How Radius CEO Lee Everett grew Radius to $5.9B revenue and 150K customers in 2023.

hello everyone my guest today is joel carrosone he's the ceo of company called radius the first b2b enterprise customer data platform joe holds a wealth of knowledge on and a passion for the cdp space and was one of the original architects of radius unifi the first ever fully flexible b2b cdp bringing the new solution to market joel are you ready to take us to the top i'm ready all right so first off help us be really prescriptive here on kind of the definition of or how you define b2b enterprise customer data platform what's that mean for sure yeah i mean i think cdp's have been around for quite a while now it's more synonymous with the the business consumer side about a year or so ago i mean radius has been in the i would say the b2b uh customer data space for a number of years before cdp's kind of got hot on the b2b side at the end of the day what we're doing is we're taking through either native integrations or through an open api that we have available ingesting merging matching normalizing customer data whether it's from first-party systems like crm or marketing automation or third-party systems that they're buying data from say done in bradstreet or info group or some of the other major players and basically leveraging our infrastructure uh to create that single source of truth for that single customer view with the idea that you can then um pump that that that kind of single source of truth out across the organization so it's not just for marketing but for marketing and sales and ops and even in i.t for data um you know analysis or um or data science so help me understand single source of truth is an interesting concept in the data space and the reason i say that is because when i talk to so many of these providers ranging from small sub 10 million ar players all the way up to 100 200 million dollar range it's very incestual kind of everyone buys everybody else's data and it's hard to understand who truly has a moat around the data set so so when you're capturing this data is it unique data that nobody else can get a hold of yes our model is it's based on two different kind of two different approaches so one is we do have our own core data assets so radius has its own proprietary b2b dataset uh domestic only today we cover approximately 18 million businesses in the u.s and summer neighborhood of 25 to 30 million contacts uh we've got partnerships we just announced a big partnership we're doing some co-selling with the folks over at dunn and brad street so the dmb global file is part of our ecosystem as well but the nice thing about our model is that it is somewhat of a consortium so clients that are working with us the you know enterprise clients we do have some ability to leverage the data that their sales and marketing teams are generating as part of their normalities to do data validation standardization even even in some cases suppression so it is a crowd-sourced type model we're not doing enrichment on it but it's more from validation and suppression but it's leveraging you know our customer base uh comcast sam's club first data you know large large enterprise clients with large sales teams and large marketing team so they're generating a lot of exhaust data as part of just normal business processes so that's our moat at least the way that we've defined it today is that that network contribution side of the business so joel how might how might exhaust data or we'll call it sawdust at the sawmill from first data influence the value that customers like infusionsoft get from radius yeah for sure so i think the usually the use case that i go to pretty quickly is let's assume that you've got you know an eloqua or a marketable instance that's got 10 million contact records in it you know you can leverage uh you know there's a lot of email validation providers but there's a subset of emails that are just not verifiable right the the email admins go out of their way to make it very difficult to um to be able to test those but you can imagine when you have a large number of customers that are all marketing to you know different populations you're going to get some overlap so what we're seeing is a you know an email campaign that may go out by comcast there's going to be a population those that are open there's gonna be population that bounce within 30 minutes of that balance happening it's available uh for our purview and then we can go look across the customer base and say who else has this email address it's bounced let's go and actually scrub it interesting you can leverage that type of exhaust it works not just for emails but for phones um we help on the ranking logic because you've got you know n number of sources that are available within our ecosystem um as well as what the clients bringing on board you know being able to choose the right revenue choose the right head count for that client that exhaust data becomes extremely valuable if their sales person is putting in the head count of the revenue you know you have potentially can make some more assumptions on the machine learning side that that number may be better accuracy than something that you got from six months ago it looks like you guys are serving a pretty wide cohort of customer show but if i forced you kind of into an average just so we can focus the discussion what would you say the average company would pay per year for this kind of data set so we do we sell into three different uh tiers so we've got a mid market uh offering it's typically in the you know the 50 to 60 000 range annually that's correct yeah it's a sas product uh we don't charge for data so when you purchase our platform as part of that you get unlimited access to our standard data offering so that 17 million business uh data set is just it's kind of a free a freebie that we give away as part of the relationship uh the second group they're going to be the the enterprise clients uh somebody within say 750 employees or less um that one you know getting to the you know the 100 to 200 000 range and then we have some that are you know that exceed the 2 million acv yep that's great and is there any cohort that you have concentrations in or it's really fairly equal yeah i would say the bulk i think 80 of our revenue comes from our top 20 customers so it's fairly well concentrated they're large strategic deals multi-year in most cases and then we have a you know a decent volume in that mid market um mid market 500 to 750 range yep fair enough put this all on a timeline for us when did you guys launch the company and help me understand your involvement uh were you one of the early founders or you were kind of leading product at the beginning and now your ceo how's that all work yeah it's uh it's been an interesting journey um i joined the company about three years ago on the product side my background was in more on the on the data data space so i came out of healthcare data enterprise data management for one of the boston hospitals uh so i was actually more interested in some of the data challenges as opposed to just like the marketing and sales aspect of what we do at radius so joined the company three years ago on the product side um with vp of platform for a number of years and then uh uh moved into a cto role almost a year ago now um and then over the last year or so darien and i who founded the company um have been talking about you know what it would potentially look like for his transition he was looking to move more out of the operational side of the business he's now moved into chairman of the board um as of the last couple of weeks when i transitioned into the ceo role mm-hmm and company was founded in 2012. companies found in 2012 yeah the company was there's two there was an initial company that was more of a data provider called fwix and then that was uh that after one of the i think the series a they um they rebranded as radius and that's kind of the path that we've been on since and total capital into the company today how much have you guys raised about 100 million okay 100 all equity or is that some of that debt uh so some of it was debt but vast majority of it was equity okay were you there when the decision was made to use some debt uh i was not actually so that happened um trying to think i was at the company but at that point i wasn't involved with any of the fundraising got it and i was gonna ask strategically why that dinner didn't make sense but we'll skip that for now um and focus on things that you might be closer to so okay good so you joined about call it three years ago and what have you guys scaled to today in terms of total customers using the platform so there's around 100 customers today um as i said the bulk of the revenue comes from the top 20 logos yep yes 100 customers yeah so this is very much kind of obviously you know high touch uh high rpoo kind of accounts what's your team breakdown today and what does the sales organization look like yeah so team the company is around 75 employees right now sales is around 20. yep that's broken down we've got a sales leader there's three rvps that cover different territories um they've each got you know a handful of people that's just a total sword size around 20. engineering is 23 today combination of folks that work on either data engineering data science and then we have our platform team that are writing the apis and some of the um the microservices as part of that and where is everyone based on san...