By clicking “Accept All Cookies”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.

Startup Happy Hour Podcast with Robin Marcenac

EZ
Elizabeth Zink
Sep 22, 2020

Diana Chen: Welcome to Startup Happy Hour, sponsored by Content Allies. Grab a drink and join us to hear fun and inspirational stories from startup founders and visionaries who are making a positive impact in our communities and learn how you too can turn your new and exciting ideas into reality.

Hey everybody, and welcome back to another episode of Startup Happy Hour. I’m Diana Chen, your host, and I’m here today with Robin Marcenac. Robin is the Head of Customer Experience and Success at Pypestream, which is an online digital messaging company, and I’ll let Robin talk a little bit more about that. Hey Robin, how’s it going?

Robin Marcenac: Hey Diana, great! How are you?

DC: Thanks so much for – Great! I’m doing very well all things considering. Thanks so much for being here today and taking time out of your schedule to share your story with our listeners.

RM: My pleasure.

DC: I’m excited to have you here because you’re the first CX person that I’ve had on the podcast, so I’m excited to learn more about that world and let our listeners learn more about what it’s like to be a CX professional as well. So, why don’t you just start by talking more about what Pypestream is, what you guys do, all that good stuff.

RM: Yeah, absolutely. And let me say, I’m honored to be the first CX guest on the podcast, so glad to be here. So, yeah, let me talk a little bit about Pypestream – Pypestream is a startup based in New York City, we’ve actually been around for just over 5 years, we were founded in 2015, and we were founded basically under the premise that consumers, especially younger generations of consumers, Gen Y, now Gen Z, entering the professional marketplace are looking to interact with brands and companies, large enterprises that they interact with very frequently, like cable providers, telephone providers, at home security, even retail and CPG brands, that they want to interact with them in the same that they do with humans and their friends, right? So, friends and family you message, you use iMessage, you text, you might use Facebook Messenger or other channels to interact with them, and we wanted to bring the same kind of basic messaging premise, the always available, always on-demand, chat experience to the enterprise world. In this space which has really evolved since then we’ve found that there is a really big opportunity to that with automation, meaning using artificial intelligence to, not only offer those kinds of messaging experiences, but also automate them; meaning having fairly advanced algorithms in place to understand what humans are asking and what they are saying and being able to, kind of, automate those interactions. And, the basic premise, again, behind that being that the large enterprise space, especially with, you know, customer support, other types of common interaction channels, whether it’s, kind of, online and in an eCommerce interaction, there’s a lot of repetitive tasks and things that automation is perfectly suited for.

So, we’ve built the company – our CEO Richard Smullen founded it, like I said about 5 years ago – and I joined just about 2 and a half years ago to lead, really, the entire part of the company that’s responsible for taking our underlying platform which is comprised of many different components, NLP, natural language processing, being just one of those and really deploying that for all of our customers. So, customer experience is a huge part of, not just my title, but pretty much my entire life. We’re all about really working directly with these large enterprises that are customers of Pypestream to onboard them onto the Pypestream stack, onto our platform, and then build these really rich, fully automated conversational experiences, that they then make available to their customers, their consumers, on their website or in other channels that they might interact with their consumers on. So, in a nutshell that’s what Pypestream does and I can certainly dive a little deeper into my role as well.

DC: Yeah, for sure, I would love for you to do that. But before we get into that – so is my understanding correct that Pypestream, on a basic level, is just like an advanced chatbot?

RM: Yeah, it is. We actually – and you wouldn’t know this if you weren’t in this space – but the chatbot industry, unfortunately, got a pretty bad reputation in the early 2010s, mid 2010s when a lot of NLP technology came into the market and it’s been around forever, NLP is not a new concept, the ability to understand what a human is typing in is technology that predates me even being born, going back to the 70s and 80s; but we found that chatbot technology was really poorly implemented and a lot of that was due to misconception in the industry on both vendors and buyers of the platform that you could really, kind of, train models and get chatbots to understand anything and everything under the sun and as long as it was trained properly you could, kind of, let them go freely and you’d solve all the problems that these large companies have, and we identified that as, really, a gap where in order to have really rich fully automated, really valuable conversational experiences – which go beyond a basic chatbot question and answer – you needed really rich UX, almost in the form of a digital agency coming into the fold to really design these great experiences and you also needed just quality front-end experience and design which is a big part of Pypestream as well. If you use a Pypestream solution on one of our customer’s websites, like many of the P&G brands we work with, you’ll find that it almost doesn’t look like a chatbot, it’s much more immersive, almost like an app-like interface, like a canvas really, that you have a lot of graphical user elements to interact with. So, we found that it’s really a hybrid of a chat experience with a more traditional kind of web-based or app-based-like interaction.

DC: Gotcha, and do you guys have a part in designing or building on the NLP or is that not something – is that something you take from third parties?

RM: Yeah.

DC: Yeah, is that something you guys do in-house as well, is work on that component?

RM: It is, yeah. We truly do bring the full stack to market for our customers. So, I should say actually I, in my prior career, was with IBM and I was deploying IBM Watson technology, so very similar use cases and what I found was you can have really powerful NLU, really powerful individual components but if you don’t have the full package you kind of fall short because large companies are looking for, best case scenario, a very small set of vendors, if not one single vendor to give them all the capabilities they need. So, at Pypestream we have all the NLP and the capabilities to, again, understand a user’s utterance, so what are they asking, we trained our own NLU algorithms in-house, so we’ve taken in open source classifiers and technologies that exist out there and, kind of, supplemented them with our own industry-specific training or in some cases specific use case related training models and so we’ve done that all in-house and that’s managed by our data science team, our R&D team, our Engineers who maintain all of that component of the platform. We take, really, that underlying platform which has all the components out of the box, with the NLU capabilities, with the front-end experience, which is really that canvas that you can build on top of, and the backend, kind of, call them the designer toolset to actually build out all of these flows and train the models. We’ve taken all that and my team, which is really our implementations and customer success teams, is responsible for taking all that and building unique, fully tailored solutions for all of our customers that want to use Pypestream.

DC: Gotcha, and I don’t know if you can answer this without divulging too many of your secrets or going everybody’s heads, but for me, personally, like I – even as humans like we all text in different ways, we all message in different ways and you might be able to imitate the messaging style of your close friends and family, people that you know really well, but even if I asked you to message in the same way I would message, like us having just met, you would have no idea how to do that. So, as a chatbot – even as an advanced chatbot that’s trying to read all these different styles of messaging, how do you train it to be able to pick up on all these different styles and different ways of saying things or people that have typos, you know, or type in shorthand and all these different things. Is that something you’re able to speak on?

RM: Yeah, that’s a really fantastic question and quite frankly it’s one that our Data Scientists are constantly focused on and improving our underlying NLU models. In short there are a couple things and part of it is expectation setting with the end users as well. So, first and foremost when we design our solutions, basically design these chatbots for our customers, we always advocate that upfront it should be very clear that the end user, like you for example, communicating with your phone provider over, let’s say messaging, on their website that this is an automated solution, right, it is a bot, it’s not a human because context is key and I think it’s important for the end user to know that. Actually part of that is that we’ve found just looking at logs and looking at usage is that people will actually communicate a little bit differently when they know they are, in fact, speaking with automation and that’s part of just the general population understanding more and more about this space and knowing that hey if I’m communicating with this bot or this solution that it’s different than if I’m speaking directly with an agent, I might not want to type a whole paragraph, but to get back to your specific question, you know, we train – and this is not unique necessarily to Pypestream, this is kind of an industry standard approach to training NLP models – you really want to leverage real data and so we work with our customers to get logs from existing live chat solutions where perhaps they don’t have some automation or bot in front of it, we’ll look at call logs as well and it’s all about the quality of the training that you do – garbage in, garbage out.

So, we work a lot to curate that data using sample utterances that are representative of a wide range of how someone might phrase a question and then you specifically asked about spelling mistakes – there’s this concept, again fairly standard across the industry, and I would say adopted and used by many different NLP models is fuzzy matching. So, the ability to look at a misspelled word either missing characters or, you know, characters that are off by one or two spaces within the thread of a word and that’s where fuzzy matching comes into play. So there’s a lot in the NLP space that allows us both from a training standpoint as well as just from a general capabilities of these models to have a pretty good accuracy ultimately, it comes down to the training but we have customers where 80-85% of the time we’re accurately identifying their intent, what they’re asking for, and that remaining 10-15%, whatever it is, we handle through maybe a disambiguating question to clarify what they’ve asked, then in some cases, yeah maybe we can’t actually service that particular request, then in that case we always have the option to get them to an agent, right? Because ultimately the goal is to make this a seamless experience for them.

DC: For sure, yeah I think this is all super fascinating stuff and not an industry that I have experience in or that I’ve delved into very deeply so it’s fascinating hearing all of this from someone on the inside for the first time.

RM: Yeah, it’s the tip of that iceberg I should say.

DC: Oh I bet! Yeah, I could totally – this is something I could see myself just going down a rabbit hole on, like, reading on Google or watching YouTube videos or whatever the case may be. But let’s go ahead and dive more into your specific role as a CX manager or head of CX at a company like this. What does your role entail and how do you contribute to making this technology successful?

RM: Yeah, you know, when you’re in the B2B space our customers are large, typically large enterprises, Fortune 1000 companies that really want to invest in a digitally transformational experience, right? They’re trying to take a legacy, maybe website, legacy call center experience, something that today might be fragmented and they’re really trying to adapt that, maybe leveraging the same backends and making this something right for their consumers which is, again, a more and more technologically savvy consumer coming in, wanting to interact in these messaging channels. So, in my role as a CX leader it’s perhaps a bit different than a CX lead for a B2C startup, you know, a company that’s directly out in the market, maybe has an app in the app store, something that you can download directly and just go off and running, right? What we do does require a fairly significant list, it requires coordination for our teams of resources, implementing the product and it requires coordination with these large, publicly traded companies that need to dedicate some resources as well to support really standing up and deploying this solution.

So, in my role I’m really responsible for a couple different things; I have a team of individuals that span a couple different functions but it’s broken down, ultimately, into two main functions – one is implementations and other is customer success, which might be more traditionally aligned with customer success across other SaaS companies for any of your listeners who are in those roles. The implementation piece is really that hands-on, onboarding and development cycle that we have to go through with these companies. It can be as short as a couple weeks, less than a month, it could be multiple months, right, depending on the complexity of what we’re deploying, but ultimately it comes down to, like we just talked about, training an NLP model to understand the scope and the use cases that we’re building the solution for, whether that’s customer support related, sales related, marketing, whatever it is, it’s building out actual dialogue, so we build out comprehensive responses, how to route users appropriately based on context and, again, automating all of this. It’s similar to maybe platforms out there like RPA tools or no code workflow design tools, so we have, again, a graphical UI where our designers go in and build these solutions. And then we focus a lot on integrating, you know, we have to integrate into backends, another key premise and basic requirement for us to really drive value for our customers is to be able to integrate into their backend, if we want to be able to really serve the needs of a customer going in to get support with their last statement on their phone bill, we need to know who they are, and integrate into that system and maybe help explain to them why the bill is higher than it was last month and maybe give them a promotion for being such an important customer. So, all this really cool, complex logic comes into play and that’s what our team focuses on. So, I manage a whole team of project leads, designers, engineers, resources that are really doing the end-to-end development work in partnership with our customers. And then lastly there’s the customer success side which is super important, obviously. It’s all about once we’re live with customers we focus heavily on reporting and analytics and making sure that we’re measuring the impact of the solutions, looking at KPIs they want to measure against, whether it’s things like how much volume are we handling, what are deflecting away from other channels, what’s the success rate, and then informing our own customer about where can we improve the solution. So, we do a lot with supervised machine learning techniques to look at questions and things that we didn’t understand properly and reroute the user. So, obviously you can tell I’m pretty excited about the stuff we do but it’s really a very white glove service to how we deploy our technology and then make sure our customers are then using it to the fullest extent possible.

DC: Yeah, wow, that actually sounds pretty different from a traditional CX role, at least from the couple of clients I’ve had who are in CX roles. It sounds like your role is a lot more comprehensive and covers a lot more things. So, given that you’re in charge of so many different things, what does a day to day look like for you or if there’s even a day to day.

RM: Yeah, and to that point CX in the SaaS world, you know, especially in the startup world, I see to be a more customer support focused function, it’s kind of a nice way of saying customer support without saying support, in my opinion. We like to think of it as customer experience because it’s really everything we as a company have to do at Pypestream, to create a superior customer experience for our customers, right? Or I should say our customers customers, which, you know, is that classic B2B2C space where we’re serving both the enterprise that’s a subscriber to Pypestream but ultimately their consumers.

So, a day to day for me is – we have, because of the way we operate, right, Pypestream has dozens, not thousands of customers, right? What we’re talking about is large scale, multi-year agreements with large enterprises that have commitments with us, we have almost partnership level engagements with them to ensure the longevity of these contracts that we have. So, my day to day is really overseeing active, large scale enterprise deployments, making sure that we’re delivering against specific milestones, making sure that I’m working with my project leads to ensure that we’re hitting those, working with our customer success lead, as well to ensure that we’re having regular QBRs, checking in with those key accounts that have been live, you know, benchmarking against those KPIs that we may have set for those accounts and ensure that we’re seeing growth or at least trending in the right direction against those KPIs and I work very closely as well with the rest of our leadership, and department leads. So, in my role I’m part of the management committee at Pypestream so a lot of what I focus on too is collecting feedback from senior stakeholders from within our customers, feeding that back to our product team, helping to find the roadmap and influence some of the strategy around where we want to go as a company, knowing that ultimately what we see from our customers and the things that we’re doing for them really feeds very closely into our roadmap, right? We have an innovation side of the roadmap where we’re constantly adding new functionality and features we believe will differentiate us and bring value to our customers but we also have a piece of that which is our customers came back to us and say hey, you know, this is really valuable or would be great for us and we, kind of, go back and add it into our strategy. So, a lot of my role is, kind of, playing and interfacing between our customers and our product team as well.

DC: Gotcha, gotcha. So, I know this is your first customer experience and success role that you’ve taken on and I’m just pretty fascinated by your background, just doing a little Linkedin stalking here, but going way back to college, I know that you had studied, well, a variety of things but amongst those Material Science Engineering. So, what was going through your head at that time, what route did you think you were going to go down and then what route did you end up taking and why? Kind of take us back and then take us through the journey of how you ended up here where you are today.

RM: Yeah, that’s a question I get occasionally is wow Material Science so why didn’t you have a Phd or why aren’t you in that field now? So, I can even go a step further and go back to my teenage years when I was in school. In high school I always had that side of the brain, maths and sciences was where I enjoyed, that’s why I excelled and then I went to UPenn for my undergrad, that had a joint program and it was a joint degree between the business school and the engineering school. At the time I just loved physics, I mean properties of materials, you know, outside of my day job I actually have books on my shelf here that go back to the structure of materials which was always something very interesting to me. I found that after pursuing my undergrad degree I, quite frankly, didn’t see myself pursuing that path despite having an interest in the space, of going beyond and working in a lab or working in maybe an engineering field, like mining or oil services or whatever where those kinds of key skills would come into play. So, I instead took a route of going more generalist into, actually, a consulting field and even though, of course, I don’t apply my engineering skill set directly, I’ve always been a firm believer that being an engineer, having an engineering degree does, kind of, create a specific way of approaching problems and just, kind of, that different troubleshooting mindset. So, in a consulting role that came really in handy for me just in the way of dissecting and getting to the root of problems. So, I was with IBM for a few years and got more and more into, given of course, IBM is first and foremost a technology company, got more and more into the software space of things, and so ultimately combined that engineering background along with the business degree I had into becoming much more focused into, again software implementations, the software industry in general. And yeah, after spending a few years with IBM, seeing both the good and the not so good of being at a large company, I wanted to take that and apply it to more of a dynamic, really smaller scale space, in a startup, ultimately with Pypestream, to, kind of, flex my muscles a little bit more and take on a larger role within a smaller company and that’s how I got to Pypestream.

DC: Wow, that is quite the journey, I think that, I mean, it’s super impressive if you can start with that kind of foundation and go to where you are today and, kind of, pursue more of what you’re passionate about, what you’re interested in. I think that’s awesome. So from more of, like, the startup side, I know one of your many majors in college was also business and entrepreneurship and innovation, so clearly you had an interest in entrepreneurship and startups by that point in your life, when did it start – is that when it started in college or did it start when you were younger back in high school – when did you interest for startups and entrepreneurship initially start?

RM: Yeah, I think it started back then, you know, I was fortunate to be able to get really a – I mean at UPenn the business school, Wharton, is a great school and the curriculum I focused on there in the entrepreneurship and innovation space was because I had that interest, right? It was knowing that, you know, quite frankly, I’m the first to admit that I probably didn’t have the courage to go out and start my own company but I knew that I had that interest in understanding how do you do it, how do you scale a company, how do you build a company from the ground up and I thought having that skill set was really something I was interested in. So, I focused in that space and, of course, did a full 180 and instead went to work for Big Blue at IBM but I never lost of sight of that interest that I had and that experience that I had just gotten from school, so, ultimately, when the opportunity presented itself I was very interested in what Pypestream was doing it’s, of course, directly related to what I was doing at IBM which was really in the NLP space but focusing on large scale enterprise implementations of this type of technology and so I jumped at the opportunity, it was really a great opportunity to take what I had learned, both at school, in my time at IBM in more of the corporate setting and then take all that and bring it into the startup world which is, of course, much more dynamic and unpredictable then the large corporate world.

DC: Yeah, that was going to be my next question is how was the transition from IBM to a startup and also, you know, having said that you had that entrepreneurship interest back in college did you ever feel like you were selling out when you went to IBM or what was that decision process like?

RM: Yeah, I mean, did I feel like I was selling out? No, I mean, certainly it was a more conservative career choice to begin my career but my – I grew up in a family where my father worked for the same company most of his life, actually, and so for me that was actually important to, kind of, start and build a foundational set of skills, foundational – just an understanding of what it means to work in the enterprise world, right, or, quite frankly, business in general. And so that was really, I think, very helpful for me and I think that if you are – and maybe some of your listeners are in the same position – if you are yourself in a small company, in a startup that is serving other enterprises in this B2B space, I think hiring or having a team of individuals that themselves have been in a large company in the past is incredibly valuable because you really understand what it means, you know, your customers look at you and understand that hey, this person knows what it means to work in our industry, to be in a large company. There are, quite frankly, a lot of, you know, I should say downsides to be being in a big company, a lot of red tape, a lot of corporate, just things that slow things down and being able to navigate those, especially if you’re serving that industry, which Pypestream does, is I think super, super relevant and is very important for us to be successful as well. So, I’m very happy with the journey I’ve taken, I think the startup space that I am in now is certainly where I hope to stay and I’m a firm believer that with Pypestream we have a very bright future ahead of us.

DC: That’s awesome, and what’s the goal for Pypestream long term? Is the goal to grow in a leader in the space or to sell or, you know?

RM: Yeah, so I can’t speak – certainly we have a long term strategy as to exit scenarios as a company, I can’t disclose those here but our goal is absolutely to be one of the premiere vendors in the space. It is still a very fragmented industry there’s more than a dozen vendors in the space, although, I would argue that there’s probably less than 3 or 4 that truly operate at the level that we are at Pypestream, in terms of just having the full solution set and having the expertise that we bring; but our goal is to continue scaling, right, we’re growing at a fast pace, achieving our targets year over year and our investors have seen that. So, we’re on the path of where we want to be and I’ve been fortunate to be able to hire within my team resources that I trust and help deliver this to our customers.

DC: That’s awesome! And then what about for you personally, what’s in the future for you? In the long run is it to – do you want to start your own company one day, do you have ideas brewing already? I mean you don’t have to divulge all of those but I guess , what are you thinking for yourself down the line?

RM: Yeah, you know, my – for me I guess personally in terms of my professional career, I’ve always, kind of, had a variety of ideas especially in the NLP space as to how this technology can be applied in other areas. In the shorter term I think it’s pretty unique to find a startup where you can really see yourself growing and see the company growing around you so, I see the potential in what we’re doing at Pypestream. So, for me it’s all about growing the team I have, continuing to grow our offering, and ultimately being at a point where we have a very large portfolio of companies and we have an entire organization supporting those customers, ultimately, reporting into me. At this point we have a team of about 12 individuals, you know, that keeps growing year over year, and, for me, that’s where I see a lot of – you know, I’m just very satisfied in that role, very eager to see where we can take this next at Pypestream.

DC: Yeah, I think that’s very special and I do hear that a lot more from people that work at startups as opposed to big companies. I think when you’re at a startup you have a lot more say in where the company goes and you feel like you can actually contribute a lot more, whereas I think at a big company it can feel – it can be easy to get lost in the company and feel like you’re just a pawn in the game and you’re not really sure why you’re there everyday. But that’s awesome to hear.

RM: Yeah, I mean it’s the classic, you know, trope of big fish, small pond versus small fish, big pond, right? I mean, when you’re at a large company you have, certainly, influence within your own sphere and your own area but being at a smaller, fast paced, growing company you have the ability – and not just me, right, I mean, folks within my team we – I like to keep a relatively flat hierarchical structure in my team and I think applies within the company, you know, everyone from backend systems engineer all the way up to our CEO has say in what we feel is important to us as a company, what we think our customers want and it all, kind of, comes together to define where we’re going as a company.

DC: Yeah, this is something that I just – mostly out of my own curiosity – but what are some of your biggest management tips now that you’re leading a team, not just one team but it sounds like you’re leading and managing teams from design to CX to all these different groups. I’m more just curious for my own self and I’m sure a lot of people listening are in positions where they have to manage teams or maybe they’re just stepping into the role of managing a team and that can be a lot to handle at first. So, any good tips for managing a team?

RM: Oh yeah, yeah, and certainly a lot of this is from trial and error from my part. What I think, without getting too, like, pie in the sky, there’s a couple things that come to mind for me; one is there’s different stages of building out a team, if you’re starting from ground zero and it’s literally just you, you want to hire, first, people that you trust and people that can compliment your skill sets, whatever those may be and I think that’s something that we were fortunate, and I was fortunate, to do rather effectively at Pypestream early on was secure. Let’s say in a customer experience organization, you’re that people person, you’re really good about managing the accounts and coordinating with every individual customer, you know, find someone that compliments your skill set and is maybe deeply data oriented or focused on the metrics and reporting and something you can bring into the fold. So, number one, as a manager, hire in areas where you know that you have those gaps and hire people, ideally within your network that you trust if you’re really starting from the ground up.

As you get to the point where you have a handful of people and now you’re maybe starting to hire managers that will be managing others on your team and you’re now, kind of, once removed at least from your team it’s – another big thing, I think for me, is learn, because you now hopefully have hired the right people is and you should put your trust in those people – is avoid micromanaging, make sure that you have the right processes in place to get the updates you need and the ones that you want, there are plenty of great project management and task oriented tools that are out there and leverage that to get the information you need without slowing down your team by implementing yourself in spots or in steps in the process you really don’t need to be in. So, those have been 2 big things for me, I myself used to be really bad, actually, about micromanaging and it’s been something I’ve tried to really, kind of, step away from and do a better job of avoiding doing.

Last thing is, especially now, I mean, most, especially in our space, tech companies in particular, I think have been at the forefront of working remotely. We’re fortunate enough in that we’re able to do that, most software companies don’t rely too much, or at least don’t require that in-person interactions, so, you know, with the pandemic just that human touch can sometimes get lost. There’s certainly the risk of the opposite with, like, Zoom overkill, which I know is happening a little bit now, but as a manager I just, you’ve got to try and build a relationship outside of just the day to day, blocking and tackling in the work, building that out of office relationship, getting to know your team, it does wonders in terms of overall morale and also in terms of retention, right? I mean, I think as people feel like they’re part of a team, they feel committed to the overall company vision and the strategy then I think you can really create yourself a high performing organization. So, those are just three things, there are certainly more, I don’t think any of those are particularly groundbreaking but those are the things that, for me, have been very important.

DC: Yeah and it’s interesting to hear different perspectives because it’s like, going back to your second point about micromanaging, I feel like I had the opposite problem of that where I, kind of, I have always hated being micromanaged so I went the opposite extreme and was like, oh, I’m sure you know how to do, I’m not going to tell you how to do your job, I’m sure you got it. And they come back to me with totally not what I was looking for at all and I’m like, okay this is probably because I didn’t give you accurate instructions on what to do and didn’t check in with you on a month long project, you know, in timely chunks, so, yeah I think a lot of that does come from trial and error and apologies to everybody who was part of that trial and error process. But, yeah I think those are very good tips.

RM: Yeah, I feel like it’s like most things in life, it’s a healthy balance of proper direction without too much direct, like I said, micromanaging. I’ve been guilty of doing – like what you were just saying, right – not enough direction and so, you know, I’ve been in a managerial role for now 6 or 7 years, going back to my time at IBM, so, you know, like you said, you kind of learn by trial and error and hopefully you’re peers and coworkers are patient enough to work with you through it.

DC: Yeah, yeah for sure. So, tell people more about yourself outside of the professional and career driven Robin. Like, who is Robin outside of work, what are your hobbies, interests, what do you like to do?

RM: Yeah, so you wouldn’t know based on my voice but I’m actually French, I was born in France. So, that’s a little tidbit about me, I’m a dual citizen and all my family actually lives back overseas. We have, you know, my parents were first generation expats who moved to the U.S. when I was very young and actually got our citizenship back in the 90s, so, whenever I can, and actually being in a remote setting has helped a little bit, I try to go back and see my family. Of course, that’s – family for me is really important, just in all paths of life. I have two sisters, a couple nieces and nephews, so, spending time with them is super important to me. I’m married, my wife Cara and I have been married for just over two years, so starting a family, hopefully, very soon. And outside of that I, you know, when I’m not in front of my laptop in my office, you know, for most of the day, I live in New York City, I live in Brooklyn, so I try to get out, I bike quite a bit, so I have a nice road bike and try to get out on the streets. It’s actually pretty nice now in New York because there are fewer people so you can actually do pretty long stretches. So, that’s what I really like doing. If I’m feeling a little bit lazier I am probably unhealthily obsessed with soccer, in particular, I’ll watch an incredible amount of Premier League or Spanish La Liga so anyone who’s out there, big soccer fan, just hit me up, I’m always watching. Yeah, that’s a little about me, I love sci-fi too, I’m a big sci-fi reader, very psyched about a Dune movie coming out this winter, if anyone again is listening, so, highly recommend it, it’s one of the best sci-fi books out there.

DC: Nice, you could have led with the soccer and then the French part wouldn’t have been so surprising.

RM: Yeah, I mean, you know, that, kind of, if you’re – well I shouldn’t say every French person is a soccer fan, but it’s certainly a higher probability than if you’re living in the states, that’s for sure.

DC: For sure, for sure, I think I have, like, one friend here in Chicago that’s really into soccer and that’s about it. He knows all two or three soccer bars that we have here.

RM: I, actually, when I moved first to the U.S. we lived outside of Chicago, actually in northwest Indiana so I used to go see the Chicago Fire games back in the day.

DC: Wow! Wow, that’s – yeah, what a small world. I was just going to say all of that was – well all of that minus the soccer and the sci-fi was pretty relatable for me. I was also born outside the country, I was born in China and came here when I was four, so, very similar story, most of my relatives still live back in China and it’s nice to be able to get back whenever I can, but right now Americans aren’t very – well you still have your French citizenship, so you’re more flexible to travel – but I think the rule back then was that you had to give up your Chinese citizenship to become an American citizen so we haven’t had our Chinese citizenship in years and right now Americans aren’t allowed into China! How the tables have turned.

RM: I know, it’s a crazy world. I’m fortunate that I was able to keep my French passport and haven’t been back since March of 2020 but do plan, if I can, get there by the end of the year. So, we’ll see how things evolve.

DC: Yeah, I’m hoping to get back sometime early next year for my grandpa’s 90th birthday.

RM: Wow! Yeah you’ll have to be at that.

DC: I know, I know. But, okay great, so why don’t we wrap up with something inspirational and tell the listeners your biggest piece of advice for somebody’s who’s trying to get into your role at a startup company somewhere down the line. What’s your number one piece of advice for them?

RM: Number one, that’s a – can I give you maybe two?

DC: Yeah, yeah, we’ll let it slide this time.

RM: I mean, for me, it’s – especially in the – I think this applies across many different spaces, but the startup world is tough to break into, of course, if you’re founding your own company it’s a bit different than perhaps joining a startup, but I think you have to leverage your network and I think that applies across the board. We’re living in a hyper-connected world, the concept of your network is very different now than it was 10 years ago, than it was 20 years ago, and it’s so – it’s an invaluable resource, if you’ve been lucky to build up a good network, either from school or from whichever path in your career you’ve taken, to open up those doors, right? In the startup world in particular there’s just a lot of connections between VCs and startup founders or founders looking to grow their teams within other parts of their network. So, it’s a very interconnected world, it can feel a little bit exclusionary if you’re outside of it, but if you have the skill set, if you have the talent, and if you have the drive to put yourself out there, I think, that’s my number one piece of advice.

Me, personally, I’ve found that good things come to those who also wait and those who are patient and those who apply themselves and for me that was, maybe a bit of – you know, that’s kind of illustrative of my time at IBM, I, kind of, really committed myself to the role and spent 6 years there growing my skill set, growing my experience in many different areas, which allowed me to ultimately move into the role I’m in now. So, for me, patient application, being, almost like a – this is going to sound bad – but a servant to the job, it’s like you really want to apply yourself and prove that you’re not there necessarily for the recognition but you’re there to really prove that you can excel in the role. And I think that to me was very important and it kind of segues into the last thing which is, personally, I think egos don’t work well in – I mean, certain company cultures are very focused on the big leader or the set of management teams that are making all the decisions and they all have very strong personalities and strong egos – I think that can work well in some instances, personally I’m more of a believer in ego and – set ego to the side and have firm decision making, have really strong opinions but, kind of, bring in the opinions and the best practices of people around you whenever appropriate. And so that to me has been the three things, right, leverage your network, apply yourself in whatever role you’re in, and do your best to put egos aside and just take the best of everything you have around you in addition, of course, to your own opinion. Those are, for me, big ones.

DC: Three great pieces of advice, love it. Alright, before we go are you up for playing a quick game?

RM: Yeah, why not? Let’s do it.

DC: Okay, so we can either play this or that or we can play the word association game. I’m gonna let you pick because you’re the guest.

RM: Uhhhh, I actually don’t know what this or that is, so let’s do word association.

DC: Okay, cool! Apparently nobody knows what this or that is so maybe I should change the name or clarify it.

RM: What is it?

DC: Well, this or that is I basically say two words, like A or B, and you pick one. No explanation, these are both rapid fire games, no explanation needed.

RM: Oh, alright. Well because maybe people don’t pick it as much let’s – I’m gonna change my answer – let’s do this or that.

DC: Okay, alright cool. So, I’ve got ten sets of words, I’m going to say A or B and you just tell me which one. Super quick we’re going to fly through these. Alright, ready? Okay. Plane or train?

RM: Plane.

DC: Hot or cold?

RM: Cold.

DC: Night or day?

RM: Night.

DC: Beach or mountain?

RM: Mountain.

DC: Coffee or tea?

RM: Tea.

DC: Freedom or stability?

RM: Freedom.

DC: Business or engineering?

RM: Engineering.

DC: Ooh, okay. Customer experience or customer success?

RM: Ooooooh, customer success.

DC: Okay, past or future?

RM: Uhhhh future.

DC: Work or play?

RM: Work.

DC: Nice, that’s a wrap.

RM: Awesome.

DC: Good job. Good job, that wasn’t so bad.

RM: Not at all, that was fun.

DC: Nice, alright well, before you go, Robin, tell people where they can find you, where they can find Pypestream, if they want to learn more about that and go ahead and plug yourself.

RM: Yeah, let’s do it. So, first and foremost, pypestream.com that’s our company’s website. You can learn more about what we do, reach out to us directly from there as well. You can get in contact with us and if this type of technology, if what we’re doing sounds like you or your company might be interested in, definitely hit us up. You can also reach out to me directly, hit me up on Linkedin, my email is rmarcenac@pypestream.com, so that’s a great way to get in touch with me. And if you’re ever in the New York City area I live in Boerum Hill in Brooklyn, that’s another option too. So, always eager to find and meet new people.

DC: Awesome, sounds good Robin. My sister actually lives in New York, so pre COVID days I was out there a lot. She’s actually moving to Brooklyn, in October.

RM: Yeah! That’s where to go!

DC: So, we’ll have to grab a drink when I’m in New York or if you’re ever in Chicago, definitely let me know.

RM: You bet.

DC: Thanks so much for being here and sharing your story with us and we’ll be in touch, I’m sure.

RM: Sounds good! Take care.

DC: Alright, you too, talk soon.

We hope you enjoyed this episode of Startup Happy Hour sponsored by Content Allies. If something we said today resonated with you, please share our episode on social media and sign up for our email list at startuphappyhourpodcast.com. Happy hour doesn’t have to end just because this episode is over, continue the conversation with us at startuphappyhourpodcast.com or on Instagram @startuphappyhour.