How Spoonshot CEO Kishan Vasani grew to $480K revenue and 20 customers in 2019.

hello everyone my guest today is kashan vasani he has worked in the food tech industry since 2011 he's the ceo of techstar's back taste ai business spoon shot their food brain predicts consumer tastes and food trends he previously worked in two leadership roles over 3.5 years at just eat prior to this he founded a digital marketing agency okay shawn you ready to take it to the top sure all right so tell us about spoon shot uh what the company does and then what's your revenue model are you guys a pure place sassa company or no well we have a suite of products um across the food domain tackling different ear problems all of those problems go up to our kind of our vision what was the vision problem which is essentially around helping people have better experiences with food so everything we that's where we kind of have that passion we want people to enjoy everything they eat every experience they have with food so we've come up with a different number of solutions one is a recommendation engine for the food service industry hospitality industry and delivery platforms we have a front of house restaurant tech product which is called guest intelligence and that helps people understand or restaurants understand what's going on in real time in their restaurants and then there's our fmcg or cpg product which is helping large manufacturers around product innovation by understanding trends early okay so just because we don't have time to go down every single product kind of rabbit hole here are any of these a sas product do you bill any of these a monthly recurring um so two of them are but let's talk about let's talk about the um what we call it we're launching spoon shot genesis next month that's the one we should talk about which is the cpg product and that's a pure sas model okay which of the two right now though are sas uh the recommendation engine okay so you have taste intelligence personalized recommendations and guest intelligence you're saying the personalized recommendations engine that is a sas model yes okay so because the show obviously is focused on sas i want to double down on that here for a second and then talk more about what you have coming up which is genesis it sounds like um so let's start there personalized recommendations help us understand um again where where are restaurants using these recommendations are they actually in the restaurant or pre-restaurant where are they so there are anywhere that there's a in like online or digital interaction with a restaurant or a consumer right so it could be inside their mobile app it could be in their website it could be at a self-service kiosk any kind of digital interactive point of sale essentially okay but it's obviously mostly tailored for online and what are people restaurants i guess paying for this on average per month or per year would you say so it's probably around the two thousand dollar mark per month is is our sweet spot um it really depends on the size of the the brand they were working with and of course how much more value we're adding size based off size based upon the volume of for example transactions they might do etc okay so it's all about making sure that we always say the technology should pay for itself so they're really feeling the value and not it's a they're getting incremental gain but for us recommendations really about the trust factor yep okay good so it's based off number of transactions not number of staff or number of seats or number of locations correct so the difference here in our sas model is that we choose a number with the with the customer up front after because we have a 60-day pilot model where we test out the technology with them and show them value up front and then we pick a fixed monthly subscription amount based upon the 60 days that we work with them okay well if they use your software to grow their business say in three months you basically have killed your ability to drive expansion revenue because you have a locked in fixed fee it sounds like for some period of time why would you why would you agree to a fixed fee because of the nature of this particular product right we want people to not worry about exactly what how many api calls they're making and stuff like that so that's why we have the trial up front so we understand not just what they're doing because the pilot is or the trial is usually like a certain percentage of their traffic or users or whatever it is but then when we discuss with them the actual the annual deal we talk about where they're planning to use it and how much they're planning to use it so it's a combination of the value that we're providing and the volume that they're going to use sean isn't the number isn't the number one driver of value if you price your own number of transactions and they used your software to build their business and double transaction volume wouldn't you want them to be paying you double if that is your value metric well our value metric is not this is not our primary product as i mentioned earlier so what's valuable to us is that people use the technology and what in this world of data you know having ownership of the pipeline itself is valuable to us for our food brain to learn a lot more about what's happening in the world of food and trends okay so you have this core product it's a fixed price after the six day pilot and what you're saying is your upsell revenue and things like that can come from upselling your other products potentially exactly or it's or it's used in a different part of our business like for example we have as i said um taste intelligence and the restaurant technology products so it's it's not even about directly cross selling or upselling to the existing customers who are using personalized recommendations but it is about helping our food brain to understand more about what's going on in the world of food i got it okay put this on a timeline for me when'd you launch uh this product we launched the company about just over three years ago and this personalized recommendation product about two years ago okay so then 2016 company launched 2017 recommendations yeah okay and then you had to think about that for a second just want to make sure that's right yeah i'm just like what year are we okay got it good and then how many customers have you scaled to just on the recommendation engine today so i mean i i'm this is one where i'm not sure we should disclose that i'm not sure the nobody told me that i had to kind of disclose that information but i can tell you that we have more than 20 customers on it okay um by the way did you listen to an episode before you came on nope okay yeah we do one every day we've been about three thousand so it's we follow almost the same format every single time so you you wouldn't you would have known um but look let me i mean let me get in your head a little bit so um in terms of customer count you held back there a little bit why would you see it as an advantage or disadvantage to either share or not share that number by the way some people see it as an advantage if you have fewer customers because it's higher touch more care um i think it's more from a size uh perspective we have competitors as well and so i'm conscious of that so like that's one of the things it's not normal to kind of for private companies to reveal exact details around what they're doing um but yeah i mean that's just the way we've taken our position on this thing just more than 20. yeah i don't know i get it well look the show's about learning and so um the the other flip side is i let people come on and kind of spew out relatives all day long without getting details so the reason i asked the customer account number is because we have people listening uh that are looking to launch their companies and trying to figure out where do i go to get my first 10 customers how should i do it so tell us that story how'd you get your first five customers um the first five customers is for us was all about leveraging our my existing network because i had worked in in this sector for a few years now i was able to tap into some of the other members of my network who had also launched food startups and and and we saw this as an opportunity to kind of really show them the power of this technology because personalization has a leader in every uh vertical almost we like netflix amazon pandora but food there isn't a hard like well-known leader in personalization so it was it was when you paint that picture i think people really buy into the idea so leveraging the network was definitely valuable okay but but that's not helpful for my audience because leveraging they don't know that means leveraging the network so where where were you before this you're talking about the agency you had before you quit the agency and launched the software no late agency was before i worked there was agency where i had my marketing agency then i worked at just eat for three and a half years and then i launched this startup okay so your first five customers you're saying we're also customers of just eat and you saw this need and built it for them and then signed them up first no no my first five customers were in my personal network through having networked in this industry who had also started food businesses or food tech businesses or restaurants and they would like use our technology okay i can leverage that relationship and how did you do did you pre-sell did you pre-sell the idea and then spend money on developers or did you develop it and then sell it um it was kind of a little bit of both to be honest i mean we had this very very strong idea around building actually started it as a b2c product as well in bangalore in india we wanted to put it directly in the hands personalization technology directly in the hands of consumers but we realized that the long-term plan didn't work out because we would always be sort of a commission of a commission if we were working with food delivery aggregators so we thought from a commercial standpoint it was better to kind of make our technology as a service through an api and so when we made that transformation suddenly a lot of people got interested because this is not something uh personalization is important strategically to a lot of businesses but it's not necessarily the most urgent thing on there on their agenda because they're trying to put out their regular fires in their in their food businesses and so selling them on this model where they could just plug and play our technology uh kind of work for us and especially like getting our first few customers so i mean did you decide to bootstrap the company or have you raised we have raised uh so we've raised about just over 500 thousand dollars so far in the last three years okay and most of that was from the tech stars or no you had angels coming after so we've had a couple of angels tech stars xeroth artesian um arts alliance you know they're all on the website but yeah it's kind of like nobody was out of that you know it's a fairly even split across those guys yep and then talk to me about the team today how many folks 20 people all based in bangalore bangalore okay very good and um and and walk me through i mean there's a lot of people in the us that are going i need to i need to build tech talent in bangalore or argentina or ukraine because they're really smart people at one-third the price you're there you're on the ground is it true absolutely there's a there's a ton of smart people here uh the difficulty is um getting them at the right price that you you know that you want to leverage that cost advantage and also because it's a huge population here in india and that you know a lot of people are engineers there's obviously good and bad talent so you have to really go through a rigorous process of recruitment and work with the right partners to identify quality candidates i mean personally we've made many recruitment mistakes you know like we've been through a journey where we've learned a lot of things about the process over here and working with the local community yep you have two or three years of history now again we're only talking about this one specific recommendation engine product um churns critical and a sas company um how do you measure your churn everyone does it differently and how do you use it to guide the business ah that's a good question so um we've had a couple of customers not renew with us um and that was obviously disappointing for us but i think it was more about the case of you know the biggest argument we face in our sales cycle is build versus buy you know that's quite a common thing i guess for many b2b companies and um you know i think in some of those cases we had a feeling that they were using us as a short-term stop and then with a plan to kind of build out their own engine afterwards and that's also you know one of the perhaps that you know why would restaurants hire that seems like such out of their expertise to go build a dev team to build in your space this would seem like a very easy build by decision so it's not it's not a it's not purely restaurants though it's it's tech food tech companies right so like think of it like i mean i'm not saying it's a customer but let's say um grubhub you know obviously companies like that food delivery aggregators um you know a lot of them haven't done personalization so we're a kind of a for them who have got huge resources maybe short term we're the right solution but long term they might want to build it in themselves because as i said is a strategically important feature for most companies of that size a lot of them do personalization though but they use like more like marketing automation and sales automation and data tools versus something like spoon shot which seems like it's very specific kind of like the food industry why would they use you over the all the other tools that exist right now for personalization well it's all very domain specific our data is purely uh in that world of food and solving this exact use case for food delivery platforms for meal subscription platforms all of those for restaurant platforms that are going through digital transformation it's designed purely for their business so i don't think there is a like-for-like player outside of this domain there are a couple of other people who have recommendation engines in the food domain but i think absolutely we've built up a data set that allows us to really understand people's taste preferences very quickly and that's kind of powered by our food science understanding to we use food science and food science uh hypotheses to kind of extrapolate insights to understand people's taste preferences really fast so that's you know it's a very domain specific tool you're right how do you okay so let's say i use grub tub and i always get the um the uh yummy pad thai right um and i buy it from the cart they don't need to know if when i put it in my mouth i was happy because they see me reordering it on their site once every week and that is the indicator that i must think it tastes good so again why would they need you over just a one a basic marketing and sales personalization tool so so that you just described as a use case of where there's a frequency or a habit or a behavior in your eating but that's just one way in the many ways in which people eat many times people are in discovery mode they don't know what they want and the primary benefit of the aggregator is to provide that choice but it's almost like over choice like you've got you know dozens of restaurants to choose from and then within each menu you've got dozens of items to choose so helping people make an intelligent choice and removing the risk of having a bad experience is what we're about we're nudging people towards the right dishes and the right restaurants and i think you know there's a the thing people forget what though so the thing people forget about this if on netflix i get a recommendation i can just press pause if i don't like what i'm watching and move on to the next thing in food i have a real downside which is i wait for food i'm hungry i eat it and i don't like it and then i'm like frustrated by that experience so i think there's a lot it's a different kind of user experience and journey that we kind of helps how do you get the date how do you get that emotional moment when the consumer puts the food in their mouth and they're not happy how are you i don't understand how you're getting that we're not we don't need our technology doesn't need us to get the feedback of course when we set up and integrate with certain companies not all of them collect feedback or not all of them collect enough feedback so we've designed our system to work without that it doesn't necessarily just tell me that's your advantage though that's why i'm confused if if grub tub delivered someone to me today and i didn't like it i just won't reorder it again and so why i don't understand why that's what i'm trying to figure out is why would someone needs you you're saying the benefit is you're getting the consumer's taste if they're happy or not making recommendations to the consumer and i'm trying to figure out well where are you getting that data from are the consumers uploading this to you specifically and that's your advantage for like a grub tub or these food delivery apps no so so i think it i mean if we had the time we could talk through the specific mechanisms but we don't have the time so all i'm going to say is that we get we work with the company and they provide us feedback loops if those feedback even if there isn't a feedback loop in terms of the experience with the customer they send us like anonymized transaction data so that we can understand and build a taste profile and use the food science to extrapolate what people like and dislike got it okay very good um okay so you mentioned you lost a few logos over the past couple years i mean can you quantify this are we talking like 10 annual logo churn or something like that i'd say less than 10 percent okay less than 10 and then to get one of these new 2 000 a month customers again this is just for your recommendation engine product how aggressive are you being with cac right now will you spend the first kind of full year of acv to get them uh no absolutely not because of the nature of this product as i said it's not for us uh the primary product so our focus is really about helping dealing with the inbounds right today if you'd asked me this maybe a year ago i would have been maybe more willing to spend on the cache side but today we deal mostly with the inbound inquiries that we get regarding our product okay but you still have fully weighted cat though there's people creating content for your website of your team of 20 in bangalore you have to include their salaries divided by new customers per month i mean it's not just all inbound and organic and rosy dosey oh it's definitely not rosy dosey but you could think of this product almost as a loss leader in some way for us we don't think of it as a strategic revenue driver that's what i'm saying okay you have over 20 customers paying 2 grand a month so that's 40 grand a month in revenue at minimum correct yeah yes okay so if you didn't care about that revenue and you want to be a loss leader why i'm not saying i'm not saying i don't care about it i'm saying we have other priorities in the business where our focus in terms of the ltv and the sas um the lifetime value to cac ratio is far more important to us where we focus on that okay and what part of that business what what part of the business are you focused on those metrics in the ones where as i mentioned earlier we're launching spoon shot genesis and that's really the focus for us as a company yeah but you're launching that you don't have cohort data to analyze ltv to cac absolutely but we do have projections on understanding from our beta testing of what's going to happen sure i mean of course you don't know the reality yeah come out of the reality that's like yeah i mean pro you can anyone who put a pro forma together in excel sheet they rarely come true i'm trying to understand actual real cohort data you have so so to land i guess let me ask it differently the team at 20 have in bangalore they're all just right now fielding inbound lanes i mean do you have like an sdr to ae kind of setup or it's just like a guy that gets emails and closes deals and that's me okay so there are no sales people i don't have any sales and market people okay so so so how are you how are you going to try and then drive growth if you don't kind of have a sales and recommendation engine i didn't hear what you said could you repeat please sure you're the only sales guy on the team right now so right in order to scale obviously growth and sales you got to figure out how to replicate that process um what are you still learning right now where you have to be the one selling as i said to you um as regards this particular product it's not something that we're currently focused on whether you have 20 people or 200 you have to make calls right and we have multiple products and we have to okay talk about your other products talk about your other products whatever you're the only sales guy whether it's this product or selling other products all i'm asking is in order to scale the company you've got to scale yourself in terms of sales why so what you're you're still doing it yourself right now because you're trying to learn something you haven't figured out a scale yet what is it right now that you're not confident you're stuck you're still trying to systematize or learn um well that as i said if you want to if do you want the answer related to personalized recommendations or the other product if you're not focused on selling personal recommendations right now it sounds like you're not and it sounds like it's like a side project then tell me about what you are focused on selling and why you're the only sales person well i mean of course they're a resource limit so we we're in this track right now where we're trying to get our product launch uh timeline ready for mid-march where we launch screenshot genesis and at that point that's when we'll start to scale the sales team we've got a set of private beta users right now using and learning and helping us give feedback on the product and making sure that we actually deliver value for the customer that we're trying to chase until that point i can prove that point that i'm not going to scale anything on the sales and marketing side no i think that look i think that makes good sense um let's uh let's wrap up here with the famous five number one what's your favorite business book uh the hard thing about hard thing number two is their ceo you're following or studying oh [Music] that's a good question no i'm not okay number three what's your favorite online tool to build the business [Music] that's slack number four how many hours i sleep to get every night six and what's your situation married single kiddos family uh kids dogs everything how many kids one yeah another one on the way oh congrats good so married one kid soon to be two and how are you sean uh 37 okay last question take us back to your 20 year old self what do you wish he knew don't go to vegas so much actually invest your money that you earn guys invest your money don't go to vegas again launch spoon shot really food intelligence platform launch in 2016 launched a sas product really in 2017 a recommendation engine has 20 customers paying 2 grand a month for it to call it 40 grand a month right now in sales he got those sales from a network he built previously in this kind of food industry looking now at scaling they've raised 500 grand 200 sorry 20 people in bangalore less than 10 percent logo turned annually as they look on and work on launching their new product called genesis all right thanks take care