The Revenue Engine

How to Use Data to Scale the Revenue Engine with Nick Bonfiglio, CEO of Syncari

June 28, 2021
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The Revenue Engine

Each week, Revenue Operations expert Rosalyn Santa Elena shines the spotlight on founders, CEOs, and Revenue Leaders from hyper-growth companies and dives deep into the strategies they implement to drive growth and share their learnings. Rosalyn brings you inspirational stories from revenue generators, innovators and disruptors, as well as Revenue Leaders in sales, marketing, and operations.

As a two time founder and CEO, Nick Bonfiglio knows what it takes to build a company.

So what are the lessons learned? Nick shares three things that are important -

  1. Build the right team for the stage you are in
  2. Build a great product that solves a real problem
  3. Make sure you have an initial TAM and a path to TAM expansion that will help you build a big business  

Then he says that “The rest is all about trying to enjoy the journey, with minimal stress, while riding the line between confident and paranoid”.

In this episode of The Revenue Engine podcast, Rosalyn and Nick also discuss the idea behind Syncari, the exponential growing need for data, and best practices to approach your data strategy.

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Thanks to Sales IQ Global for powering the Revenue Engine

Nick Bonfiglio
For more than 25 years, I’ve been seeing problems and building products to solve them. Currently I’m the CEO and Founder of Syncari, where we’re helping revenue teams solve costly data inconsistencies in their CRM and other platforms, through modern multidirectional synchronizat

Rosalyn Santa Elena: Welcome to the revenue engine podcast. I'm your host, Rosalyn Santa Elena. And I am thrilled to bring you the most inspirational stories from revenue, generators, innovators, and disruptors revenue leaders in sales, in marketing. And of course in operations. Together, we will unpack everything that optimizes and powers that the revenue engine are. You ready? Let's get to it

As a two time founder and CEO, Nick Bonfiglio knows what it takes to build a company. So what are the lessons learned? Nick shares three things that he knows to be important. One build the right team for the stage you're in. To build a great product that solves a real problem. And three, make sure you have an initial Tam and a path to Tam expansion that will help you build a big business.

Then he says that the rest is all about trying to enjoy the journey with minimal stress while riding the line between confident and parents. Having a background in engineering, operations, product and development, Nick shares more of his experience, learnings and a ton of insights in our discussion. Take a listen as we dive deep into not only his expertise, but we talk about the all important topic of data.

So, so excited to be here today with Nick Bonfiglio currently the co-founder and CEO of synchry. Nick has had such an interesting professional journey through engineering, operations, product and development, as well as being a founder, author, and CEO. So I'm super excited to dive in for those of you who may not be familiar with tinkery synchry is taking a data first approach to data integration.

Automation and management their data platform, not only uniforms scores and cleans data, but then ensures that this comprehensive data is available in all of the different systems and kept aligned and in sync. So welcome Nick, and thank you for joining me. I'm super excited to learn more about your journey.

Nick Bonfiglio: Awesome. Thanks Roslyn. And I'm happy to be here and thank you for having me on. That's

Rosalyn Santa Elena: Great. So you have had such a comprehensive professional journey, right? Starting on engineering, you've done dev ops and then into product. Can you share more about your career journey and maybe, you know, how it led to Marquetto and then to founding century?

And if they're in the, you know, maybe some of the key milestones or major events that kind of pushed you forward.

Nick Bonfiglio: I mean, uh, you look, I've been around for a long time. I'm an old guy compared to, uh, best thing I could say. You know, my entire career in general has prepared me for SAS. I've been an, you know, an engineer back before the internet was even created and, uh, was popular.

And, uh, and I know, you know, been in SAS businesses with the exception of a small stint at Lucasfilm. I've been in SAS software businesses, my whole career, and I've seen. Uh, I have a balanced perspective on, uh, you know, what works and what didn't work and why. And, uh, this is sort of helps me to, I guess, see signs a little bit earlier than most.

And so, yeah, I guess the best way to say it is my whole career up until this point. Pardon me for this role.

Rosalyn Santa Elena: That's awesome. So when you think about it, You know, Syncariand being a founder and CEO now, what are some of the lessons learned from that experience?

Nick Bonfiglio: You know, I, I, I kind of, uh, boil this down to like three really important things, um, that, that I've learned as a second time, a founder and, uh, and also doing the things that I've done in my whole career is that.

And probably the most important thing is to essentially build the right team for the right stage you're in. I mean, if you try to over gyrate to, to experience at a S you know, at a seed stage, for example, or, uh, you know, not enough experience when you're at some advanced stage, it's just not going to work.

So it's really hiring the right team for the right stage. Probably the number one most important thing. Obviously second is, uh, you know, having a great product because I'm a product guy. I have to say that, but it's really a great product that solves a real problem. So make sure. Not just building a product because you can, and that you're actually building a problem, a product that solves a real problem that people are having that would want to pay you money to solve.

And then lastly, I think, uh, what happens is when you're starting out, you have to enter into a market in a particular way. So you have an initial Tam that you're going after, but you really, really have to have. The path to Tam expansion in the back of your mind, the whole time in order to go build a big business.

So you can't just rest on one part of your Tam. You have to continue to think about. Where am I going to go next before you get there and make sure you're preparing yourself to go take on that Tam expansion when the right time comes. So the rest of it to me is, uh, you know, it's hard to say, but it's try to enjoy the journey, uh, with as minimal stress as possible, because it is, it is hard.

I'm gonna tell you, it's not, not for everyone, but you know, and you know this job to see you. I like to think of it as, you know, riding the line between ultimate confidence and ultimate paranoia. So somewhere between there is kind of where you tend to run. Um, but that's yeah, that's, that's how I'd characterize it.

Rosalyn Santa Elena: That's awesome. Thank you. Um, so let's talk a little bit about Syncari, right? And as you mentioned, you know, kind of oftentimes, you know, I think you're trying to solve a problem, right? So I think a lot of businesses start with that. Founders are trying to solve a problem and data is often a very big, if not the biggest problem I would say for businesses.

So how did the idea start? You know, what was the vision you had right when you first started the business two years, right?

Nick Bonfiglio: Yeah, well, after seven years of Marketo, one of the things I realized is that day it was becoming a huge issue and the way people were using the product, um, you know, I don't know if you're familiar with Marketo, but we have bass campaigns that let you run all kinds of different things against your, your data.

And a lot of people are running these one-time bass campaigns that do simple change data values, and all kinds of different things in their data. And I started seeing that. And people were asking us for like data hygiene, kind of, how do you solve for this and that and the other thing. And so in their data model and, um, what happened was I went to lunch, uh, with a CFO friend of mine.

And that person who's probably well known to you guys is, uh, uh, was just bitterly complaining essentially about the state of data and the companies that he sits on the board of, you know, um, Marketing comes in with a set of numbers. It doesn't match what a sales is talking about, but finance is talking about, and somehow we're all in the same room talking about different sets of numbers and different sets of metrics and, um, and things like that without there being a tie across them.

And it made me start to think about what was going on in the world, uh, with data and why in 2019 companies are still struggling with data. It's fair to say that. You know, we spent the last 15 years in the SAS explosion and then we started inventing APIs and everybody thinks of this problem is just a simple integration problem like we have for the last 15 years.

But the reality of what's going on is that people really want interoperability across their stack. They want their. Essentially their business to operate cohesive motion that they're going through to support their customer journey. And so this is what we set off to do. It's not about just work flow.

It's not just about, um, you know, uh, the data itself, but it's about making sure that you have the right data in the right place at the right time, uh, as, as it comes up. And so out of curiosity, I just started researching this problem and realized that. You know, the things that came before us, the I-PASS, the MDMs, the CDPs of the world.

We're never really envisioned to solve that data management issue. That companies struggling with at that point. And so when we looked at what that was going to entail to solve it, it required a complete rethinking of how systems are stitched together in order to interrupt.

Rosalyn Santa Elena: Got it. Okay. Well, so as you've started though, to build out the company, right, you're bringing on a ton of amazing customers.

I saw a greenhouse log DNA service max, and I saw Dremeo on your, on your customer. Who I love Billy Bosworth, by the way, he was like the best CEO I've ever worked for. And apparently my dog thinks so too. Yep. Go ahead and close that door. Um, and tens of other companies. Right. So, you know, what have you seen, um, what have you been seeing sort of in, from your customers and what are some of those key learnings and even in talking to prospects as well, like, has anything surprised you or sort of change the way that you're approaching the market?

Nick Bonfiglio: I think the interesting surprises that as we were doing the research and the initial, um, you know, product market fit for the, for the product is that nearly everyone we spoke to, uh, had complained about silo, data management problems and data quality issues across the board. So, which is great for us, but I think the other key learning is that, um, you know, a lot of these customers have different requirements when it comes to their own individual stuff.

And their distinct go to market motions that there happened to be doing. And so this, um, is how we ended up essentially with the platform we have was how do we create a flexible no-code platform in order to support the go to market motions of, you know, all these different combinations of systems, as well as the go-to-market motions of each individual company.

And, you know, that's why we came up with this. No, essentially this pioneering of this data automation category, which we feel we've built right. Platform to make it adaptable to every business, to control sort of the, the data destiny that they happen to be on, uh, for themselves. So. Those are the kinds of key insights we saw.

We never run into people that say, yeah, my data's perfect. Right. It is bad. And I've been trying to fix the various different ways a lot, uh, several times, how has your, how are you going to solve this problem that no one else has solved? And it's a great opportunity to say, well, you know, let us show you.

And you know, it's, it works for us when people say like, yeah, I don't believe that you can do this. And then immediately moves into a demo. They see the platform and go like, oh wow, this is. Not like anything I've seen before. Um, yeah. I could see how this is going to be highly relevant to solving, not just my immediate problem, but then they start thinking about.

All these other issues that are happening in their businesses. It's something like synchrony can help them with. And it, it, you know, as a product guide, I think they're speaking for all the product guys and engineering guys out there. The thing that fuels us the most is when we hit on something that really solves a real problem for people, and they want to use it to try and solve their problem.

And the feedback we're getting right now is that, uh, this has been really great.

Rosalyn Santa Elena: That's awesome. That's so awesome. I know that the technology is just getting so complex and trying to manage the data, you know, within so many different systems and keep them in sync and aligned. It's a mammoth mammoth, you know, opportunity, not just opportunity, but challenge for everybody.

So, I mean, I think about, you know, the desire and the requirements and the need right. For data, right. Just continues to blow up exponentially. Um, it's not the, you know, it's not even just the data, right. Per se, it's all the insights, the analytics, the predictability for go to market teams. Right. That good data.

And it enables I revenue teams really can't be successful without it. So what are some of the, you know, The mistakes are really the no-nos right. That you have seen companies make when approaching their data strategy.

Nick Bonfiglio: You know, we're, we're seeing this in a few, uh, prospects and customers. I think the biggest number one no-no is the absence of a real stress.

Um, because in the absence of a real strategy for what it is you're trying to do with your data, it gives away to one specific person sort of taking the reign and defining their version of what they think you want to get done. And that's what we see happen in a lot of organizations. And not saying that it's wrong, it's just that, that was that person's interpretation of what was going on with the lack of a real strategy.

So I think number one is make sure that you've got. Um, a real strategy for your data. Um, and we talk more about that in a little bit, but, um, you know, other no-nos, um, you know, I I've seen is overly complex CDP and environments that people try to stitch together. Using multiple tech stacks to do their integrations.

I mean, I think I just recently wrote a LinkedIn post about, you know, reverse ETL 42 transformation through DBT, a data warehouse and all of this stuff all stuck together to try and fix your data. And it's. Not gonna not going to yield the right solution for people. And, and, and the most important thing is people start thinking about moving their departmental data out to something else to try and make it cleaner or accessible when you really need the data and the insights, which are different than just the data.

Um, is. In the departmental systems where you already have the business logic to take action on that data. And so whenever I see people trying to move data off to the side or treat the data and the data warehouse as their source of truth, leaving their departmental systems without a source of truth is what the implication is there.

It just just seems like it's a complete backwards way of thinking. And you know, the, the example I tend to use here a lot is that. You know, having an account insights in your data warehouse is essentially like being able to, you know, to, to use a CRM and marketing and customer success systems that makes, um, that insight useful while you're actually wanting your business.

And what we see happening is like, I mean, I don't know how you operate. When was the last time you said I'm going to log out of my CRM system and I'm going to go to the data warehouse. So go see what the real truth. It just doesn't work that way. And so when you think of it as that problem, It's just not the right way to solve it.

Yeah.

Rosalyn Santa Elena: It makes a lot of sense, you know, as, um, I guess as data continues to play sort of a more and more critical role, like what have you seen in the market in terms of trends? Right. And do you have any predictions for sort of where you think data is headed, especially when it comes to revenue? Hmm.

Nick Bonfiglio: Yeah. I mean, look, there has been an explosion of SAS. We all know this over the last 10, 15 years. And like I said earlier, Um, trying to get the systems to, uh, inter-operate is really what is becoming the growth trend that I see happening. And first of all, SAS systems and data warehouses are not going to go away.

It's just, what do you need to make these siloed systems work in tandem together for the business that you're trying to run across the entire organization? And that's what we think is, um, changing in people's minds. It's not, it's no longer just important to say. I need this piece of data to exist over there.

It's, you know, I need that data to exist over there at the right time. And it needs to be the truthful data. I need to know that it's governed by the system. That's supposedly responsible for this data. And a lot of the things that we did, uh, with synchrony is about not just automation and transformation, all the things that you can do, but it's also the governance aspects of ensuring that that source of truth is maintained by the system that's truthful at that time.

Uh, the way we like to talk about it, Rosalyn is if I have an opportunity, you you'll get this. If I have an opportunity that's in, uh, you know, in a particular stage before close one, certainly probably want the sales team and the rev ops team to be responsible for that opportunity at that point. But as soon as that thing hits closed one, and you have some automation to automatically create them.

In NetSuite that creates an invoice and tracks it. At that point, you really don't want your sales team or your rev ops team for that matter to really be editing that, uh, Willy nilly. And so the ownership and the governance of that opportunity at that point belongs to the finance folks. So being able to just run that drill as opposed to just saying, oh, I'm going to shove this data from over here to over there, which is what we've been doing for the last 15 years is really, we're kind of bring to the table.

That's going to change the system.

Rosalyn Santa Elena: That makes a lot of sense. I love that. Yeah. There's a lot of, there's a lot of governance around the data. Like we don't want this person touching it at this point in time and who needs to see it and just managing that. It's just, it's a lot.

Nick Bonfiglio: I'll Just say it isn't. And the, our unique approach is that you don't have to operate on the systems, which is why.

We automatically create a unified data model from automatically for their customers, by the systems that they're using. We actually know the data model in Salesforce, Marketo and HubSpot, all, all the systems that we support in the platform. And we're able to create a unified data model from all those systems.

And so we provided people with the ability to not do it. Um, integrate the systems as, uh, as we did for the last 15 years, but to get them to inter-operate from a unified data perspective, meaning I have an account object that runs my business. The data in that account object is X, Y, and Z. And it's stitched together from all the systems that control the different parts of the account object.

If that makes sense. So being able to operate on from this unified data model perspective, as opposed from a connection perspective, which we've been doing for so long is, is the change that we're trying to bring to them.

Rosalyn Santa Elena: I love that. I love that. I think that's so great. Um, you know, as I go to market and rev ops leader, right?

I think I can speak for every other ops leader. When I say no one thinks their data is a hundred percent accurate, a hundred percent of the time, right. I'm in the data, maybe 90%. Correct. And 90% of the time, right? To me, that end state of sort of data Topia is, or data Nirvana, right. Is when you have real time comprehensive, accurate data, that's visible, it's accessible by the right people at the right time.

And that's a lot, you know, that's a lot of words and, and I think it's. Huge huge challenge and huge, huge problem, um, for teams. But I think that's the end state, right? I mean, that's where we all want to go. So, you know, for ops leaders who are listening to the podcast, how do they get there? I mean, like, what are the key things they need to do and maybe not do right.

To have consistent, accurate, and meaningful data.

Nick Bonfiglio: Yeah. I mean, uh, so one way, and you know, which is where we're very unique, different in the, in the marketplace is to scan your data for accuracy, relevancy, and quality. And so, you know, where you stay stand, you can't fix anything if you don't know where you stand.

So we created something that we're calling our data fitness index that is really important for creating a continuous, empirical view of your data. Based on rules that come out of the box from us, but also the ability to customize those rules for what does data quality mean to you? And because we figured out that data quality to, you know, clarification, Rosalind is very different than what data quality may be to someone else.

Uh, and, and it changes between your leads, your contacts, your accounts, and even opportunities or other custom objects you may have that you're tracking data with. And so we really thought of it as more. How do we provide customers with the ability to always have a humanized view of where they really stand with their data based on how they want it to be.

And so this notion of our data fitness index, so you can think of it as like a continuous antivirus, like scan of your data. That's always presenting you with a score of where your data quality stands based on where you want to be. And so that's. What we're really trying to bring to the table. That's very different than just, you know, the integrations that came before.

In addition to the truly multi-directional sync capabilities that we have in the platform. It's how do we humanize the data and expose the challenges that people have with, with their data quality at every stage of the, of the customer's life journey.

Rosalyn Santa Elena: I love that. Do you call it a data fitness?

Nick Bonfiglio: That's right. That's what we call it. So it's part of our data quality studio, which is a part of Syncari's platform.

Rosalyn Santa Elena: I love that because sometimes, you know, your data is wrong or it's bad, but you don't see it right until, until potentially it's a mistake somewhere on, hopefully not like a board slide or something, but oftentimes we won't know.

So having that sort of continuous scan. That you can actually customize to what you believe data should look like is great. That's amazing. Um, so, so maybe we could talk a little bit more about the platform then, right? So you mentioned a little bit about how synchrony can really help, but what other things does tinkery do to help really accelerate that end state help us get to that data Topia sooner?

Nick Bonfiglio: Right. So the first step we just mentioned data fitness sickness is measurement and understanding where you are. And so then from that point on, you can think of. As a treasure chest of capabilities to help you deep and transform, automate, and eradicate, which is one of the more important things you want to do with data from all your connected systems.

It doesn't help you to have a bunch of email addresses that never pass through enrichment that never even meet your minimum bar for engagement in hanging around your system all the time. So exposing even just that aspect of it and giving you the tools to go eradicate that day. Or fix the challenges with your data.

So what we do is when you have a data fitness on all the objects that you support, that you know, that, that you wanted to run it for, we then point you to places in that, um, in, in the pipeline where you can go act on that issue. For example, let's say your phone numbers were not poorly formatted. And so they weren't always in the same format or they weren't.

Um, you know, consistent, um, we can help you transform and keep your phone numbers consistently E one sixty four format or whatever format you want. But the point is, is once you fix that piece of data and you've transformed it for the within Syncari, the answer to that ends up in all your connected systems at the same time.

And so being able to do these operations in a central place, but then affect all the connected systems from one place is how you not only achieve good data, but ensure that that good data is getting out to area. Organization and your business to do you to be able to have the best view of what's going on.

And so at the same time, um, you know, we also talk about how to include our data store, um, which is essentially, we'd like to call it a rev ops person's personal data warehouse, and without doing anything in synchry, we expose the ability for you to start running now reports and BI reports and whatever.

Point what your favorite BI tool at synchry and you now have a sort of a, I would call it a departmental or rev ops, specific data warehouse. It doesn't require any attention from any it, no coding or anything like that. And so we provide you. So project, the score provides you with a way to fix it and get it repaired.

And then we provide you with a way to report on that data. In that those reports are literally an exact replica of what's going on in your operational systems. So no longer are you going to show up in one meeting with marketing thinking, the number of leads is X and sales thinking. They're Y and your data warehouse thinking their C in the equation, which is what tends to happen a lot in today's infrastructure.

Rosalyn Santa Elena: Oh, I love that. I love the no code part too, because every time I hear code, it's like, oh, I got to get a developer because I'm definitely not a coder.

Nick Bonfiglio: Yeah. Yeah. If you're, if you're a decent marketing operations or sales ops person, you should be able to use synchrony. No problem. It does have require some logic knowledge, but if.

Comfortable in Excel. I mean, that's another way to think of synchrony is think of a giant Excel spreadsheet on top of your unified data across the board and being able to do whatever you want with it. And the answer from that ending up in, uh, all, all the connections.

Rosalyn Santa Elena: That's awesome. Well, so, you know, as I, as I think about the revenue engine, right in this podcast, you know, I was hope that others will be able to learn how to accelerate revenue growth, right.

Power, the revenue engine. So from your perspective, you know, we talked a lot about data and a lot about things that will actually help to enable rev ops and help power that revenue engine. But from your perspective, what are the top things. You know, revenue leaders should be thinking about right. In terms of data, as it relates to powering that revenue engine.

Nick Bonfiglio: Yeah. So I'll go back to developing the strategies, the first thing, which means determining what are the most important pieces of data that operate, manage, and help you grow your base. And, um, I, and I think as part of that strategy, resisting, adding too many fields all over the place, it's something that needs to be part of that strategy to make sure that whoever where's responsible for curation of the data model is, is, you know, understands that in, you know, you didn't have anything that's not pertinent to your strategy and removing those fields.

Yeah. Is a great thing to go off and start thinking about. You know, I, I like to think of it as like, you know, a customer journey is no different than a relay race. Right? So what, what is, what is the most important data? Um, that's critical to a particular point part of the customer's journey journey and communicating that across the business as your customer progresses through that journey, and then ensuring that that truthful data.

Reaches the appropriate teams at the right time, essentially to take the Baton. So that's how we see it. And it's not just about shoving data all over the place. It's about how do I get the right data from the right places that are the truthful way places and make sure that it reaches all the other areas of my brain.

At the right time with the most cleanli and, you know, consistent, accurate data that I possibly can get there. And it's lastly, it's important to know, I guess that, you know, key insights that you plan to glean from your business, like what, what are those are from your data? And I, I. Stress that separation of what our metrics versus what our insights metrics are, you know, one thing, but what are the insights that you need to share across all these connected systems?

The way I think of it as like how many open P ones are there for a customer in my zone. And how do I get that number to exist in my account object and that account object that is used across my marketing success and financial systems. So I kind of know a little bit more about the health of a customer.

So there's no way I'm going to go out and nurture a customer to upsell or cross sell. If I know that they're in some state where there's the sentiment of that. Is not there. They've got a bunch of P ones open or whatever those, those insights are for your business that tell you that what I would do, if I knew that I had a customer had too many open PNLs on the account object, uh, I would probably want to nurture them to help.

And so then I would probably want to put them into a cadence that nurtures that customer back to. How have you talked to your success person? Have you, you know, you sure you're getting all the support you need, uh, things like that in order to, so they know that, Hey, you're watching, you know, where they are.

I mean, you're, you're, you're engaging. To get them to health, as opposed to. Just blasting them with more cross across that.

Rosalyn Santa Elena: Yeah. I love that analogy of being in a relay race. Cause I think that is exactly what it is. Right. Kind of customer journey, those handoffs between not only the teams and the people, but the data, right.

The data, getting to the right team and the right person at the right time. I love that. So if there was one piece of advice, right. That you would give maybe to another CEO or founder, or even a revenue leader, kind of that one thing that you think made all makes all the difference. Like what would that be?

Nick Bonfiglio: Hmm. Well, two revenue leaders and CEOs. Well, I have a catch phrase. I use all the time with my team. They don't really like it too much, but I'll just use it. I usually just say, just try not to lose whatever you do, like just try not to lose. And that's what I would say is the one thing.

Rosalyn Santa Elena: That's great. I love that.

I'm going to have to use that with Scott. The next time I talked to him,

Nick Bonfiglio: especially for revenue leaders and CEOs, try not to lose it.

Rosalyn Santa Elena: Very important. So cool. So as we wrap up, you know, I was asked, um, the guests, you know, I've loved to know two things, right? So one, what is the one thing about Nick that others would be surprised to learn?

And two, what is the one thing that you really do want everyone to know about it?

Nick Bonfiglio: Yeah, I guess many people would probably be surprised to know that I'm an immigrant. Um, so, um, and I am, and so I'll leave it at that, but that's probably one.

Rosalyn Santa Elena: What about the one thing that you really want everyone to know about?

Yeah.

Nick Bonfiglio: I, you know, I'm a certain, uh, appearance on the outside. And so I've learned that people try to judge me by the cover of my personal book. Um, and you know, they really don't know that, you know, what's inside. Of me is nothing like what's on the outside. And so I, I battle this continuously in my career and, uh, everywhere I go, where they see somebody on the outside, that's not the same person on the inside.

Rosalyn Santa Elena: Really. I'm going to have to offline. I'm going to have to dig into that one with you because I, I see you. And I think you're just so transparent, so authentic. And I kind of like when I, when we talk, I always feel like what you see is what.

Nick Bonfiglio: That is true, but I mean, uh, you know, I think my size and other things come into play.I see.

Rosalyn Santa Elena: Well, good. Well, thank you so much for joining me and sharing your thoughts. I think this has been incredibly helpful. I think that the listeners will definitely be able to not only gain a new, fresh perspective about data and learn a little bit about Thinkery, but also some things, some really useful tips.

I think that they can go away and actually go and practice. But thank you so much. I really appreciate your time.

Nick Bonfiglio: Hey, thank you Roslyn for having us and check us out. www.syncari.com. Um, and, uh, we're, we're here to answer any questions we have about data. Thanks.

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