The Power of Hyper-Personalized Content for Customer Success with Nik Mijic of Matik | Episode 043

Nik Mijic, co-founder of Matik comes to us this week with not only a fascinating back-story, but some great CS-related content as we discuss a wide variety of very timely and important topics. 

In this episode, we talk about:

• How Matik automates the creation of content with personalized data, primarily for CS and Sales
• The current state of the ‘digital business review’
• A good understanding of your data is needed for a quality DBR
• Sending out one-pagers based on usage milestones or monthly project status updates - automagically
• A lot of people are scared of negative data, but using it to highlight customer improvement opportunities is key
• The importance of benchmarking cohorts of customers to help them grow and act on the adoption of the product
• Keeping a library of common customer objectives and content/measurements to help them along that path
• Moving beyond rules-based automations in favor of GenAI improvements of the inputs that would normally feed your automations to make them even better.
• Savvy sales teams are taking post-sale data and aggregating business value cases out of it to help set expectations
• Nobody’s data is perfect - don’t let that keep you from getting something in place
• Feedback loops are very important in Digital CS to make sure you are constantly monitoring what is working and what is not working
• The Kirkpatrick model, typically used in L&D can also be used in other ways to measure the short and long term efficacy of your programs and content

Enjoy! I know I sure did...

Nik's LinkedIn: https://www.linkedin.com/in/nikola-mijic-9012201b/
Matik: https://www.matik.io/

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Transcript

Speaker 1: 0:03

This is where we don't want them to spend three hours putting the deck together for a half hour meeting. Right, correct?

Speaker 2: 0:08

Correct Right. Well, even better. Yet you don't need to have a meeting, right Like be, proactive. Right, talk about being proactive. What if you were able to go and I think this is where the digital piece comes in what if you were able to go and send that out on a set kid, and even if you don't have a meeting? A lot of people are scared to show bad data, but it actually can be a very effective tool in increasing adoption and getting your customers to realize the value that they've purchased your product or service.

Speaker 1: 0:35

And, once again, welcome to the digital customer success podcast with me, alex Chokovic, 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. Greetings and welcome to episode 43 of the digital CS podcast, so happy to have you back. As always.

Speaker 1: 1:16

For those of you in the States, we are at the beginning of spring break week, so that means probably one of several scenarios Either you took some time off and you're going on a trip, going camping who knows what you're doing or you're working from home with kiddos in the background, either way. So no matter where you are, I'm so glad you joined us today and I say us because I'm joined today by Nick Meach, who's the co-founder of Matic. If you're not familiar with Matic, it's a super cool platform form. You'll learn a little bit about it in this episode, but they specialize in populating content dynamically with data Just really super cool stuff. That is very, very CS related and so obviously we talk about that and some of those technologies. We talk about the importance of data and benchmarking and how to use that with customers, feedback loops and automations, gen, ai. We just kind of touch on a wide variety of things and I think you'll find some really useful tidbits in this particular episode with Nick Meach. Nick, it is Nick, right, it's not Nicola.

Speaker 2: 2:41

Yeah, I go by Nick.

Speaker 1: 2:43

You go by Nick, Do you ever? Who calls you Nicola?

Speaker 2: 2:48

You know my mom.

Speaker 1: 2:48

Your parents.

Speaker 2: 2:50

Yeah, my parents too, my siblings. But when I moved to the US, Nick was easier for people to pronounce and so we ended up just going down that path and it's kind of stuck. So Nick has been kind of what I've gone by over the past few years.

Speaker 1: 3:06

Yeah, for sure. And when we talked like initially, I think we both kind of shared our kind of stories about, you know, moving to the US, Like I moved to the US when I was 10, Austrian born, and you had kind of a similar journey, right.

Speaker 2: 3:24

Yeah, so I was born originally in Bosnia, so Sierra Igua, Bosnia. Most of my family's from that area. And when the war happened, the Yugoslavian war, we fled to Hungary. From Hungary we went to Germany, tried to stay in Germany, but we couldn't get our papers and citizenship. So because there were just so many refugees that were coming up from the Yugoslavian war and ended up kind of applying all over the world Canada, US, Australia got accepted to the US and my parents decided to come, come out here. So we moved here when I was eight years old and I was in Utah for a really long time, but I've been in the Bay Area now for about 11 years.

Speaker 1: 4:05

That's amazing. It's such a cool story. I mean I love it when there's amazing weird circuitous stories into you know just adulthood, because I mean there's few people that have a straight shot or I guess, and I think, similarly to CS, like there's few people who have cuts into CS as well, because it hasn't been around for that long, totally, totally. Yeah Well, I jumped right into it. But welcome to the podcast. It's super awesome to have you and obviously we're talking because of this wonderful thing you've built and are building with Madagascar. I'd love to kind of get a little bit of, I guess, an origin story of what led you into building this company and how your experiences kind of led you to want to do that and just Give us a sense for for what it is you're trying to solve.

Speaker 1: 5:13

I don't want I hate putting words it's not as, when it comes to, like you know, this is what you do, right.

Speaker 2: 5:21

Yeah, I guess the elevator fish kind of at a high level. Just to starting there, you know Maddox. What we do at Maddox is we we automate the creation of content within PowerPoint, google slider, email with hyper personalized Data in the forms of charts, tables, text images that we insert into that content on your behalf. So we work a lot with customer success and sales teams across companies like greenhouse is sauna glass door To automate things like business reviews, renewal decks, roi decks, automated one pagers that gets sent out via emails, anything that incorporates data where you're trying to highlight value and when how the kind of idea originated is. Way back when I worked for a startup that was in the customer success space, I was a CS platform very similar to Gainside or catalyst or any of those tools that that CS teams use.

Speaker 2: 6:18

And you know one of the things when I was at the startup, our customers were always asking us hey, we do these things, we do these decks and these ROI calculators and these business reviews. They're really, really time-consuming but they're Extremely valuable to share with our customers. And so when I joined LinkedIn After the startup, I joined a team called insights that basically we built internal tools and narratives for our customer success and sales teams, and so typically the workflow that we saw was you'd have a template right in PowerPoint, google slide stored somewhere for all the different touch points, whether it's a business review or a renewal deck, whatever it may be, and you as a rep let's say you had a business review with a client tomorrow You'd go there, you make a copy of that template that had your design, everything, and then there would be instructions that would say Alex, go to Salesforce to get this metric.

Speaker 1: 7:08

Go to Tablo, take this screen use this go to this report and go to the yeah, yeah it's into Excel.

Speaker 2: 7:14

Do this math and we had an internal tool that already existed at LinkedIn that kind of automated that process and I had the chance to rebuild that and it really kind of got me thinking hey, I think there's a huge opportunity for this one, such such Huge impact at LinkedIn, not just from a productivity standpoint, but this whole notion of when you're sharing this hyper personalized, data-driven content with your customers. That usually led to better business outcomes, right like adoption.

Speaker 2: 7:43

Upsells and so forth.

Speaker 2: 7:44

So I thought, hey, if this works for a LinkedIn, there's got to be other companies that have very similar problem, and so I've always been on the support side, meaning ops. I was always the data person that you would go to to request data, and I met my co-founder through a mutual friend. He was an early engineer at box and I was like, hey, I've got this idea. I'm not entirely sure if I'm ready to quite leave LinkedIn, but I'd love to kind of noodle up on this with you and see if it makes sense. And sure enough, him and I really hit it off and the feedback we got from our network was really positive.

Speaker 2: 8:16

So we took the leap of faith and started the company back in 2019 and fast forward to today. We're back by some of the top tier BCs and men, love ventures and treason Horowitz. We've raised 23 million today and again work with a lot of companies like a sauna, a glass door, auto desk and so forth, to help their teams automate the creation of this content with hyper personalized. You know, tables, charts, images, text you name it.

Speaker 1: 8:46

That's so cool, it's, it's awesome because I mean, obviously it fits perfectly into the podcast which is, you know, digital customer success and and I think In a lot of ways, you know, I feel like this is one of those Kind of ideal maturity steps in a digital program is to to be able to create kind of personalized content.

Speaker 1: 9:14

That's that's, you know, at his doorstep, at the right persona at the right time, and those kinds of things. And I think the digital business review is is one thing that has been kind of elusive for for a lot of folks and and I think, still is in the mind of a lot of people, and so I love the idea that that mattock is kind of at the at the front edge of Really trying to solve for that, you know. But going back to the digital CS theme, one one thing that I do like to ask all of my guests is is the standard question of you know what's your elevator pitch of digital CS? Because everybody comes with, you know, to the show with a slightly different flavor, slightly different background. There is no kind of one size fits all definition. So I'd love to kind of get your stuff of what you would tell somebody that digital CS is.

Speaker 2: 10:05

Yeah, I mean, I think at a high level.

Speaker 2: 10:07

Digital CS is just kind of the ability to automate certain functions right there. Typical CSM doesn't mean that we're going to totally eradicate the need for traditional CSM and it will automate some of these processes. That will help alleviate the time for the CSM to do more strategic work right, and I think that's a really important thing to do is to really get the idea that we're going to do more strategic work right. And I think what biggest misconception misconceptions that I've heard and speaking leaders and our customers around this concept of digital customer success is that they think it's only for their long tail of their business right.

Speaker 2: 10:41

It's like hey, we're only going to do accounts that are not touched by CSM, when in reality a digital CS program can probably benefit not just your long tail but can also benefit your enterprise CSM's, or enterprise accounts that do have a CSM, to hopefully give them more time again to do more strategic things that will hopefully lead to better business outcomes. So at a high level, that's that's kind of my thought on on the, on the concept.

Speaker 1: 11:09

Yeah, I love that. I Really love that and and I you know the the again the concept of a digital business review. What do you think the current state of the dbr is when you talk to customers and all that kind of stuff?

Speaker 2: 11:27

Yeah, that's the current situation, I think, a step back. I think a business review is just one touch point, right? I think people who do this really really well don't focus on a singular use case and Take a more of a holistic approach. We're looking at all the different touch points in the customer lifecycle, right, whether it's onboarding, whether it's a business review, whether it's a renewal deck, whether it's, you know, adoption, and they're trying to tie some sort of content to those touch points to be able to help the customer do some sort of action or realize some sort of value that your product or service is rendered.

Speaker 2: 12:05

And so, in terms of speaking like specifically around the business review, you know, I think today it's obviously really widely adopted, right. It's its best practice to be able to go and do those. I think what we see typically With companies that we work with is that there is a resource constraint, right, with a typical, you know, customer success where hey Book of businesses are doubling right, given the macroeconomic climate, and, as a result, we want our reps to do a lot of these business reviews or renewal decks or adoption reviews, but they don't have the time because it's so time consuming to put them together, and so this is where we don't want them to spend three hours putting the deck together for a half-hour meeting, right?

Speaker 2: 12:47

Even better. Yet you don't need to have a meeting right like be pro right. Talk about being proactive. What if you were able to go and I think this is where the digital piece comes in what if you were able to go and send that out on a set kid, and even if you don't have a meeting?

Speaker 1: 13:01

to hopefully then.

Speaker 2: 13:02

Get a meeting where you can talk about more strategic things that they're trying to move the needle on. So I think we're still kind of in the early stages of, you know, mainstream adoption and I think some of the things that I've seen is one you really have to have a good understanding of your data. To a certain extent, I think that's always a big thing is because it's digital, it's it's you want to ensure that somebody's getting this, getting the right message, just getting the right data at the right time right and you want to trust what you have in the data.

Speaker 2: 13:36

Exactly, and so I think this whole notion of smart automation, where you know you can add that rule-based logic to indicate hey, I know that if this is zero, we shouldn't be sending this out at all, right, hey, so right, right, hey, you don't have this product, we shouldn't be sending out this one page or at all, because they're not going to be using it. So I think there is some of that stuff that people are trying to figure out and map out that entire process and you know, this is where we hopefully come in and can help with that Making sure that you feel comfortable and confident sending out this content to your customers without having too much worry.

Speaker 1: 14:11

What my brain is going all over the place as you're talking, because this is super exciting. But you know, one of the things that I've talked about a lot recently is the the crazy amount of variability that exists in digital CS, meaning that you've got, you know, multiple products to support you've got, you know, internal folks.

Speaker 1: 14:34

You've got external motions You've got, you know, collaboration with different situations You've got, you know, collaboration with different situations. You've got different tools. I mean, the variables are insane to where if you were to, like you know, pick up a strategy that worked in one organization and plunk it down on another one, it just it probably wouldn't work, just because the variables aren't the same. I think goes without saying. But you know what. What comes to mind as you're talking about this is, you know, persona specific use cases where you're sending different things to different personas. Also, the use cases around, like you know, sending positive things is great, but also like letting an executive know that, hey, you're off track here and this is what you need to do to course correct. I'm just throwing shit out here. Sorry, pardon my French, but I'm throwing stuff out here because I would love to get a sense from you of what those use cases are beyond, just like the business review of how people are using cool ways and innovative ways that I may be missing.

Speaker 2: 15:48

I mean that example of like you know, usage is a directional based off of implementation, or how you get started with the product, right. And so I think in the onboarding phase typically, you know, there's probably certain milestones of like, hey, you've got this setup, boolean fields and you've got this setup yesterday, no, right. And you know, I think this is a great where where you can send out a one pager to not just the people that are tactically implementing your solution, but also including the decision makers and the leadership team on where the implementation is. So being able to send out a monthly review of where, if your product is very complex and there's a huge onboarding process, to be able to say, hey, here's where we're on track, here's where we're not, and everybody's fully aware. So like kind of automating, like a project tracker of the onboarding process, and your most companies have that codified at this point. Right, you're scaling and growing you can't be doing ad hoc.

Speaker 2: 16:47

You have to have some sort of a playbook. So being able to send a one pager or an email around, that is simple use case that I think I'll allow you to do that. I think the other is this what we call like an adoption monthly newsletter, where it doesn't just give you usage data of, like how your team is using your product or service, but being also being also able to then translate into ROI. So in our case, you know time savings, productivity gain is a huge ROI component of our solution. So us being able to send a here is the number of presentations your team has generated or emails that they've sent out with data driven content. Here's what it would have taken prematic, here's what it is now with magic, and this is the time savings and the ROI that we've been able to deliver. So being able to send that out on a monthly basis with recommendations is a great way to not only just throw data at your project You're probably your customer for the sake of showcasing data but translating that data to recommendations that they can act upon, and the hope is you are getting in front of it, even if it's bad, even if it doesn't show great results.

Speaker 2: 17:53

If you do it early on, you know. Hopefully at that point it'll cause your customer to be like hey Nick, what's going on, usage is not what I expected, or ROI is not there, let's jump on a call. It's easier to do that in month three versus month 11, month prior to the renewal, and so I do agree with you. I think a lot of people are scared to show bad data, but it actually can be a very effective tool and increasing adoption and getting your customers to realize the value that they've purchased your product or service in.

Speaker 1: 18:24

Yeah. And also showing where you stack up against other customers. And simulcs, yeah. Benchmarking data Like, hey, this is where you're doing great compared to your peers and this is how you're where you're not doing great compared to your super powerful, because it turns you into a consultant. You know like you're turning to just not just a software vendor, but then you become a consulting arm of the company.

Speaker 2: 18:50

Totally. I think some of our best customers, I think the people who are doing this extremely well in terms of leveraging data are people who are benchmarking Right and I think, there's so many ways. We've written a lot of content about this on our blog in which you can visualize benchmark benchmarks right.

Speaker 2: 19:07

It can be a cohort of customers that look like you. It could be time based even to say hey, this is what you were, this is your results last year compared to this year, quarter of a quarter. That's technically a benchmark as well, but I think the more context you can provide in the data, I think the better it has to leading your customer to act on it right, Versus just being like, cool, I generated X amount or I logged in this many times. I think that's that's not good enough anymore. You have to be able to rely back to benchmarks. And then the other thing, too, is being able to tie it back to the goals and objectives of why they purchased your product or service. Right, Like everything that you share, post purchase should tie it back to why they purchased your product to begin with and hopefully over time. You know you have a library of objectives that are most common across your customer base.

Speaker 2: 19:58

I know that some companies may not be able to do that, but you know in order to really scale you're going to have to try to come up with some sort of a library and then you can then, just similar to the personas, you can then start creating content that's tied to those business objectives that say hey, alex, for this reason. So here are the metrics that we associate with that objective to help them realize that value, and that's what we're going to be including in our ongoing content that we generate for Alex right.

Speaker 1: 20:28

Are there? Where's this all going, like you know? I mean, obviously there's this whole generative AI piece that's lingering in the corner and coming into play, but you know, it's not completely like we can't just plug it in and use it. It still requires kind of human effort. But, like what, you know what? What are you and the team talking about in terms of, okay, you know, we can populate these things and we can provide contextual, you know relevance, which in itself is is a big leap forward. But but what are you guys talking about?

Speaker 2: 21:06

I think one of the things that really excites us as an organization and the feedback that we've gotten right is you know, we've typically had what I've called smart automation.

Speaker 2: 21:15

Like the intelligence layer within Matic allows you to do rule based logic that says, hey, if this happens in the data or you know, delete this slide or add this chart instead, right, to help you, you know, get to close to 100% automation as possible, right?

Speaker 2: 21:32

I think where I think the generative AI can kind of come in, especially when it comes to our space, is taking a step further and really covering the edge cases.

Speaker 2: 21:40

And so what I mean by that is we just had an AI summit back in September where we had folks from open AI and others join and talk about AI within the CS motion.

Speaker 2: 21:53

We talked about what we launched called automated insights, where we can not only populate, let's say, a chart on a slide or a table on a slide, but scan the data that we're sending to that chart and give you the three key takeaways that summarize the trend.

Speaker 2: 22:08

So, for example, if you have, like, a number of presentations generated over time that we share with our customers, it can actually look at that data, analyze and say here's a top template that was being used, here's the percent growth or decline. So that way you're not doing the heavy lifting, not just putting the data into the presentation, but Matic is now also analyzing that data and giving the key takeaways in the exact summary that you can then share and alter that you go and share with your customers. So I'm really excited about that last mile piece of not just being able to create the content but also taking a step further and covering some of those edge cases that you can't do with rule-based logic. That really has to happen on the fly. I think AI has a really good possibility of helping us solve that problem.

Speaker 1: 22:56

Yeah, for sure, because, like you pointed out earlier, like a piece of data is great, but it doesn't mean anything unless you tie some insights to it and some meaning to it. So that's super cool and an awesome use of AI. I know you work with a lot of sales teams as well. Obviously, I think the use case is very different from a pre-sale to a post-sale perspective. I was curious just to get your sense on what that looks like and how you've worked with your customers to make sure it gets adopted in both worlds equally. Is there internal thing, use cases and things like that as well?

Speaker 2: 23:46

Yeah, typically our primary persona has been customer success, followed by sales. We have gone a huge internal poll to be like hey, our FPNA team puts this content together for internally every single month and it's a huge pain to put together.

Speaker 2: 24:00

We haven't focused on energy there, just given the demand on the externally facing content that sales and customer success put together. For sales in particular, some of the common use cases that we see is like pricing proposals, roi calculators. It's more sumptive base where you put together a business case that's based on assumptions that you would put in a calculator that says, hey, here's the ROI that you're going to get from our service, alex or product over the next 12 months if you decide to purchase our product. We see a lot of those use cases. As well as going back to benchmarking, one of the things that I think really savvy sales organizations have done is taking the aggregated customer usage of their customer base and then being able to translate that over on the pre-sale side to say, hey, look, a customer that looks like you, meaning your industry, your size, whatever it may be here on average the results that they get with our product or service.

Speaker 2: 25:02

So it's being able to illustrate and, like I said, I think you have to have data in order to do that. We work a lot with mid-market enterprise customers, so they've been around for a while and they're able to go and aggregate that information and then include that within their pitch deck, for example, to hopefully get someone to cross the line.

Speaker 1: 25:21

Yeah, we talked a little bit about data, the fact that a lot of customers struggle with data. A lot of everyone struggles with data and you got to have some clean data to be able to feed some of the stuff. But what are some of the other things where you would look at a prospect and go you're ready, you're not ready? What are the stumbling blocks that you try to advise customers on?

Speaker 2: 25:50

To be clear, I think no one's data is perfect. You've probably worked at a lot of companies I've worked at a few as well and there's not one company that I have worked for where the data is perfect or it doesn't have issues. I think that's just the name of the game.

Speaker 1: 26:06

Or there's too much of it.

Speaker 2: 26:08

Yeah, too much of it.

Speaker 1: 26:09

Also, think about it CRM a lot of it is naturally inputted data so there's going to be a lot of discrepancies when it comes to that.

Speaker 2: 26:17

So I don't think the state of your data needs to be perfectly clean to get started, especially if you do have rule-based logic that can prevent, to make sure that they're not going to get something that they should in a customer or prospect.

Speaker 1: 26:32

He's not going to get something that they shouldn't.

Speaker 2: 26:34

I think another thing that we see quite a bit in terms of readiness is people think that they need to have a perfect template or use case to begin with, and I think one of the things that we tell our prospects and our customers is content is similar to building software. It's not like you'll come up with. Let's say, you're a leader, you put together a business review template for your team. Right Six to 12 months from now may look different, because they use it. They get feedback. Hey, alex, slides three and four are great, but you know what? This isn't really resonating as much. I've combined it into one slide and it's been amazing.

Speaker 2: 27:11

Or hey, instead of talking about ROI this way, I've talked about it this way and this is resonated, and so part of it too, is you got to get something out the door to get feedback and there needs to be feedback loops to continue to iterate on that content. Because your product is evolving, your process may be evolving, your content also needs to be evolving. And going back to the software building software analogy, when your team ships product, it's not like they ship and say, hey, we're done, we're not going to touch it anymore. People start using it, they get feedback and then they start making enhancements and iterating on it.

Speaker 2: 27:45

So I think, it's also another misconception that you have to have everything or boiling the ocean. You got to get started somewhere, start with a few use cases and then build on top of that. And typically it's a business review that people start with, then they go to a one pager, then they go to like an adoption review, then they do a benchmarking report, a renewal deck, so you don't have to have all of it in place. And this is where the AI is also can be extremely impactful, right, like we have out of the box templates where you give us your website and we will actually generate a best practice business with your branding and your. If you don't have those resources, your branding and some of the metrics that we've gotten from your website that we think are gonna be applicable to you as a starting point, right? So I think AI can definitely help close that gap as well.

Speaker 1: 28:36

Yeah, I mean, the number one question that I get you know from folks is where do I start? And I give them your answer, which is you start, have you start somewhere, you. And then you build upon it and you iterate it and you know, if you have one dataset that's super clean and it solves an issue you know like, don't hesitate to send that email or to get that thing out, just ship it.

Speaker 2: 29:05

I had a mentor of mine who gave me some early on in my career, gave me some really, really great advice and said, you know, don't let perfection be the enemy of progress. And I think that's so true in a situation where I think we are so enamored with being perfect. I think something that is really perfect, when in reality that's really limiting the progress that we have as an organization.

Speaker 1: 29:28

Yeah, and when it comes to digital CS, a lot of folks think that it's this black box like you either have it or you don't have it, which is interesting, you know to think about. But it's totally not the case. It's like you have it by building upon, you know the things that you implement and growing it over time and getting more sophisticated over time, and you know working your way into a maturity model. You don't start at level four or five of a maturity level. You start at level one or two, depending on what you have.

Speaker 2: 29:58

Yeah, yeah, I think. One other thing to add to that, as you were saying, that is, I think, the notion of feedback loops. I think is really important in digital CS, because you usually have a small group of individuals that are setting up these programs holistically for your organization and they might be on the front lines. They might not be on the front lines and making sure that you're constantly having a health check on top of your programs to be like, hey, are there changes that we need to make? How do we know what changes we need to make? Where are we getting that feedback? What's qualitative, what's quantitative? I think is hugely important to make sure that you have long-term success and not just short-term success with your program.

Speaker 1: 30:42

Yeah, and I think it goes beyond just the survey. It's like actually exchanging mouth words sometimes. You know, one of the things that I've taken from, I guess, a former and current professional life in learning and development is the Kirkpatrick model, which is basically how you evaluate the effectiveness of a piece of training content. But I also I think it's wildly applicable for automations in general or just really anything agile related, where you have these various ways of measuring efficacy of something that you've implemented, whether it's like immediate impact of thumbs up, thumbs down or the long-term impact of how has this affected your business in a positive or negative way. It's interesting to think about.

Speaker 2: 31:33

And I would argue too that I think early on you're probably going to be more reliant upon qualitative, subjective feedback, like the conversations that you have with your customers one off right, or maybe some CSMs that get their input.

Speaker 2: 31:47

And then over time as the program becomes more and more established, hopefully those feedback loops are more data-driven and you can see it in the data and I think a lot of people want to start with that ladder when in reality, you've got to start with the former first in order to get to the ladder right, yeah, yeah, you really do.

Speaker 1: 32:05

You really do. That's awesome. What's in your content diet? What are you paying attention to? What do you feed your brain when you're not deeply entrenched in medic?

Speaker 2: 32:22

With content in terms of business or outside of work anything, anything yeah.

Speaker 2: 32:30

You know I do. Well, I'm a big soccer fan, so I do, I do. I do wash a lot of soccer to kind of de-stress from, from the work life. When it comes to work, I do think there's some, especially when it comes to CS. I think there's some great thought leadership out there that I'm always you know.

Speaker 2: 32:50

I think Nick met it as a fantastic job at King's site. I think the folks at Catalyst as well do an amazing job. I think Vitaly produces some really great content, plan Hat as well, and I think that's one of the things that I've been, you know, being in CS like I remember when I was at the CS startup, what now over eight, nine years ago, such an tech in CS was so early on and they were kind of building these foundational blocks for thought leadership, and just to see how many thought leaders there are now and the exchange of ideas across these different groups, I think it's been fantastic. So I definitely try to stay up to date with all of the major CS players out there and, you know, pay attention to what they have to say.

Speaker 1: 33:36

Yeah, well, you gave a couple of shout outs already Nick Metta and the bunch but are there any specific folks that you feel are doing really great work in digital? In terms of companies, particular, yeah, or companies or individuals that are building cool programs, whatever that looks like.

Speaker 2: 33:57

Yeah, we definitely have some great customers. I think the folks at Greenhouse have done a fantastic job. We work with them, we publish a case study where they've done a really good job at incorporating data into their content, but without just the sake of data, but really trying to tie it to objectives of their customers and tying it back to value and ROI. And just to see how much they've done has been amazing.

Speaker 1: 34:24

I think they have some of the best templates in the market right now, and what they've been able to audit yeah, and somebody else mentioned them as well as an outstanding contributor, and I forget who was which episode it was, but yeah, that's good stuff. Look, I've really really appreciated your time and your insight and I love what you guys are doing because I think it's so needed, especially right now where the need to prove you know, efficacy and to drive outcomes within your customers is more needed than ever before. So it's awesome to have that insight and I appreciate the time. Where can people find you engage with you, any parting words, any webinars coming up that you want to promote, any kind of like? I know you're going to have some paternity leave coming up, so congratulations on that, but yeah, it is like end of hot ones if you watch that show Totally To promote or just say hi, or where you can engage.

Speaker 2: 35:33

Totally, I mean, being a former LinkedIner, always feel free to reach out to me on LinkedIn. Try to be very active on the platform. If you want to learn more obviously about our product or solution or what we do. Feel free to go to our website, mattockio. Feel free to fill out a demo request form and our team can kind of give you an overview of our solution and the problems that we're trying to solve for so those are probably the two best mediums to go through.

Speaker 1: 36:01

Amazing, cool. Well, again, I appreciated the time. Thanks for giving us your knowledge.

Speaker 2: 36:07

Awesome. Thank you for having me. I actually enjoyed the talk.

Speaker 1: 36:10

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 Turkovich. Thanks again for joining and we'll see you next time.