Streamline your sales phases for teams

How to create outlook signature

alright let's let's get started so hi so my name is Philip battery I'm with excel so we're we're global venture firm with offices in in Silicon Valley where we have our origin and I'm based in the London office and we also have an office in India so we're one of the very few early-stage venture firm with a truly global coverage and it is that network that we give to to our portfolio so we're we're here because we are you know we're pretty big on SAS we've invested in companies like Dropbox FLAC Qualtrics Atlassian in France there is a pretty vibrant ecosystem so we're in a you know algo Lea doctorly people dock and shifts technology so I'm I'm very pleased to introduce Jeremy who is the founder of and CEO of shifts so shift is a SAS leader in fraud detection and claim automation for for insurance so as you all know insurance are large quite large and the deals when you sell to insurance are big quite big and they're not very easy to tool and especially when when you're small so in this session we'll discuss how to structure your sales and marketing team to scale fast when you sell to 200 price so Jeremy is great to be with with you today first as I start can you give a sense to the audience about what is your you know typical deal size you know how many customers do you have so we get an idea of what you're dealing with every day hi everyone so I'm Jeremy thanks for pretending so achieved we sell software service solution for insurers so it's a wrecker --nt so interests a yearly usage the average deal we have is around five hundred thousand euros records so it's not small deals of course you have small deeds that go to like 100 thousand a year but large ears can be multi million so our current largest is 200 million records which are 2 sorry 2 million euros records ok I think the average ood would wouldn't be 500 thousand ok good so maybe yeah well yeah I wish it was 200 million I would be a very happy investor but I am still very happy with 2 million ok so let's talk about your your first customer because I mean it's always hard when you start your you know you were the smallest you have ever been and you have to sell to a big insurance company so tell us about your how did you learn your first customer so yeah the for shift it was it wasn't an easy sell so to give you the context for those who are in the same situation shift we are three founders I'm where we were at the time 26 27 years old and we created shift saying we want to sell software service ai algorithm for insurers so we were targeting insurance company in France and we went to see them claiming like we will we will automate your fraud detection you just need to send the data and we'll do it and everybody was looking at us like you're you're 3 27 years old guys you want to have all our data process it and send it to us are you mad and so we we were like struggling and having our first deal so the way it went is we got introduced to one one of it's a funny the first one is quite funny we got introduced as all incubators and and start up to an insurance company and we got introduced to the head of innovation and innovation were very excited to meet us because his job is meeting startups and introducing it and we spent six months having dinners and lunches and discussions and business case with the head of innovations and we were not meeting anybody else so we we were like well I don't know how this works how we can land a deal of several it was like a million euro record deal and we're not meeting everyone and we were like it's we were first-time entrepreneurs so we thought maybe this is the way you sell stuff and then we had our investors did our seed Iran they were like you never gonna need land a deal like this you need to find who's the key decision-maker and this era realized that the keys decision-maker wasn't this guy and the funny story is that we met we get dentro met this guy signed the deal in the office which is exactly next to the office of the head of innovation and a month after he just called and say like well are you guys we need to start working on the deal and we already signed in the same in the office just next to him so the first deal took us a year to land okay so the first learning is don't talk to the head of innovations alright so nobody can tweet that because my wife is actually a head of innovation for large companies though so the key learning is just make sure you're speaking you you can identify the organization the right decision maker okay so you've landed your first customer very sizeable deal so that obviously gives you a lot of credibility when you speak you reach out to other customers so now from there you say it's not saying you know how do i scale and in the first question for you is like how do you organize your your sales team to scale first in France and then across different countries yeah so then once you had our first customer it was about scaling sales the first thing I learned is that I'm not a good salesperson so the first thing you do when when you're turrible are something we did not know that at the time of the investment is that you hired somebody to do it so so the way we scale that we we spend six months looking for a head of sales so we hired she's not our chief revenue officer somebody that was head of sales for SAS tool as organizations and we took somebody that already scaled the business so she was the head of sales of IBM cloud worldwide and six months because you need to convince somebody to quit a job with 450 sales rep to one sales rep in Paris and and then this is where you learn how to scale so it's about having the right proposition value having the right references organizing packages for sales and then hiring sales and all the work we've done is packaging how we can identify who's the key decision maker what is he interested and how we sell it to these people and what's the right business model and this is what we've done for six the first six months and then it's about having the right team under the right team so that was four friends so basically the structure of the organization you hired a head of cell and then under that head of sales you had different reps though do you have a specific cells UPS team to prepare I mean to do all the account management preparation identification of the target decision maker was is done by the reps so we organized in a way where we have the reps that do all of this work but all the technical sales is done by data scientists in the company because it's very important that the people that gonna do implementations and work on production are the same people that talk to the customers and this is also what forces us to have data scientists from different countries because you want them to talk to in German - German to talk in Spanish to Spanish and so the organization is you have head of sales with sales wrapped up that they're really literally takes the whole sales process and then within the sales process you have data scientists that are experts that work with these guys and are in front of customers so you send your data scientists in front of the customers can you imagine sometimes situations I'm not going to come in on that so how do you hire your data scientists it's because usually data scientist I mean the bit of data they love and science so they love to work in front of their computer they are not the people I mean if your data scientist you don't do that because you want to go and sell to people so as you go into cells so how do you screen and hire your data sent is to make sure that they can also do this sales role so we did an internal data scientist study and we realized that the first feature was being a fan of Stowers so this is the first thing you want to look at the data scientist now I'm just kidding it's we're big fans of Star Wars in the company so everybody makes jokes about that so yeah what's important in our interview process is of course there's like mathematical questions and coding questions and then there's there's a me there's loss interview where what we try to find out is is this data scientists would be able to work with users that are today claim handlers work in insurance company looking at papers and dealing with claims on a daily basis or they're gonna be like crazy geniuses in front of the computer that want to go to meet customers so this is the first thing is hiring the right people so once they're hired the first thing we ask them to do is work with salespeople and they spent four months with a user in an insurance company so before hiring status and you tell them the first four months you'll be sitting with claim handlers and working as a claim handler so you come out of university doing a lot of mathematics and then the company puts you where I came Handler taking calls and settling claims this is a good way of selecting the one that we don't want to do it so this is this is the complete process we have okay so it's very interesting because as we see I mean you love the new products we see right now i mean there is machine learning everywhere and when there is machine learning that is you have some technical sales to do and so it's not the first time i hear that you know data scientists have to be in front of the customer and so it's very important what you describe in terms of how to onboard and making sure they really understand what's happening at the customer before they're actually placed in front of new customers so in your organization so how did you handle the geographic coverage like was everything based in France to cover all of Europe or did you start separate the country organization and then how did you address the organization for the US market so the way we're structured is you have sales rep that are in countries where you wanna land deals we have a rule internally where these sales rep needs to be at least once a month a week in Paris very important and then for the data scientists either it's in Asia so you put them on-site so what we do is we send French people that go outside and create teams easier for the rest for Europe it's in Paris and we are quite an international team so if you visit our office you'll see we have a lot of people that don't speak French we have a German team and Spanish team and a UK team so every country has its own team and they all work on the same solution so it's quite interesting because this is where you see that for instance German people really focus on identity aggregation in terms of pushing into the solution Spanish people who focus a lot of networks detection so it's a quite international culture where people are per country working with the sales team but work on the same platform ok and so do you have the country head managing all the different people in the country or do they report to you know whatever head of function based in France yeah so this is the toughest part of structuring the company so we don't have local managers when I say like we don't have a manager of Singapore or a manager of of Japan we have Head of Sales reporting to the chief revenue officers and we have data scientists reporting to the chief data scientist and this is where the biggest part of my job is being sure that there's a harmony between these people and they work together and it goes with the right processes that people need to execute like like I was saying like in sales you need to have sales rep taking there a scientist so he can't go to a meeting without a data scientist and all the other side you need to have data scientist team being able to execute what the sales team self so it's all about making sure that there's a real team spirit the right process in the right harmony and this is the tough part of what we do but when you when you looked at it today we have a really amazing conversion rate we don't have any any problem in getting our customers and it wasn't easy at the beginning can you imagine like you hired a bunch of IBM sales guy and you told them you know what we don't have technical says you take these data scientist 25 and your sales meeting pitching the product there was a small time adaptation Wow so that's a so Becky if I try to summarize your sales model what the the key thing is making sure that you have a dual team like join team sales and data science making sure that the data science people are trying at the customer so they really understand the business and then you develop your country teams but they are managed kind of centrally right exactly that's a playbook and did this scale into the US as well or did you need to do something different from for the US market so for the u.s. is like we've done in Asia like we've done in Europe so it's hiring local head of sales local data scientist training them from Paris and repeating exactly the same the same modus operandi and and it's funny because one of the funniest things is sometimes you have this ranking about startups and once you've done this opening an office with local data sends it out the local head of sales since we're quite international there's a lot of startup ecosystem tweeting like shift a Singaporean startup in the top hundred I don't know what shift a Japanese startup in the top two any something and everybody thinks were local because like the eyes that are on site local and we have this really how many where the head chief revenue officer goes to this meeting and help the local sales I travel everywhere so what's important is make these insurance people feel their local while everything technically is some kind of centralized embarrass how much time do you spend I mean you have customers within Asia Europe in the US so like how much time do you spend on the road to answer that question so let's talk about hiring the the sales reps so what what are the traits that you're looking for for when you want to hire sales person who can sell and like 200 million or you know maybe a two million dollar you're working on that promise two years two hundred million dollars so in terms of hiring this is also yeah so I spend most of my time meeting customer and hiring this is my job so about about hiring the first rule is trust the person you hired so this is the first rule so our chief revenue officer is she source candidates her team source candidate gets candidate and what they try to catch is people that know sales so can stick to a sales process understands the key sales processes in terms of who are the key decision-maker when I'm selling I'm assuming I'm selling and then the last meeting is with me and what what I try to understand is if they can fit into the culture of the company so it's very important and there's a lot of work and we have a whole bunch of questions to really we worked a lot on it too depending on how the person answer you can feel if are they going to fit in the company or not there's a lot of can you give an example of this kind of questions an example is you you ask like we have some basic questions what he thinks about something and my job is saying in not approving what he's saying for 10 minutes and taking the data scientist role like I don't agree it's not like this and like I'm annoying for 10 minutes so 10 percent of the cases they leave the interview which happens sometimes and and then this is well see like this guy is gonna be in front of the data scientist that means to go with him to meet a customer and the data scientist won't agree because he won't agree selling this because he won't be able to do it how do you react so these are kind of things that we have in our process and the last thing is does the person on the still the person understand our business and a part of what we're doing because like every startup we have failure when you hire somebody that may be a great salesperson that you had from a great software company but then you know that this guy would never understand what he's selling and even with a data scientist he will never understand it and we had some failures where you have insurance calling you like you're sure you're doing this it's it's funny it doesn't look achievable and you end up signing deals where you think it's not cute interesting and at the early phase of the selection process I mean do you say well you know I hired like to sales people from you know with this kind of background you know very specific on on companies and years of experience and you're like okay well that works so let's go and look for this or do you actually find more diversity in the background of your salespeople yeah so in terms of selection exactly we were looking for for two there's two component and depending on countries so if you want to hire somebody in a country where the biggest roadblock you have is software service in some countries people don't go for software service they don't want to send data outside of the company so you're gonna look for somebody that already sold SAS or cloud in this company so IBM cloud is a good way of hiring and in some countries SAS is much more common what's important is having the insurance them because insurance is very local so for these countries you're gonna look at somebody that already working in an insurance environment and Schurz know them and this is what you're gonna look for so we per country try to find what are the biggest roadblock and this is how we define people you want to hire okay and how do you define the quota so what's your your typical quota and you know what's the the comp you know fixed bonus so this is where I trust my chief revenue officer she's like comp it's 50 fix 50 so ot is 5050 and in terms of quota its we defined a strategy this is what we need to hit and then she does her stuff and at the end I can see how many like which each sales person how much code that I have and when they start the quota is quite low and and goes up and I ramped sales person from our side that is somebody's like bit experienced there Kota is between two to four million like three million average yeah yeah oh that's a it's a big quota and when you start so how long does it take to get to the full ramp and where do you start so get full ramped it's quite long so we observe that people in order to be ramp first and start signing deals there's nine months because they need to get to know the marketer to understand the product it's not an easy sell and then so for the first nine months you're gonna hit a coder as her around like 500k million and then you have nine more months in order to hit the full rent so we have a selection where if the nine the first six months you know he's not gonna hit his nine months plan he just don't keep him and once he had the night moncla and how he can rubbed him to be sure he gonna achieve the high high quota so when you have a long ramp like this for sales right what are the milestones that you give the reps in between just to make sure that he knows that he is on track and that you know he is on track so this is this is where we have internally a good process is you need to be able to track every quarter the KPI as you give it to your salespeople because you're close to them they they can tell you like I'm not hitting it because of this or dad's so you can actualize your KPIs but it's important to really track it very precisely and being able to put the emotional part aside and understand like is he hitting escape ears or not and why and if the why is that it's not the right person you just fired him so it's there's a lot of work when we hired somebody in the sales team which is much more work than my data scientist it's being able to have the right pick API make the person understands why he has API and being able to track it so it's all about kpi's per quarter that are very precise what kind of keep he has because if you're not expecting them to make a sell before six to nine months and what is the KPI for the first quarter so the first thing our chief revenue officer did when she arrived is putting a different sale steps so identification of accounts qualifications like she's very very known qualifications he put something qualification not qualified she's called Marion company and start showering so it's a qualification proposition approval signing so there's a lot of different stages we have seventy agent company and then she has her plan where the first quarter into this number of quota and this column and this number of quote and this column and she has a nice statistics on how do you go to a stage another and what's the conversion rates so it's quite statistics and mathematics I should have kept KPIs and you look at how its ramp it's it's very easy now with all the process we have and how do you check that stage is actually achieved because I mean salespeople they're pretty good you know being a bit forward-looking right so if you don't read that I'll give you the secret is you ask the data scientist that goes with them that's why you want the data scientist in the team okay that's that's a nice tip and so how much do 443 million Cora like what's the salary that that you pay sales rep no not here you know we it's it's we what we do is we take like other companies salaries and we pay 20 percent more okay and how do you set your overachievement curve like it is the when you look at the the the bonus payout like is it linear pay out up to a hundred and then continues to be in error or do you have an axe you know first you're kind of an exponential where at the beginning you do 50% you get nothing then you tax iterates 100 and then how do you manage the acceleration beyond 100 yeah this is this is quite interesting as a first-time entrepreneur like I didn't get it people were asking me I understand so it's very important I didn't know that the way you structure compensation is very important so the way we have it internally is if you achieve under 70% you get zero if you achieve 200% it's leaner and above 100% there's an acceleration where everything more than 100% you have a multiple that is quite high and this what attracts very good sales people and this is where also I learned the 30-30 stuff so the 30 Authority I didn't understand what was it but it means that sales people will tell you I cannot achieve only this which is 30% lower than what he think he can achieve so you need to know it so you can put 30% more and this is where like it's now as usual you just take 30% more and it put 30 percent lower because of these acceleration stuff nice so 30% is the number good so what are so if you were to you know to summarize I mean when I hear what you're saying I mean it sounds like to sell into enterprise you basically need to put in place a very organized machine so it starts with you know mapping the accounts to understand really who are the decision-makers it's about making sure you have the right team which is a good mix of cells and technicals figuring out how do you have local and people in the local region where you sell to make sure that your customers locally think you are local and then put in place a very structure sales process to be able to measure the progress of the sales people even though you're they're not expected to make a first sale for the six two to nine months so then once you put all this in place so what are the challenges that you're facing today now as you scale the challenge so it's not easy to do this but the challenge after that is making sure that people stick to the process and that the people at hire people at hire people are still exactly in the same culture that people you hired and this is my job today is being sure that process I put really put in place and being sure that data scientists go to all of these meetings and get the feedback from the data scientists so after that it's about looking at things scaling be sure still scanning right way great well thank you very much Jeremy was a pleasure to be with you today [Applause]