Xeneta Revenue, Valuation & Funding (2024)

hello everyone my guest today is patrick berglund he's the ceo and co-founder of oslo based zanetta the leading price comparison platform for containerized freight transforming the shipping and logistics industry with data analytics he's a logistics and tech enthusiast possesses a true passion for modernizing business processes related to logistics procurement and the supply chain patrick you ready to take it to the top yes beautiful all right so tell us about this company and again this is one of those things which i love because people might call it an unsexy area which means there's a lot of opportunity right so paint a picture for us what does this tool actually do well hey come on container shipping provides 70 of global trade it's a 200 billion dollar industry where they buy and sell the actual transportation not the cargo value inside right but these companies they they buy and sell something that looks like a commodity but is missing proper transparency of price development right so imagine you were buying something that you know prices shifted all the time up and down one time you paid 1 000 the other day three three and a half thousand so very volatile and you bought a whole lot you bought for let's say 10 million dollars or 100 million dollars and you were always questioning do i have a good rate do i have a good price is this the right spend this is what companies are facing whether it's automotive companies chemical companies fmcg whatever industry they all move their product in these lego boxes and it influences all of us and the big question these big spenders have is is this a justified price and the way we come at this is that hey let's just collect everybody's price and then we aggregate it and they can see how they perform yep so first off what's the ins and by the way are you pure place sas company do you is it a sas model yes okay so i want to get in that second but first how can you convince all the people that are doing all the shipping to give you all their data there must be some incentive structure you've set up yeah well you have the initial chicken and egg problem yeah because giving a proprietary contract away to a third party like us in the beginning it makes no sense but as soon as you know that this third party have all the other contracts that will make me smart in my negotiations with my suppliers then that's the incentive okay well so wha i don't understand that again if you told me nathan i have all your competitors data now i need your own you're basically saying you'll also give if i give you mine you'll also give me my competitors no i don't give you competitors what you're questioning is do your 50 million dollar is that 50 million spend competitive are they justified is it plus market 20 or is it minus market 20 you don't know i know because i've collected all the pricing from everybody else so that i've aggregated that and said here's the average okay you're giving averages you're not saying you're cheaper or less than company y or z precisely because that's proprietary confidential information so now you never know what adidas is paying nor that i'm saying anybody's using the platform right but i can show you the spread of the market and the average and then i can show your own yeah interesting okay i imagine my audience is very number driven educate us real quick i mean they see these shipping containers and we're in this trade war and so this is like top of people's minds right now like what does it cost i mean on average to take one of those shipping containers give me the size dimensions like go from like new york city to paris yeah that's not a very high density trade give me a high trade yeah let me give you an example so so a 40-foot container is like a semi trial trailer in terms of volume so it's a lot of cargo that goes into one of these boxes one vessel might carry anything from 10 000 to 20 000 of those boxes so they're massive right now for the u.s trans-pacific would be the biggest trade right so they would go from shanghai hong kong tianjin or whatever port in far east right into west coast and east coast of u.s so shanghai to long beach would be a very big trade right and due to the trade tariffs spot market rates going skyrocket high because companies want to rush the cargo in before the tariffs comes into play right so capacity gets scares and moving a box from from let's say china main ports has went from let's say fifteen hundred dollars to two and a half three thousand dollars right from one box all right and then you can there's there's several vessels every week going fully loaded on that trade right more or less could be at some space capacity and so forth right do you get volume discounts if i say okay i'm going to ship 10 000 on the thing can i get my cost down to like a thousand per container that's what makes this market so interesting from my friend of you right because let's say walmart moves a million boxes here just to give you some numbers right well target moves 250 000 who knows right they have different procurement power now the cool thing about this is that you can find a big volume company that expects to have the best rates in the market to have a mediocre price because they went to market at a point of time when the market was high and this smaller guy nailed it and went to market when the market was down right and this is so it's sort of non-comparable because of the volatility of the market and this is what makes it consistently relevant to have this data available for these businesses interesting this is almost like uber right but but you're getting fares updated real time based off supply demand well not fully because we're not this is this is really where it becomes different i'm not offering the actual booking or the actual trade just the data just the data from a procurement point of view because you got to understand the cargo doesn't go from port to port it goes from door to door yeah so you know putting that together is like a 16 stakeholder on average orchestration right in order to have the cargo moving i'm just saying there's a very volatile component on the deep sea here in the middle that we provide pricing transparency on got it okay let's dive into your model here i want to get more of your story patrick i get the product now i get the market it makes perfect sense to me um what do people pay you for this let's say again we won't say yes or no on in terms of if nike is a customer of yours but let's say as an example they are what would a company like nike pay you well anything from anything from 20 25 000 a year to almost say 400 000 a year and why would someone be on the cheap side of that versus the expensive side what do you price against so different products different market intel and amount of users amount of seats right okay is the amount so i'm really interested in the in the data-based upselling so number of seats is one of them is are there any other kind of number based things like like number of data points you're giving them or things like that yeah so we can provide more granular information and insights that relatively speaking are more valuable for some of the high value volume buyers right an example is let's say that you want to look at the market average development between sean and hambury that's fine but i could also potentially aggregate all the data per carrier saying that this this shipping line has this spread between a to b whereas this other shipping line has this spread in their long-term contracts and imagine if you buy for two hundred thousand dollars to 200 million dollars a year sitting with that intel while sitting negotiating on the other side of the table with your suppliers you have incredible leverage because you know how they perform relative to their competition right yeah and you know like the the season where you get better prices is the fall so you'll wait to negotiate until the fall when you know you have leverage or something like that yes for instance now there's also other things we do api deals and stuff like that where we can offer them more access to our data which you know they're basically buying our asset if you set up an api right so that comes at a higher price ticket as well okay put this on the timeline for me when'd you launch what year we launched in 2012 i'd say okay 2012 and then from 2012 to today how many customers have you scaled to a few hundred okay couple can we say north of 200 but south of five yeah okay good and how did i mean where was your head in 2012 i mean what what possesses a guy like you to go you know what i want to go try and get 16 people from door out to door or door in their door out to all degree and get the data and jump in what were you doing uh i used to work for a freight forwarding business called quinongle you're probably more familiar with ups or fedex sure sure ginongo has 70 000 people employed and they're the world's market leader when it comes to ocean freight shipping it's a massive company and one of the things that annoyed me is that i kept on selling to my clients at very different prices all the time and they always ask me is this a good price how do you justify your price and you know think about other commodities coal grain soya beans coffee beans uh gold silver electricity you'll find indices that that shows you the price development and you can then relatively say that you know here's my price and this is the market this industry had no transparency and that's why i'm so flabbergasted you know it's it's as i mentioned 70 of global trade and it's it's 200 billion dollars worth plus minus that they buy and sell for every year without any proper transparency and that's what we really wanted to solve initially yeah right yeah and coming to the industry that's very easy to see i think but it's a massive chicken and egg problem that you're dealing with for the first few years patrick have you bootstrapped the company are raised we raised 30 million dollars up until now and um uh probably gonna need some more down the line what is the next right amount for you to raise would you say oh it really depends on how the company develops and how the market develops right those go sort of hand in hand right is it is it right for taking the way it looks like now do we get the right traction but next probably would be around probably 20 30 million dollars and what would you try and aim at in terms of like a pre-money value you're talking like 80 90 100 million something like that on the next round should be north of 100. okay you want to get north you think you feel good about getting north of 100 million pre-money value yeah if the company is growing quickly enough from a proper revenue base then yes that shouldn't be and you think this is like a q4 kind of thing or a q1 20 20. i think for the first time ever we're probably going to be in that situation q1 2020 where we can choose whether to raise or where to you know scale organically yeah no that's that's obviously a good position to be in um help me understand a little bit more so raise 30 million bucks um what's the team says today how many people we're 85 people all right so about 50 in oslo 50ish then we have offices in hamburg and new york uh smallest team in new york about six people working on scaling that um 15 or so in hamburg but then we also have some people sitting in remote in like frankfurt barcelona amsterdam copenhagen berlin montreal and so forth very good and you mentioned that this team has been able to drive like healthy revenue growth i mean are we talking are you still at able to do 100 percent year over year or where are you today would you say we're aiming at doubling and doing 100 this year yeah did you do that historically from 2018 to 2019 yeah we've done we've gone quite close to the sauce benchmarks numbers of what are you talking about three x three x two x two x two x quite close to that yeah that's helpful that's okay that's good fair enough all right um talk to me here i churn can kill a sas company right so so how do you think about churn and how and what are you at today well yeah this is sort of what we learned as well in the beginning we sold to everybody yeah and it's it's not an ideal customer profile even right so we sold to anybody who reached out we've we have deals with financial institutions some of the biggest ones in the world we have some of the most renowned consultancy businesses and you can see some of the brands like that are public like nestle unilever lenovo and so electrolux and so forth on our site right so we work with a lot of brands that are well known but we shouldn't have sold to everybody because not everybody has an organization that allows you to leverage this kind of data from a procurement point of view to extract the value yeah so what we see now is that we have very healthy turn numbers on what's supposed to be qualified good customers but we've let out a lot of these smaller volume players that we should never have target with our initial value proposition we're also developing value proposition networks for more of the loan yeah by the way that's fine that's why people will measure revenue churn versus logo churn right so revenue churn is better if you're churning out lower arpu customers so over the past 12 months what would you say your gross revenue churn was or a range is fine if you don't know exactly yeah 10 10 15 gross revenue but then below five nets okay so what do you mean below five net meaning you're adding 10 back in expansion yes okay so your net revenue retention annually is somewhere around 95 percent right that's great guy man you're so close how do you get it over 100 this year that they will be able to expand much more on our existing user base these companies they buy ocean freight for for enormous amounts of money and and we were there to extract this i was just going to say that if you said nathan i want you to leave my next strategy meeting i'd walk in the room i'd say guys we are not allowed to add any more customers the only other driving growth is expansion i want us to think about how we're driving expansion because you have a price point relative to what they're paying for this stuff is like so little yes i fully agree and and that message is vividly clear for all of us this year yeah good so i get one person in the company right i'm i'm i'm kidding i'm kidding patrick you're dropped off sorry i was joking i said good so i get one percent of the company right [Laughter] no i'm kidding all right talk to me real quick here i know we just talked about expansion but in terms of adding new customers what are we what are you happy at in terms of payback period right now what i'm happy about in terms of payback period i i don't think i am happy about payback period customer high customer acquisition cost i think it's uh 15 months or something like that and you're not happy with that why because i think i think we should be able to pull in more at a cheaper cost period like full stop i think we're wasting wasting resources wasting money as well yeah in how we acquire customers but i i do care more about the evolution of things than actually where we are same as with churn like what's how which direction is it developing relative to the initiatives we're putting in place that is much more important to me than where we are at now right sure yeah so it's trending payback period is trending the right direction when now that let's say you said earlier your accounts are called minimum twenty five thousand dollar acv so to if you're gonna spend 30 grand for a 15 month to get that 25 grand on acv where are you spending that 30 grand is it inside sales commissions or what well not a lot of inside sales it's our entire engine is outbound right okay we get very small portions of business inbound like the average let's say global head of logistics wouldn't even google uh concept that's ours it's very difficult to sort of reach them and hit them they're not even uh we've spammed so many of them without even having like what's the title you're targeting what's like when you search on linkedin navigator what's the title yeah that typically would be global head of supply chain global head of logistics procurement stuff like that so it's not it's it's very it's a nice target group to go out but it's very difficult to find the right ones and usually it's a consortium of multiple people in multiple locations like asia us and europe doing a collective initiative right so that is also why it's expensive to acquire them because you you gotta you gotta you know find the champion and then uh you gotta get engaged with all of them and usually they have like a global consortium once or twice a year that's where you have your opportunity right you have to strike very good um last question here on aggressiveness right so so you obviously raise a bunch of capital i assume you're burning cash right to drive growth yes obviously as a ceo how aggressive are you being with that i mean are you talking like a negative like a hundred grand a month in terms of in terms of net burn or where are you at no we're burning more than that we're burning i'd say we burn three 400k maybe a month and in your opinion is that kind of good or bad it's fine it's fine i mean what i care about is like what's the end of the lifeline's sort of looking like and as a as i think we'll be in a position to decide whether to raise or not when we go out to one 20 20 right then then i think it's in a healthy sort of direction on the burn as well right and just around all this stuff out right so 25 000 minimum acvs and you know call it north of 200 customers that means you guys are doing north of kind of 410 000 per month right now at this point right yeah yeah no problem you said earlier you had a couple hundred customers 200 at a minimum and you said earlier also your minimum acv was 25 000 so 200 times 25 grand would mean you're doing about 416 000 per month or a 5 million run rate yeah you're quite quite close okay right around there and that means about a year ago you were about two and a half million run rate you're doing a bit more just to be honest okay and you're not too far off okay very good well by the way it's always good if my estimate's a little lower because then when people call you you say actually we're doing more than what i said on nathan's podcast right that's good all right let's wrap up patrick with the famous five number one what's your favorite business book [Music] at the moment i'd say the hard thing about heart things number two is there a ceo you're following or studying oh several but i'd say i i actually lately have leaned to some of my industry peers [Music] yeah well my former boss in berut is absolutely exceptional in his thinking about the industry and and how to deal with the ceo of which company well that's actually true he's the global head of air freight for queen inaugural okay so okay number three what's your favorite online tool for building your company uh inside squared maybe but it's yeah number four how many hours i sleep to eat every night sorry how many hours i sleep to get every night five to seven okay and what's your situation patrick married single kiddos married two kids okay here you go and how old are you i'm 37. last question what do you wish your 20 year old self knew now you got to be patient with people guys be patient with people again he launched zanata back in 2012 it was now serving two north of 200 customers doing north of 5 million bucks in ar they help bring transparency to shipping rates which drastic you know go you go up and down a ton ranging from you know going from china to california might be between 1500 and 3000 per 40 foot shipping container but that again changes by season he's being transparency up to the markets people can make smarter decisions they're putting hundreds of millions of dollars through this channel each year so it makes a lot of sense burning caught four hundred thousand dollars per month in cash 30 million dollars raised team of 85 in oslo new york and remote locations 95 net revenue retention hoping to get that over 100 with some expansion stuff this year 15 month payback period as they look to continue to scale patrick thank you for taking us to the top thanks a lot appreciate that very good summary