How do you bridge the online and offline, and provide the same level of data to people that run businesses with physical locations? In this week’s episode, I talk to Marc Stolz from Olvin, a SaaS platform that provides predictive analytics to retail and real estate professionals.
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Episode Transcript
Matthew Todd
Hi. My name is Matthew Todd, and welcome to Inside the ScaleUp. This is the podcast for founders, executives in tech, looking to make an impact and learn from their peers in the tech business, we lift the lid on tech businesses, interview leaders and following their journey from startup to scale up and beyond covering everything from developing product market fit, funding and fundraising models to value proposition structure and growth marketing. We learn from their journey so that you can understand how they really work, the failures, the successes, the lessons along the way, so that you can take their learnings and apply them within your own startup or scale up and join the ever growing list of high growth UK SaaS businesses. Hi, and welcome back to the podcast here today with Marc Stolz from ovan. Mark, great to have you here.
Marc Stolz
Great to have you too, good morning.
Matthew Todd
Yeah, good morning, a very warm morning as we’re recording this. But yeah, looking forward to the conversation today. And like always, I’d like guests to kind of introduce themselves and the company that they are a part of as well, rather than me giving a pitch on their behalf. So I’d like people to hear it from the the relevant person, the guests themselves. So over to you for a little bit of intro first.
Marc Stolz
Yes, of course. So my name is Marc. And I’ve been working with a company called Olvin. for about four and a half years now. We started the company, because we saw that there was a disconnect between the online and the offline world. And that’s mainly getting access to data. So for online businesses, for many years, it’s been really easy to collect and measure data of the consumers. So for instance, if you go online on a website, and you’re trying to analyze basically which websites people have been visiting, how long they’ve been staying on a page, which other websites are they browsing, it’s very easy. But the moment you close your laptop, and you actually own a physical business, it becomes more tricky. The only data that you have available is mainly your sales data. But then you don’t really understand what’s happening outside what is affecting your business. Why is it been more popular? Why there have been more people on my store this week or last week? And is that a problem that’s linked to myself as a business? Or is it just the whole industry that suffering. So we decided to create a very easy and simple tool for a business owners, that’d be a mom and pop shop, or a big enterprise business to really understand consumer behavior and the journey. So not only looking at historically where consumers have been, but we thought the most important, especially after the epidemic is being able to predict where consumers will be next. So that’s why we created this dashboard, this platform that uses AI and machine learning to really understand consumer behavior and analyzes consumer footfall data. So the way we actually analyze that data is by looking at what we call geospatial data. And that’s a blend of different data sources. So the core of what we do is GPS, mobile location data. And all the data that we receive a comes from a variety of sources such as apps, Wi Fi, sensors, Bluetooth sensors, all the data that we collect is consented, anonymized and then aggregated and used for statistical purposes. So we do not hold any personal information. We don’t know which DevOps it’s from, or any kind of personal detail from people, we just know, time and location. But it’s really good. But it doesn’t tell us much, much much information.
So we need to start enriching the data to make it talk. So we add different layers of data. So we add mapping data to understand where this device has been seen on a map. And then we add another source, which is called Point of Interest, detail, poi. And this is basically understanding if that device or that person or that individual has been seen in a store and which type of store these people visited. So that’s great. It tells us where people have been. But then we add additional data sources to really give context and try to understand why these people have been there. So we look at, for instance, weather data, transport data, demographic data, but also credit data to really get that context and see which type of individuals go to which type of stores and then we do predictive insights up to 90 days ahead. So we look at all the historical data that we received. So we have access to about five years have historical data. And then we train our models daily to being able to predict up to three months ahead, how many people will be either in an area in a city in a zip code, or even down to a store. And then the use cases that we have right now, are predominantly for retail and commercial real estate. In retail, we help businesses with staff scheduling, how can they make sure that they have the right people in the right store at the right time.
But we also help them with store operations, making sure to have the right opening hours that they have the right inventory will also support with optimizing marketing campaigns, are they actually targeting or making sure that they’re communicating to the right consumers. And then finally, we also help them understand where to open or close a new store that’s been specially especially important after COVID there’s been such a shift of demographics that we can actually support with that, looking at footfall and comparing pre pandemic levels with with actual levels nowadays. And then we also support in commercial real estate. So landlords, property developers, but also brokers to understand the financial viability of a site, does it make sense to buy this mall or buy this specific store based on footfall data, or we can also support them to get access to data to attract the right tenants. So before, people used to use a lot of outdated data, which is census data, or they would actually send a team to specific location to really analyze the venue, use all clickers to actually count people in front of stores. We’re really trying to optimize that by just being able to provide the data and just a couple of clicks, and really get another source of data to actually be able to take strategic decisions. So we’re not only saving time, but always saving money as well.
Matthew Todd
Yeah, it sounds like there’s a number of benefits there from yeah, optimizing what they’re already doing, as well as making the most of potential opportunities that they’re completely unaware of at the moment.
Marc Stolz
Absolutely. And these are the two big industries that we’re focusing right now, obviously, we start to get interest from a lot of different businesses. So hospitality, for instance, which will also have governments, so municipalities that really want to get access to data. And they see a lot of use cases, we also have hedge funds that want to use our data to predict, you know, how the performance of some companies will affect the stock based on foot four. So there are a lot of different use cases. But as you can probably imagine, being a small growing company, we can only cover so much with with our resources.
Matthew Todd
Yeah, absolutely. And I guess on that point, you know, the company is is relatively new. And, you know, how did how did the company kind of come about in the first place, I suppose and and decide on those use cases to start with?
Marc Stolz
That’s a great question. Well, at the beginning, we thought about using basically just the location data to help brick and mortar businesses, but most importantly, the drinks trade. Okay, because we actually had a side project where we’re hoping we’re having our coffee shop. And we were kind of facing these types of questions. And, you know, from one day to another, nobody would be coming or like the number of people would be really, really significantly less than another day. And we wouldn’t know why that was impacting our business. And we started raising this question, or we thought, okay, it would be great to have a tool that could help us, you know, answer these questions. So we’re really focused on hospitality at the beginning. And, you know, we managed to speak through to very large companies like Heineken or LVMH. And always remember a moment in a meeting with, with LVMH. They were like, really like what you do, but why do you only focus on hospitality would be great to have basically what you’re currently building, but for hold the rest of the other brick and mortar businesses, and it’s great to look at historical data. But we would also love to be able to know what’s going to happen in the future.
So at that point, it was kind of a pivotal moment for us where we decided to, to completely refocus and shift our objectives and really focus on predictions So we we started restructuring the team hiring a lot of data engineers and data scientists to build basically, our models, and use the existing data that we have, so that we could start provide predictions and forecasts for businesses. And then we opened up to basically all the other industries. So there was a great pivotal moment. Always good to get that feedback from from from large customers. And we saw that as a, as just a continuity of what we were building as a business. And I guess, especially being in a smart, fast growing startups, it’s very important to be able to listen to those signals, and making sure to constantly readapt your roadmap. So you always look at, you know, an ideal roadmap for for the next three months, four months, and then maybe a slightly longer one with much higher level insights on where you aim to be in 12 to 24 months. But that’s a constantly moving project where you have to reassess priorities and move parts based on customer insights. But also priorities that you’re setting up as a business.
Matthew Todd
Yeah, and I guess the thing with that, I completely agree it is yeah, that that research, that listening should be a continual process, that learning should be a continual process. I suppose one thing with that is you’ve got to be made sure that you’re, you’re talking to the right people that are worth listening to as well. And you’re obviously talking to some quite big potential customers, rather than perhaps starting with smaller, less ideal customers, that might have been a more comfortable conversation. So how did you find the right people and identify which ones are worth listening to, to help shape that direction.
Marc Stolz
So depending on the type of, of industry, we’ve talked to multiple stakeholders, I think what’s really important is to understand your customers and their pain points. And at the beginning, we had some ideas on what we thought would be great for our customers, and you already started building an MVP, and started shaping a product with some insights that we thought would be really, really helpful. And then we launched a product, tested it with, with some users. And that’s when you start realizing that maybe some ideas that you thought would be great, are maybe not the best for your customers, someone might like it, some might want to push it further. So I think it’s really important to really listen to the customers really do your market research, and kind of start this whole process in collaboration with the people you want to work with. So we did a lot of customer interview calls, especially for the commercial real estate part because we started as a platform for retail, and started getting a lot of traction from that. But we also had the commercial real estate part that came to us. And I was like, we like what you do, let’s have a chat. And then through the customer interviews, we really started understanding what their pain point was for these customers. And then we tried to build a small project or small feature for these commercial real estate customers based on what we’ve already built. And then we will test that again with these customers. So it’s a very different approach where you reach out to somebody just for not trying to sell something, but try to basically have their inputs have their feedback, as then if they have maybe 1015 minutes to jump on a call and you’re currently growing your growing business, you’re trying to to build a solution that will help them make their job better and faster. And most people will take the time to jump on a call and kind of share their feedback.
And then you know, you build that product for them, you get back to them a couple of weeks or a couple of months later and show them basically what you’ve built. And then it becomes a whole different sale because you ultimately solving the problem. They’ve told you how to solve it is build that for them. And then there is almost no reason for them not to not to be on boarded after that. And it’s also puts them in kind of a rewarding position where they see value. And they’ve actually brought that value and contributed in that project. So so a lot of people actually lie To be part of that journey since the beginning, and they usually stick much longer as well. And then you can, you know, ask for some types of referrals to their existing, you know, peers, you know, that it’s, it’s quite easy for them to say, hey, swap to speak to a colleague and be like, Hey, I’ve just worked with a company, they’ve built this amazing tool that really helps me gather that data in just a couple of clicks, you should have a look at it. And, and it’s that word of mouth, that also helps you grow as well and really helps you build a much stronger argumentation and then customer base.
Matthew Todd
Yeah, absolutely. And I think that the process you’ve described, gives you that deep understanding of their needs, but it also, as you say, they’re part of that journey with you, they’re kind of buying into investing in that process. And they’re thinking and working out what their value is, and their needs are at the same time. You are so kind of coming along there together, I can see that that that typically does create very engaged customers that do give you those referrals, and are kind of advocates or champions for the product as well.
Marc Stolz
Absolutely. And yeah, I would, I would highly encourage everyone to, to kind of use that kind of approach. And there’s a great book, I think it’s the lean startup that talks about this build, measure learn framework, to to really test new features, and guide, it’s worked really well for us, it’s just making sure that, you know, we just get the product out there and a minimum of time with a limited budget. Proof that, that what you’re building has, it has a value and it’s consistent. And then and the feedback and then push it for production. And that’s worked very well. And you need to put the right time and and the right team to to kind of get collected feedback and then feed that feed that into the product team, the strategy team in order to grow as a company, I think.
Matthew Todd
Yeah, absolutely. And you mentioned the pandemic earlier, as well, and how that’s impacted, you know, kind of for people’s buying behaviors, and then comparing what people are doing now versus then but in terms of a business built around, you know, retail, commercial real estate, how, how has the pandemic affected, over in itself in terms of, you know, acquiring customers providing value? And has the value changed because of that, potentially?
Marc Stolz
Yeah, so we actually launched in March 2020, which, in terms of timing was probably not the best time. So yeah, right at the beginning of the pandemic, and that’s when, basically, governments were shutting down the economy, people were staying at home. So trying to, to sell fitful insights, when people are at home is a bit tricky. Yeah, so so it, it was it was a tough period for us. Obviously, we needed to make sure that, you know, we could keep growing as a company, but we could also keep paying the bills and turning the lights on. So we’re really focused on basically product development, and optimizing our costs, so tried to cut wherever we could in terms of maybe marketing initiatives, or just just spends in terms of travel and sales, kept the whole team from during that whole period, and really focused on on product development. Building, the platform, optimizing. But also, as I said earlier, trying to get as much feedback as possible from customers, and feeding that feedback into into a product roadmap. And then at the same time, we’re looking at creating momentum, talking about all them as a company trying to push as much as we could, especially to larger enterprises, because sales cycles are always longer and getting getting access to the right person. And that company is always a bit tricky, and you need to you need different champions within the company to to get access to the right people.
So we started this discussion very early on. And the feedback we got was we really like what you’re doing. But right now we’re not spending any money on software, or we’re just making sure that you know, we can keep our own and business running. Let’s have a chat in a few months from now. So it started building our pipeline. And then we also looked at maybe joining a few accelerators. So we joined an accelerator, an accelerator called plug and play, which is, which is based in Silicon Valley, applied to that. And then joined a cohort in in January 2021. That was, that was great. Not only in terms of getting to know other peers that are in a similar, you know, stage and have the same problems. So you really get get get to bond with with a lot of different people that are that are in the same situation. But you also get great traction and exposure towards there. corporates and companies are working with. So yeah, we started doing running some pilots, with companies like PVH, or Ford Ford mobility, we also started working with companies like UNIQLO. So it’s it was it was really interesting to to really have these first pilots. Obviously, that stage was still unpaid. But it was good to get that feedback, understand the use cases and start building that narrative behind what we were bringing what we’re bringing in terms of value, and how data can fit different use cases. For retailers. So that’s been that’s been a really, really good.
Matthew Todd
Yeah, no, it sounds like that was a useful time to get some perspective, I think building that narrative, as you say, is, is incredibly important. And I suppose, in a way, you know, when restrictions lifting, you know, people’s shopping behaviors and travel behaviors, getting, you know, back closer to pre pandemic, I imagine that retailers are perhaps more motivated now, to actually, you know, come back stronger.
Marc Stolz
Absolutely. And, and really, you’re seeing that right now, most companies, you know, are thankfully back in business, they want to strive, they want to see how they can look at attracting more customers. But they also want to see how these customers have changed. And our behaviors have changed as well. A lot of people moved out outside of the cities, with the hybrid, working, working schemes of most companies. People are still saying, outside of the cities, but are they going to come back full time in, let’s say, urban areas, to these kind of insights are really paramount for businesses. And they want to understand how these consumer behaviors have changed. And we can really support them with that. So so there’s a great fit right now in terms of timing. And then the second part would be companies want to have more visibility, in terms of prediction, what’s going to happen next, and mostly, retail, retail has been left apart for quite a long time. We use predictions in a lot of industries. And we actually use it on a daily basis. So for instance, I guess you’re looking at the Weather app every day. And when there’s going to be 60 60% chance that it’s going to be raining, or you’re going to be taking an umbrella or not. These are the kind of of data points that help you, you know, make a decision and be ready in case something will happen. We want to be able to provide similar solutions to the retail world so that they have the, you know, the right tools in place. And NK can take very quick actions based on on these forecasts.
Matthew Todd
Yeah, no, absolutely. I can certainly see that. Yeah, people’s behaviors are ever changing. We’ll certainly that change has been accelerated like with with many other areas of work, as we’ve talked about with other businesses. So I can see how that that ability to predict and introduce more certainty into what has, you know, had a lot of uncertainty. Yes, is potentially very valuable and useful to them.
Marc Stolz
Absolutely. And the approach that we’re taking is that right now, most demand planners or companies that are trying to forecast are mainly using sales data to do these predictions. They’re obviously looking at a few other market dynamics. But having that additional layer of football data, I think is really important because it provides an additional source of data. And it helps you optimize and refine your, your, your forecasts. So so we see a lot of appetite coming from, from various industry to get access to more data. When you see more data is not always good. That’s why you need to be very selective in the types of data that we use. But especially for brick and mortar businesses, like restaurants, apparel stores, or let’s say even cinemas footfall has a tremendous impact on their sales. If people aren’t coming to your store, your sales are probably going to tank. We do see some businesses as well that have both the online and the offline presence. And there is always kind of rivalry between how good are we doing online versus what are we doing offline. Some people will say that the retail is dying, but we still believe that people do like to go to stores to like to have the interaction. I don’t know how it is for you. But I know that especially after the pandemic, I only had one craving, which was go ahead and go into as many places as they could and and really go back to so you know, enjoying a nice meal on a restaurant or trying out some clothes in person and always ordering things online and shipping them back. And and we’re seeing the levels of footfall going back to the levels pre pandemic and sometimes even above that. So there’s there’s there is a strong recovery receipt, it really depends on on, on the industry and their location. But in large cities like New York or Miami, we see the levels are going even even higher than before. So So businesses are striving, they’re getting back into business. But also companies are changing their strategies. They’re looking at a portfolio of stores and looking at the busyness of the stores, maybe some stores that were top performing, one or two years ago, have significantly dropped and some other stores that thought that we thought were we’re not doing well. I’d say in the beginning of 2020 in Suburbans areas are in our striving because of you know, that change in, in, in people’s pattern to to to go and live in other outside areas.
Matthew Todd
Yeah, no, definitely a lot of a lot of change. That’s I can certainly see how that data that appropriate and an analysis presentation of the data as well as the predictive sites. Yeah, can be so massively useful, especially with bigger businesses that are going to have multiple stores multiple locations. And then when it comes to kind of serving those bigger customers, as a relatively new company, how do you make sure that you, you can deliver, deliver, develop the kinds of features that those bigger customers are, are going to need and demand and get value from you know, it’s gonna be quite different to a single shot. As I mentioned, there’s a lot more complexity involved in, in serving those bigger clients. They’re just curious as to how you’ve managed to kind of keep pace with that.
Marc Stolz
Yeah. So our main product is a SaaS a b2b SaaS platform called Almanac where we’ve basically built all the insights for the retailers or the commercial real estate. And that’s what we’ve been pushing for in terms of sales in the last couple of months. But we see that for some companies, having a dashboard is really, really useful. And they want to have that they want to the visuals. But for other larger companies that do have data scientists and kind of a big data team, they want to ultimately just get access to the data. So if you look at basically over and as a company, the core of what we do is the data. So we have a lot of data on a daily basis, we analyzed more than a billion data points. And that’s every day. So it’s a lot of data that we’re storing, analyzing and processing. And the way we’re displaying that on the platform is we’ve carefully selected the most important insights for the retail for the commercial real estate industry. But some companies want to have either just a prediction and they want to feed that into their data models. So that’s that’s kind of pushed us towards being able to to build and develop an additional product line, which, which are data services, I say, and for some companies, we’re just kind of providing that feature. And it’s, for instance, for large apparel companies, that that wants to kind of feed that into their data. And then the first stage to that is just to provide data feeds, or data buckets, and then that’s going to evolve later in an API. But I think it’s very important to be very transparent with the, with the customer, and being able to say, We can do this. And we can do it in this way. But we cannot do it in that way. Most people, especially when they’re growing as a company have a tendency to say they can do everything. And once they say yes, they realize how much work it is and how long it’s going to take to be developing.
So so it’s very important, I think, to manage expectation and, and be very transparent and be like, Listen, if there’s a need for you guys to, to have that we can do it, but it’s going to take x amount of months and X amount of money for you to kind of commit in order for us to be able to build that. That’s the same, for instance, for some of our customers that are asking right now, we’re only focusing on the US market, some customers are asking us, how quickly can you do that in another markets? Could you be able to do that in Canada and Mexico? The answer to that question is yes. But there needs to be clear use case and a clear commercial contract tied to that. So it’s very important to do not start building features, and then not having anything in return. And I guess it’s also very important to prioritize based on on the needs of your customer, making sure that, that feature, that specific request, has been asked by multiple customers. And once you once you start, you know, listing all the kinds of features everybody will have a wish list on Oh, this is great. Can you this? Or can you also that feature? Or can we also input our data, or can we so people will always try to ask for much more than you actually have. But it’s very important to be strict on what you can and cannot do, and start selling which already have, and then assessing what would be great to have in the future, and kind of try to fit that into your roadmap. And then what we’ve also started doing is for the specific requests that come from customers, is kind of have client LED r&d. So we would assess the performance mode assess basically, the request of a customer that it’d be, I don’t know, we need to have this specific type of insights. And we can pull that using our data. But that means that we need to, you know, have our data analyst extra extracted data, building reports.
Marc Stolz
In order to really understand how to best serve our customer needs, I think it’s very important to qualify what our customers want, what’s the problem and how our data can solve that, and in the best way.
So it’s more like a consultative kind of bespoke project that would that would be doing for a customer. At the beginning, that would be very manual. But the aim would be to kind of automate that and then feed that to an end user inside the platform. So we started doing that third part of products, which is kind of custom reports for some of our customers, as long as it fits our roadmap and where we our vision as a company, and also if it fits, basically and covers r&d need. So making sure that the project will not be more expensive than what it actually will take us not only in terms of, you know, data processing data sources, but also man hours. So right now, just to kind of summarize, what I just said is, we’re focusing on three product lines to serve our different customer segments. The first one is the b2b sales platform called almanac. The second one is the data feed. And the third one is everything. That’s custom reports. And in order to really understand how to best serve our customer needs, I think it’s very important to qualify what our customers want, what’s the problems and how our data can solve that and in the best way, and then for each customer, we’ll take the time to see which which solution is the best for them. And how can we help them use our solution and the best way so they can take data driven decisions?
Matthew Todd
Yeah, that’s really interesting. That sounds very similar to what we tell clients as well as you. You’ve got to validate those problems and pain points. First, you’ve got to validate that what you have in mind is an appropriate solution to that problem. And then thirdly, you’ve got to validate that there’s commercials behind that as well that they’re then willing to pay to have that, that problem solved. And like what you were saying about making sure that there is that commercial model. And I think also you described something which is very good in terms of identifying where your core value is. So you’re mentioning the data feeds, to those bigger clients, where they’ve got their own data teams, you know, I know other businesses that would not take decisions like that, because they’re so protective of the whole user experience and didn’t want to let that go, because they’re afraid of, you know, losing control in some way. But if you recognize that none of the data, the insights are the core of what we do, then there are a multitude, the best way to deliver that to different types of consumers and different segments can and should be different.
Marc Stolz
Absolutely, absolutely. And our role is also to educate our users, we, we want to make sure that we’re seen as the go to platform when it comes to predictive footfall analytics. And that goes by making sure that the quality of our predictions are very, very strong. So we want to make sure that we’re doing everything to make sure that our insights are accurate and help our customers take these decisions, because the foundation of what we do is accuracy, when he, you know, how good is it to have insights and predictive insights, if the accuracy is very bad, we want to make sure that we’re guiding our consumers with the strongest accuracy levels as possible. In order to do that there’s there’s a lot of different processes, but we’re currently working on is we’re partnering with one of the largest company in the US that provides security materials to stores. So mainly also cameras, so that we can actually have a ground truth validation. So how can we make sure that our data comes from geospatial data actually matches with actual in store visits. And in order to do that, we were combining those different data sets. So through the, through the cameras, we are able to understand how many people are going to store up to a 99.77% accuracy. So we actually get the actual number of people visiting our store. And then we’re correlating that with our data, and then use this data from more than 125,000 stores across the US to really scale our models and learn from it on a daily basis. So that gives us a very, very powerful tool, that right now, nobody else has done in the industry. And I think that gives us a clear competitive advantage. And really helps us achieve our mission to become the most trusted source of US data.
Matthew Todd
Yeah, I think that’s really interesting, and a great way to use partnerships to, to really improve the quality of the products. I think, you know, some companies can be a bit too obsessed with bills versus, you know, kind of by your partner. And I think it comes down to what we’re saying before, recognize where the core value is. And you know, by partnering, you’re not going to turn them into capacity, you’re working in partnership. That’s what they’re there for to support what you’re trying to achieve for your customer segment your use case.
Marc Stolz
Exactly. And there is a variety of partnerships. There’s data partnerships, there is sales partnerships, there are strategic partnerships, marketing, partnerships, wherever we see an opportunity, especially as a growing startup, we’re trying to secure that. And it’s important to have these logos, these big company names on your website, have these testimonials, because it helps you sell ultimately, if they see that you’ve partner, I’d say for instance, we’re partnering with Google, that gives confidence as well. To to, to the end user, the customer ultimately.
Matthew Todd
Yeah, absolutely. It’s all about building, building that trust and credibility with that audience.
Marc Stolz
Yeah, absolutely.
Matthew Todd
And in terms of, you know, anything else, I think we’ve covered quite a lot of really, really good points about kind of really kind of understanding that customer and understanding where the value is for them and some really good insights in terms of how you’ve then been able to take that that fall into kind of growing the products product line and and platform. Is there anything else kind of any other mistakes or learnings that you want to get across to to our audience today.
Marc Stolz
Um, yeah, well, I think all of what we’ve accomplished would have never been possible without our team. And I guess, you know, as a company, you spend a lot of time hiring, making sure we have the right structure in place, and, and making sure that you’re covering and attracting talent in the best way. And, and I guess, I mean, it’s, a lot of companies are kind of advertising this, but I would say it’s really important to, to really hire slowly. Because it takes time to find the right talent, it takes time to make sure that not only they’re the right technical fit, and they’re perfectly capable of doing their job, but they also need to be the right fit for the company. And, you know, obviously, we, we hired some people that were either not performing well, and, and, you know, they, even though they had a great CV, at the end when when they start working and, and how they day to day tasks, it doesn’t work well. And then you have to split ways. So that, you know, puts you back to square zero, where you have to start the whole interview process. So you’re not only losing time, but you’re also losing money. And you’re also in some way, losing a bit of confidence from people on your team. If you systematically hire people and you know, me to let them go after a couple of weeks that kind of has has a strong impact on morale. So I think it’s really, really important to to structure Well, interview process, make sure you have the right people, because these are the people that will help here, build and grow. Without without this right team, you won’t be able to build a successful company.
Matthew Todd
Yeah, I think that’s really, really good advice. And when you’re hiring, you’re not hiring for the short term, you’re hiring for the long term. And too many people can make short term decisions based on the candidates, they’re in front of them. So not Should we hire this person? Or who should we hire? But is it is that kind of, okay, we’ve only got five people. Which one is the best or the least worst? In some cases? Rather than? Are they perfect for this, this role?
Marc Stolz
Absolutely. In that situation, if you have three people, let’s say in the final round, but you’re still not convinced, then I would highly recommend to keep interviewing people. And don’t don’t think decision based on the fact that you only have a certain pool of candidates, if they don’t fit fit your requirements, then take more time to hire them. Because most people think, Oh, we have so much work to do, this person will just do fine. But at the end, they don’t do fine. And you end up spending way more time trying to support them trying to to help them grow, and then it doesn’t work. And again, you have to start. So really take time hiring and make sure that they fit the team. It’s it’s super important.
Matthew Todd
Yeah, absolutely. I completely agree. And in terms of, of where we are now, then and, you know, as we go through the rest of the year and onwards, what was next? And for the growth of evolving? What are the things you’ve got going on? Where do you see it going?
Marc Stolz
Yeah. So right now, we’re really focusing on on our, on our growth. So bringing in as many customers as possible, making sure we’re onboarding them in the right way. And our customer support team, you know, guides them through the whole process, we want to be at around 100k MRR by the end of the year. And then we’ll look at during our Series A and probably summer 2023, where we’ll be looking to raise between 10 and $15 million. So we need to kind of show that growth in in these in these couple of months going from you no traction to having a first paying customer to really having a consistent, recurring customer base. And we are at that kind of hockey stick growth curve where you know, it’s always the chicken and the egg at the beginning where you want to have customers but customers want to join only Hey, if you have use cases and different things. And this is very hard and so prominent all startups will have. But once you’ve passed that stage, and build these use cases, it becomes much easier to to onboard these customers and show them the value of your platform. So it’s going to be as I said focused on on sales growth growing up with the team and then we’re going to be focusing on raising raising our Series A.
Matthew Todd
Cool awesome no Sounds sounds very exciting. road ahead. And yeah, I look forward to hearing more about that bat growth as I’m sure we will as as we go through the kind of the coming months and into next year. So yeah, I just want to say thank you for for taking the time today to, to talk. I’m sure there are many other things we could dive into. But I think it’s a good place to call it now. I think there’s a lot that people can can take away from this conversation on kind of growth on on value and, and approaching customer feedback and development the right way and going after the right kind of customers I think has been really really useful. Interesting to me, you know, talking to you today and I’m sure will be for the audience. So no thanks again for for taking the time.
Marc Stolz
Thank you so much for inviting me today. And thanks for listening.
Matthew Todd
Thank you for joining me on this episode of Inside the ScaleUp. Remember for the show notes and in depth resources from today’s guest. You can find these on the website insidethescaleup.com. You can also leave feedback on today’s episode, as well as suggest guests and companies you’d like to hear from. Thank you for listening