitome of what not to do.

Speaker 1:

Yeah, it's tough because, if I think about our tech stack, we have a pretty rational tech stack. We use Marketo for the majority of our email sends, across marketing and product marketing. We use SendGrid to send transactional emails from our product. We use Catalyst to send O-Sale customer success emails. Our sales team uses Outreach to send prospecting emails and some sequences for even O-Sale customers that they're managing. Then, of course, we have Gmail. That's going back and forth with customers.

Speaker 1:

What I've found is that, even though Salesforce is far from perfect for this, we bring all the data into the activity feed in Salesforce and into our own product heap. We basically have all these touchpoints streaming into those two platforms, and then we can use those to build suppression lists. It's far from perfect, though, because you don't really get the priority of every message. You can just look at the saturation of messages per recipient or per account, but if you look at the source, you can infer what the message was about based on which system it's being sent from, but there's definitely not a one-size-fits-all thing, and I've had several different companies try to sell them, and I just don't believe it, because some of these systems are so entrenched that we're not going to get rid of them.

Speaker 2:

Yeah, totally Absolutely. That's cool, though. I like that notion of collecting everything and then throttling a little bit depending on the volume. That's super smart yeah it's definitely not perfect.

Speaker 1:

If anybody's listening to this and they're like that's BS, they're definitely not doing that. I apologize, let me know what we did.

Speaker 2:

One of the things that we spoke about previously was this notion of just standardizing metrics across departments and really trying to get on the same page, cross-departmentally, with the goals and what you're really trying to drive. Can you chat a little bit more about what that looks like at Heap and what you're driving specifically?

Speaker 1:

Yeah, we have a company value called Taste the Soup, which might be like eat your own dog food or drink your own champagne somewhere. Sure, we really try to live this every day because, since we are a product analytics company, we have lots and lots of data. We are a self-serve platform. Everybody in our company is using Heap for various things. One of the age-old challenges that we've had is just what is the definition of active usage Then what's the definition of value driving usage? Because you can have active usage without value driving usage.

Speaker 1:

It's easy if you don't know what value looks like for your customer, but if you don't know what value looks like for your user, you're going to end up inferring that they're fine when they're not, and then you're not driving some of the most important interventions. One of the things that we did a few quarters ago is just launch a cross-functional team which is spearheaded by Daniel, who leads our product analytics team. Who's amazing. Huge shout out to Daniel to get alignment on these definitions of basically our version of MalWow and Dow basically our users and daily users. Then we have a few others that drive what we infer is value driving behavior, like repeating certain actions within the platform For the longest time.

Speaker 1:

For a couple of years, we were all customer success was using our own definition, product was using a definition, our analytics team was using a different definition. We just created this cross-functional team and basically said we need to figure out what these metrics are, and then we're just going to bless these and lock these down and we're only going to use a certain set of events to calculate them, so that when you are driving interventions, we're not driving interventions to the wrong people. I guess communication is probably the number one thing. We're awash with data, but it's really just communicating on the metrics that matter, or the metrics that we're going to decide matter together. Then I think the other big thing that helped with sanitization is just putting those metrics on display in front of the entire company.

Speaker 1:

We have a system where we track all of our OKRs as a company. These are always metrics that are what we call like top-line metrics, so metrics that we just track all the time, even if they're not at a specific OKR for that quarter. That has really helped just with the visibility, because it gets everyone thinking about how can I drive those metrics? And it also gets people thinking okay, I have an idea how we could sort of rev on this metric together, bring it to the right people, or, oh wait, I was actually using a different metric to measure success of my OKR. I need to make sure it's tied back to this one.

Speaker 1:

We don't really have anyone policing it, but organically, by setting the definitions with the department leads and then making them widely available in our own platform and in our data systems, we've pretty much driven a way the behavior of people using different metrics or just random metrics all the time. That's from a product usage standpoint. I would say that actually, one of the things that we have more trouble with now that we've moved on from that challenge is our commercial data and segmentation. Everybody wants to know what segment is this customer in in terms of how we cover that account and then what motion are they in in terms of the type of servicing that they get from us? Getting that data accurate, maintaining it based on our contractual commitments and then propagating it out across our systems is an ever-present challenge.

Speaker 1:

I think, as with any data quality, it's never really going to go away, but that is the current challenge that we're focused on. If anybody has great ideas on all years, again it goes back to communication and just communicating. Who owns that piece of data? We had a whole cross-functional team for Salesforce to just say let's list out all of the top data elements that we have. We had this spreadsheet that had 500 rows. Does anyone even know what this one means anymore? If not.

Speaker 2:

Let's get rid of it.

Speaker 1:

If people do know what it means, then who owns it? If somebody owns it and it's similar to another one, let's call that person or just have a big call where it's a clearinghouse. That is the way that we've been solving it so far and it's helped us make a dent in those standard metrics. My overall advice is put the metrics in public for everyone to see, make it easy to know who to go to when something doesn't look right or when someone has questions, and then patiently deal with all of the discrepancies. To encourage people to come to the table when they have data problems instead of reinventing the wheel on their own and trying to make their own thing, because it'll save them time for that one thing they're trying to do and then it'll create 10 times more problems in a quarter from now.

Speaker 2:

That's great. Yeah, I love that advice. I think data hygiene is something that everyone struggles with. Show me somebody who doesn't struggle with data hygiene and I'll show you a liar yeah, every company, from the tiniest companies to the biggest companies.

Speaker 1:

Absolutely.

Speaker 1:

I think the other thing, too, is just taking a really and this is something that I do and my team does with our clients all the time trying to figure out what are those value driving actions or moments, and sometimes they're a specific action that you repeat over and over.

Speaker 1:

Sometimes it's a threshold of a certain number of times that a user has done a thing, or a certain number of users on an account that has done that thing. For us, it's like saving reports and pinning them to dashboards and then sharing those dashboards with other people to drive that virality. What I find is that most of the teams that we talk to don't know what those secondary metrics are that drive the Mao-Wao Dow type metrics. And figuring those out is the biggest unlock for digital customer success, because it allows you to intervene at those moments that matter or when people are on one side or the other of that threshold. You're not telling them something that's really pedantic that they probably don't care about or they're already past it, and so that you're not going way over their head with the 103 course when they need the 101 level.

Speaker 2:

Yeah, exactly yeah. All this stuff is reminding me of a conversation I had several weeks ago with Dan Ennis, who is fairly well known and CS circles for being. Yeah, one of the things that he does really well within his organization is using usage data to figure out what persona somebody is likely to be within a customer, which I think is fascinating to do those kinds of things as well. But, yeah, it's really awesome to hear that is next level.

Speaker 1:

If someone is doing that, they're probably in the top 10 or 20 percent of sophistication, which is amazing, but this is one of my personal principles. It doesn't have to be perfect. If you're listening to this and you're like holy cow, how am I going to figure out, infer people's persona based on their behavior? Just start with something. Just try to find that one active usage metric that is not just like they logged into the platform and then just run a test around that and eventually you'll figure it out.

Speaker 2:

Totally, absolutely. Do it, see if it works. If it doesn't, go back and do it again, figure something else out.

Speaker 1:

Yeah, it's just those learning loops. That's what I think. In order to be successful in digital CS, you have to have people who are just innately super curious and willing to try and fail a lot. You'll find those breakthroughs, but they're always diamonds in the rough.

Speaker 2:

I think so too. Well, cool, as we start to round out our Convo because we're getting towards the top of the hour here and I want to be respectful of your time I'd love for you to give us a quick download of what's in your content diet. What do you pay attention to on a regular basis?

Speaker 1:

Yeah, I mentioned it earlier. Of course, I listened to your podcast. There are a bunch of other good CS podcasts out there, but I also really like to expand beyond CS and really think about what is the persona of people that we are serving, which are largely product people or digital builders. Lenny's podcast is one that I mentioned earlier. That's amazing for that, because he has a lot of guests who are just top practitioners in their field and they're often talking about product-led growth or how do you make the product just easier to use.

Speaker 1:

At the end of the day, that's really the nexus of digital CS. It's like how do you make the product and the people work together and get the people to do the things that your product is intended to do? There are a bunch of good episodes that I could share on that topic and just also goes into aligning active usage metrics and stuff I also tend to like. My wife always gives me a hard time because I'm always reading what she calls business self-help books. There's one that I read recently which is I have it sitting here on my desk of Scaling People by Claire Hughes Johnson. She was the COO of Stripe.

Speaker 1:

I'm sure many people have read that Fantastic book for anybody who is leading a large organization or relatively small organization, because she gives very digestible, very specific tips and frameworks. There's a great book of frameworks Then, one that I read recently actually listen to it while I was running on the audiobook. It's called Nudge. It's about behavioral psychology. That is really interesting just in terms of what motivates people to take certain actions. And also when you think about digital CS.

Speaker 1:

What we're doing all day is trying to motivate people to care about a thing or to nudge them into doing something and connecting with what they see as valuable and what we offer. Then the last one, which is definitely a personal self-help book, is Getting Things Done, which is a pretty old book. Some of the stuff in the book is outdated now because it's all paper process, but there's an app called OmniFocus that is a task management app For anybody who has a lot of things going on. I would definitely recommend that one.

Speaker 2:

Cool, I love it. Amazing little tidbits. Any folks that you would want to give a shout out to Digital?

Speaker 1:

CS related? Yeah, a couple. Recently, somebody that I've been working a lot with is a co-founder of an app called Athenaai, mike Molina and his team, jared and Sid and a bunch of other people over there. What they're doing is basically helping us scale Slack. We're introducing customer Slack channels to many of our customers and they help with bridging the. When people ask questions, how do we make sure those questions get answered in a timely way that doesn't overwhelm people from being in a bunch of Slack channels, and then how can we use that for customer marketing as well? It's definitely just an amazing team, but also really useful app for the next iteration and getting out of just email as the only channel that we email or in app that we use to communicate with people without being super invasive and trying to send people text messages, because I think that's one step too far. Yeah, the story that you told is like wow.

Speaker 1:

Mike is only one great person to reach out to and to follow. They put out lots of great content. This in the vein of scaled CS as well.

Speaker 1:

I don't know if anybody has ever mentioned Mark Costaglow, who's the CRO at Catalyst. He runs all of their go-to-market functions, including Postsale. He has a framework that he shared with me a couple of times recently, actually called Moments of Impact, and it's basically how do you get to these specific moments of impact that are going to drive, like the customer say, wow, this is valuable and I love this product. The reason why I really love that framework is because it relates really well to just reaching the next stair step with customers, and it can be applied digitally or through a higher touch motion. Then, actually, wes is the person who runs Scaled CS at Catalyst.

Speaker 1:

Wes has been doing a lot of that orchestration of where the rubber hits the road. How do you help the CSMs as well as the long tail with reaching those moments of impact without being annoying and just sending the same webinar content over and over. I think they both work really well together in doing a pretty job of deploying that content. Of course, one of the things I love using their product is that they're also tasting their own soup in making the product better by using it for digital CS, that's amazing, awesome show.

Speaker 1:

Last shout out is a buddy of mine, todd Bustler, who he and Steven Ruff started a company called Champify which helps you keep track of contacts as they move on. This has been a huge challenge for us and part of that motion that I mentioned earlier, where you have people who are leaving, we send alerts to the CSMs and say, hey, these people are leaving, let's figure out who the new economic buyer is on this account. We can do that at scale. We also turn around and use that for sales as well, because if somebody was a really happy customer and they moved to a new company, we can sell to them there. Todd puts out a lot of great content just in terms of little tidbits on LinkedIn that really are catered a lot towards sales, which is their main audience, but much of it is relevant to CS as well just how to get people's attention.

Speaker 2:

Yeah, I had a conversation with someone recently not on the podcast, but about this notion of CSQLs and how a CS qualified lead doesn't necessarily need to come from an account that you have. It can come from someone who you used to work with, at an account that has moved on or whatever. I think there's a lot of value in tracking those people and where they go within the ecosystem of potential clients.

Speaker 1:

Yeah, we typically find the close rate. On those accounts the time to close is three or four times faster than it is, which is somebody who's never talked to us or used our platform before. From a customer success standpoint, they get it. They struggle with some of these challenges before, so their onboarding is always much, much smoother than somebody who we haven't worked with. We're always happy to have those repeat customers and users.

Speaker 2:

Exactly, yeah, cool. Well, lane, I've really enjoyed our conversation. It's been great spending time with you again. Good to have you on the show. Where can people find you, engage with you and reach out to you?

Speaker 1:

Yeah, I'm on LinkedIn. You can definitely find me on LinkedIn Lane, hart, l-a-n-e, h-a-r-t, and on the heap community, which is communityheapio, or you can just reach me by email Lane at heapio Pretty easy to get in touch with, easy. I always try to respond to folks on LinkedIn. I'm truly curious to connect with people who are doing things even that are totally different or adjacent to the space. Definitely don't hesitate to reach out. One of the things I'll often do with folks who reach out is talk about health score. How can you build an actionable health score? You can find some stuff on our heap community that I published there about that as well, that's cool.

Speaker 2:

Okay, we'll have to hit that the next time you're on the show.

Speaker 1:

All right, we'll love to come back in the new year.

Speaker 2:

Sounds good. Thanks for the time.

Speaker 1:

Yeah, thanks so much, Alex. Have a good one.

Speaker 2:

Thank you for joining me for this episode of the Digital Customer Success Podcast. If you like what we're doing, consider leaving us a review on your podcast platform of choice. It really helps us to grow and to provide value to a broader audience. You can view the Digital Customer Success Definition Word Map and get more details about the show at digitalcustomersuccesscom. My name is Alex Turgovich. Thanks again for joining and we'll see you next time.