How Coveo CEO Louis Tetu grew Coveo to $137M revenue and 1K customers in 2024.

hello everyone my guest today is louis tatu he is the chairman and chief executive officer at coveo prior to the company lewis co-founded talio corporation the leading international provider of cloud software for talent and human capital management before that he was president of ban scs the supply chain management solutions group of ban and global enterprise software company luis are you ready to take us to the top oh absolutely okay tell us about coveo what do you guys do and how do you make money well coveo is uh is i guess a uh fast growing vendor in an area named insight engines and uh essentially what we do is uh intelligent search and uh and machine learning driven recommendations so we power a lot of the websites uh that you know um from companies you know customer service intelligence e-commerce recommendations uh things of that nature okay and how do you make money here is it a peer play sas company we are absolutely a purely sas company so uh we're in that we're we're a b2b enterprise software vendor and uh we we essentially sell software that makes our clients better and what does the average customer pay you per month uh it ranges anywhere from uh at the very low end i would say 50 000 a year to several millions a year for the the largest uh brands i don't want to go down every kind of customer cohort but if i mean if i forced you to an average would you say it's more around the kind of fifty thousand mark or more around two hundred thousand uh acv annual uh recurring revenue for the software when someone when someone pays you that what are they what are they getting is it a number of search queries per year or what are they paying that's right exactly they're uh they're basically buying this by the drink uh so we enable search queries we enable content recommendations that allow people to uh self-serve uh buy more learn more um get what they need in context uh so it's it's basically uh typically tiered to volume yeah and louis when did you launch company uh the company was launched uh a little more than a decade ago it originally started as a search company and then we added we took that company in the cloud i was originally an investor in the company when i ran to leo and uh and then loved the company so much that i joined so we subsequently took the company in the cloud got the company into analytics and then five years ago started investing aggressively in uh in machine learning and what do you add today in terms of how many customers you've scaled to we have about a thousand uh installations a little more than a thousand um actually uh mostly in the high-tech sector financial services and uh in manufacturing and those are all paid just to be clear a thousand paid costs those are all paid those those are all paid we are pure play uh b2b uh software vendor we're actually the uh in the space known as the uh gartner magic quadrant uh um uh uh top right or right most vendor uh in in and benefit from uh from a lot of recognition uh for people who need really advanced uh contextualization and uh and uh very powerful recommendations uh on their on their digital experiences nowadays you said a thousand customers you had just said about a two hundred 000 ac that would put you about 200 million a year right now in revenue is that accurate we don't disclose revenue uh we're we're private company we recently raised an additional 125 million uh from a large palo alto uh investor uh we're we're obviously growing very fast in the range of about 50 uh a year and uh and you know this is this is uh we're not the only company anytime any time you talk about machine learning anytime you talk about personalization of digital experiences uh you know driving more call deflection more conversions that's obviously a very hot topic right now just to be clear again i don't want to you don't have to disclose revenue numbers but i'm just taking two numbers you gave me i want to make sure they're accurate a thousand customers and two hundred thousand dollar acv if i just multiply those why would i why would those not be accurate the 200 the 200 uh thousand they see obviously a company like ours has a history so you know we've not always been at this pace so the solution pollution portfolio grew uh you know many companies today use coveo in a broad range of applications they'll start uh by putting coveo on their customer communities on their self-service they'll go in their contact center and we'll do their websites their e-commerce uh so there's a there's a much broader range so the deals have had a tendency well more than a tendency the trend has been that the deals have grown quite a bit over the years resulting in in obviously a very healthy revenue the company is about 300 employees today so you can you can pretty much do the math what math the math around around uh what what's you know what scale what range and scale we we operate at but we do not per the investor desire we do not disclose revenue yeah so just i want to make sure i understand what you just said clearly um you have a thousand paying customers historically your price point was much lower that average you gave me was not an app was not an average of your current customer base it's an it's no it's an average of the sales i would say we've made over the past uh two to three years more uh more recently obviously as any as any software company a decade ago the company started very small acquired smaller customers and then with a smaller portfolio of of solutions and then as we grew the platform we we we obviously inherited uh much larger accounts uh the nice metric i think about coveo is that um we kind of land and expand the customer giving us a dollar today will give us an average of a dollar 58 in two years from now sorry a dollar fifty two and a dollar dollar fifty eight fifty about two years from now so there's a there's a very good set of economics associated with the solutions we sell and uh that's obviously why we're enjoying a lot of growth yep um i won't push you any harder on this than this last question have you passed a hundred million ar at this point uh uh we're again we don't provide any more indications than that do you think you'll cross that this year is that a good stretch goal we're across this uh uh and and much more uh very imminently okay that's great and why do you say much more you just look at your pipeline and you go wow this is a healthy this is a space uh i think i think nathan uh um you know the uh machine learning uh in the whole area as it relates to the whole area of personalizing uh digital experiences driving more relevant uh digital experiences so as to convert uh whether it's sales or service or so on is an extremely hot topic right now and and really a revolution and so there's a lot of value being created so for us uh you know the the uh the performance of a company is is intimately linked to the value uh the set of economics that that we can drive for our customers and that happens to be quite significant we power uh the app exchange uh you know at salesforce and uh and uh you know uh we're embedded within adobe photoshop and uh you know we power a lot of the self-service uh sites of a lot of the software companies got it you know louise i think a lot of economics that drive that growth right now and that's what makes the company very exciting that's a great product i i think the audience and myself i totally understand i think where the products coming from i see the value walk me through some of the other economics here you mentioned earlier you've raised additional capital how much total have you raised to date uh we've raised a little in excess of 150 million uh to date uh and and obviously that's to fuel uh organic growth we're growing at about 50. that's been that's pretty much has been been our steady growth for years so just to be clear on that 50 percent you mean if you're close to 100 today you were doing call it yeah you're doing call it 70-ish or something like that about a year ago oh i've lost your last sentence probably internet uh yeah sorry lewis can you hear me now yes sorry all i was saying is if you're imminent you said quoting you imminent uh near the 100 million mark you're saying 70 50 year over year growth so call it something around 70-ish or 65-ish million a year run right a year ago i again uh you you can make your own math i'm not i unfortunately nathan i wish i could tell you more uh i'm obligated not sorry you're frustrating you're frustrating me a little bit because i'm not i'm just using your words yeah you said imminently a hundred million i'm not i'm not i'm not making anything up i'm just using what you told me so if that is true if you and and fifty percent you over your growth is true that would put you at around 70 million about a year ago why would that not be accurate uh because there might be ways that the company is structured but uh but but you're in the range okay fair enough good we'll move on from that um economics wise it sounds like you've built a great engine in terms of driving expansion revenue from a dollar to 1.58 over two years on customer accounts where is most that expansion happening and what what pricing axes well what happens uh nathan is that customers will engage us on a very specific use case so uh you know a lot of a lot of them concerned about self-service call deflection bringing more cinder and and relevance and immediacy to consumers and and customers and as...