SPOTLIGHT: He Missed Quota 5 Times in 25 Years. Here's the System Behind That.| Mike Carpenter, CEO & Co-Founder @ Xfactor

0:13Hey everybody, it's Sam Jacobs. Welcome back to Topline Spotlight, that segment of the Topline podcast where we talk about the background and the challenges of our guests. And we're trying to dig into the tactical problems they've solved over the last 12 to 24 months. It's supposed to be highly tactical. We want real insights from real operators. And today on the show, we've got Mike Carpenter, the CEO and co-founder of X Factor and the former president of global sales and field operations at CrowdStrike. Mike, welcome to Top Light Spotlight. Thank you. Thanks for having me, Sam. How are you doing today?

0:51Doing great. Living the dream out here in Manhattan Beach. Nice little enjoyed it with some good sun are you uh are you a surfer are you taking advantage of the waves out in manhattan beach i do i try to get out twice a week but you know i started learning at 50 so i'm not i it's kind of like everybody who plays golf you know i get out there we can call myself a surfer that's fair there's this book uh barbarian days about surfing and the guy says that if you didn't learn when you were young you're judged you're judged out there in the water um well let's let's talk about your business so xfactor.io is the name of the company give us a little bit of background on on what the company is what the company does and and sort of how we should you know what the offering is yeah let me kind of back it up a little bit about where i came up with it right yeah sure um xfactor is the name of it xfactor.io when i started out my career.

1:55Um, I, you know, as an entrepreneur, I sold my business when I was 24. And, um, the one thing that I didn't understand was what does it look like when a business scales? So when we got up to 60 people and, and, you know, quite frankly, it was kind of silly looking back on it. You know, I'd be there till midnight cleaning up the office and the cafeteria. I didn't even know there was janitorial services that would come in and help me out with it. Right. And so it was kind of funny having yeah I started when I was 19 and not knowing what to what services to implement to get it scaled so I was fortunate enough to have a liquidation of it and um and I wanted to go to work at a big company so I went to work at McAfee and really saw like what a business looks like when it's grown up and um while I was there I started to realize that you know I took over one of the more difficult regions.

2:54They were actually the most underperforming region, uh, across the world, which drove the CEO crazy because it was in Silicon Valley and that's where their headquarters was. And so, you know, I, I approached it and started looking at doing it the same way. Every, you know, sales guy does or sales lady does is, you know, I just got out and tried to get into every deal and be super rep. Right. And quickly realized that it was exhausting, A. And B, there's so many things, only so many deals I could touch. And so I started to look at, like, how can I differentiate myself? Like, where can I find, and I came up with the word X factors, the X factor, that thing that separates me.

3:43And so what I realized I didn't want to do is do it with grit, because that's just not enjoyable to your life. You know, I could work all morning, all afternoon, all night, not take breaks, sacrifice my life, my health, and try to get out there and touch more jails than everybody else and catch more plane rides than everyone else. But, you know, it wasn't giving me the skill that I needed to make a big difference. So I came up with a philosophy that I needed to really change my value to the team every 90 days. and so I started setting X factors and they started evolving and what X factors were for me was trying to find a way to do business differently that change the game change the rules to the game that nobody else is playing by and if I hit one out of ten I'm gonna make a difference and hit my number so part of it for me was you had to make it measurable and it couldn't be things like I'm gonna run three lunch in one of this week right it couldn't just be grit based stuff that you do on regiment you know it had to be really thinking outside the box and trying to figure out what is it when we win and what is it when we lose and what's the difference in between there and I started finding what I would call cheat codes right so the best way to explain that is when I I was in college, I think the game was Sager, you know, some of the early gaming systems.

5:18Yeah. Nintendo. Yeah. Nintendo. And I, I had this knack where, you know, you hit the button three times and you find if you hit X and then, you know, move to the right, all of a sudden, you know, the, the, you'd get this, you'd get a, a, a completed pass every time and nobody could stop it. Right. it. And so I literally, as juvenile as it sounded, that's what I wanted to create with X factors. I wanted to hack the system and try to figure out what is it that I could do that would be different. And I was an accountant by trade. So I wanted to do it with analyzing numbers and identifying what was the outliers that was the difference between us making our number and not making our number pipeline growing povs failing i went through you know tons of numbers i actually went outside the box and hired a mit grad that was in a financial analyst working for goldman sachs and recruited her away to come work for a sales organization and her job was to rip through all of our numbers and every activity we did and find anomalies.

6:32And from there, I created X factors and then they all had to be measurable. And every 90 days, I'd cross ones off the list that weren't working and I'd fail those fast. And the ones that were working, I kept doing and doing. And once I found a trend of it working, I would share it with the rest of the team and get everybody doing it and as I grew with the organization I had larger and larger teams and I started training x-factor build outs with the team and you know I increased my operation staff to be able to handle and look at more numbers and more numbers and it was a really successful endeavor the hardest thing was working across the sales mentality the sales mentality every sales route they want a lower quarter in the larger territory of course so and which is usually a sign of an underperforming company so yeah it's a quick way to know you're going out of business right yeah exactly so that's what i used to explain to them when they come back and argue their quarter every every quarter right we used to do quarterly quarters it's like getting a root canal every quarter, but having to do it to 10 different people.

7:51And so I built it into them saying, if you want changes to happen, you need to give me hours in my quiver. You need to have wins. I can't go just ask for changes from a large corporation when we have an unsuccessfully team. So you got to give me wins. And so I got them really focusing on X factors. But the funny thing was when I tried to go get the sales reps to give me X factors, they would treat it like a quota. They would give me the easiest X factors that all they needed to do was add a little grit and a little tracking and they could easily get it. So they go 10 for 10 and I'm like, this isn't changing the game.

8:38You're just doing what everybody else is doing. So I spent a lot of time, a lot of years trying to teach that mentality and trying to put them in a position where they understood that thinking differently and being able to track that could actually be the, you don't have to argue quota. You have to find a different way to win. And so you have to be able to change the games here and change the rules of the game and do things that other people aren't doing. And for me, I use numbers and I kept staffing up as my teams got larger. And I had really large ops groups, abnormally large compared to the rest of the organizations that existed around me and the rest of my peers and other companies, but it's what made the difference.

9:28And, you know, 25 years of leadership, I've missed my number five quarters. And that's like unheard of. um you know I won VP of the year seven out of eight years in a row and I did it in different industries they kept promoting me they put me in federal and I had no idea how to run a federal business they put me in state and local I had no idea how to run a state and local business they put me over consumer I didn't know anything about consumer but I just stuck with that philosophy of X factor. Now, later in my career, when I was at CrowdStrike, we were in a hyper growth stage, right? And when I joined, we were pretty small, somewhere around 25 million in ARR.

10:15And we were mainly selling services and intelligence, launching in to the product side of the EDR business. And so I put the same thing to work. I really staffed up, Um, you know, had the arguments with the board nonstop about why I needed so many analysts and I still used my travel, but my travel was for me to be able to put my finger on the heartbeat, like trying to figure out what's happening in these calls that are different recording copeless notes, coming back with my analyst, trying to figure out what's different, what trends are off. And I remember sitting in Austin and, you know, at this time we were probably a half a billion dollar business and we'd start our planning in the May timeframe, which is early.

11:09Most people start in like late June, early July for the following year. And I build this plan with AOP, with a mountain of people, right? And I go ground up, I go top down and I'm on the way to scale the business. I had a lot of fail safe plans to be able to adjust to different curves in the business. And I'd submit it around September. And then by the end of October, the CFO would come back and say, we need to do 15 % more and you need to cut the budget 10 % more. And that blew up your plan. Like every assumption you could run was off. In addition to that, what was happening was when you're running a business on a spreadsheet, one wrong command with multiple sheets of cloning and cloning and cloning creates a cascade failure of your numbers.

12:07So I'd walk into these board meetings and somebody was good with numbers and would find that's wrong, which means all of this is wrong. And I blow me up and I'd have to revert to horse trading, which is the balloon squeeze that happens between sales and marketing and GNA and the executives and all the different groups running their silo trying to compete for their unfair share of budget. And it drove me absolutely nuts that I'd spend all that time and then have to go back to an archaic, you know, political game of trying to get the budget. And by the time I got the budget in December, I wasn't even able to start executing my hires until February.

12:51And if you understand capacity planning, if you're selling in Europe, you need a 90 day timeframe when you find a person for them to leave the company and come to join you, which means I needed to start my hiring in October to get my international markets to be at full capacity. So I had to find all these different avenues to get there. And I remember saying in Austin, when I retire, I'm going to solve this problem. An operating plan can't be built once and forgotten. It never came out again past February. and microeconomics change, macroeconomics change, and it blows your plans up. And now you're flying blind.

13:38It's like literally, you know, being a pilot flying across the country and all your instruments go right. And it's just not a recipe for success. So yeah, I'd ramp up more and spend more. And we just, I kept that plan running and kept, um, you know, maneuvering and trying to get through it. So after I retired, you know, I was, did my typical board thing for a while and just, you know, did absolutely nothing but go skiing on the back of the lake and having fun. And then decided that I was, I was getting a little too bored. So I started X-Factor and I figured I was going to solve this. So I hired a bunch of engineers and AI engineers and we started rethinking the process i hired a bunch of go-to-market experts and operational experts trying to figure out how do we build an always-on operating plan that can adjust and that can find those glow-in-the-dark x factors they can find those cheat codes those those hidden areas that can unlock revenue right that can solve problems what's the number one uh like what's the number one example of that in your experience having done this for so many years gosh um i would say being able to understand uh one of the big breakthroughs we had is when we started incorporating conversational intelligence and being able to ingest it and then run ai against that against the crm system against the outreach systems against the sdr pitches and trying to find the key words and how much time on offensive talking versus time on defensive listening and being able to find correlations between those that was a difference from a Dale moving from stage two to stage three and then tying in heap and looking at you know heap will track how a user is using your technology and understanding churn rate against that how often are they using it?

15:48What features are they using it for? How are they finding return on investment on your product? And then tying that back into the first call and tying it back into enablement, like the training process for when you're onboarding. And then that impacts how quick you can get people onboarding. If you ask any CRO in the industry, it's really funny. it's like the common lie. They all say, how long does it take to onboard a rep? Six months. It's the same answer for everybody, no matter what. And it's not six months because if you're warming territories and you're virtually cutting them. So if I hired you, I would virtually cut your patch without you knowing.

16:33And I'd have patch A through D. And I'd look at where you're spending your time and your time is spent where the value position is already recognized. The customer has a budget and they're going after it. The rest of them are just getting email outreach, right? But there's a certain amount of touches you need to an account before they start to tie a problem into an opportunity. So we started really spending our marketing dollars towards those areas and trying to figure out how many touches it took in order to get a client to recognize the need. And then I started warming those patches. Once I got a patch to a 3x pipeline that was a virtual patch that was being done through a combination of marketing outreach efforts, then I'd cut that patch and I'd start ranking which patches could take my new hires.

17:29That would move my ramp time from the theoretical six months, which was probably more like a year and a half to 90 days. When you have a seasoned salesperson come in to a warm patch of accounts that haven't been physically touched and haven't been talked to, but they actually understand the problem and they can resonate with the issue, you could really set up a much faster ramp time from stage zero. The warming them up is like basically drip email campaigns. And maybe today it's like AI voicemails or something like that. I mean, there's probably a lot of ways to connect with people, but it's some marketing effort that warms them up so that the person steps in and they have a dashboard of, these are the people to call.

18:19One of the things that we built was, I'm not a fan of MQLs. Nobody is. You know, what MQLs to me are, I'll give you a story around MQLs. We had a large marketing team and after the quarter closed, they would put a spiff for the next 30 days for their entire marketing team to go through the CRM and tag marketing sourced from every deal that didn't have the appropriate level. There you go. Mark is the reason you're in business. Yeah. Well, that's helping their MBOs, but it's doing nothing for lead generation and telling us where to spend. And so, obviously I put a stop to that and I started thinking about it more, thinking like, who cares?

19:13Can you really tell a marketing qualified lead came in through an email campaign? You can't because it could be a friend they talked to that went to the website, that started a demo, that then again saw a banner in an airport, that then again saw you at a conference, that got a phone call from a friend of a friend. Like there are a million ways. So I look at it as touches. Like how many times can we qualify a touch? And how many touches does it take to warm it? How many does it take normally? 16. Okay. And that's a lot, right? That is a lot. It's not 16 emails, it's 16 correspondence. And so in order to get them to those numbers, you have to really be creative.

20:04You have to be analyzing massive amounts of data. And it just so happens we're in a stage of the world right now with AI, where you can take those massive amounts of data and not have 100 analysts like I had on my team, right? The issue that we're facing right now, I would say over the past 12 months, and I think we're going to face it for a long time coming, is you hear a lot about Claude and different open AI systems, and everybody thinks they're an AI engineer. And we faced the same issues, right? You can't just take Claude and throw it on a massive database, and it's going to tell you the secrets to life.

20:43You know, you need causal AI and you need a co-pilot, a twin that starts mapping potential links. And that's a huge human intervention piece there. And, you know, I could go take, we've done studies ourselves, we've taken Claude and just thrown it on the same data set we have, and it completely hallucinates an answer, but it doesn't just hallucinate or drift an answer, it gives it to you with certainty. It is like your dad telling you, if you cross the street without looking, you're going to get hit by a car, right? Like it is certain. And so it's dangerous. Very dangerous. I think that's my biggest competitor right now.

21:26And it's a shift that we've been going through, really staffing up around the intelligence to be able to map cause and effect and then allowing the system to learn those cause and effects. Because if not, you could just index anything on the internet or from documents from your internal communication systems, whether it's Slack or email, and it's going to learn the wrong data. And it's going to tell it to you with absolute certainty. And then the other issue it has in the way that AI works, when you're looking at systems like, like Claude will pick on Claude, is that it's basically generating new Python call code every time you run a query.

22:11but the problem in that is that every time it generates a new query it's not pulling anything back into memory and learning from it and therefore it's going to give you a different answer every time you ask the question with a slightly different accent to it or slightly different word to it and it's going to tell you with certainty and you're going to pivot your business in a way that you know you're not going to know what's wrong until your numbers start dropping yeah and yeah i think that's massive you're right that uh the the the primary feature of ai is is persuasiveness and is certainty it is not necessarily accuracy so that's why you need subject matter experts to be able to say that doesn't work you know or that's not correct what uh we've only got a few minutes left yeah that's a blow you away like brilliant firms and And they say, we're doing the same thing.

23:05We implemented cloud on top of our CRM. Well, McKinsey just had this massive breach where they figured out that their whole AI systems had all these back doors and were like the most vulnerable cybersecurity systems out there. So you're absolutely right. So X-Factor, just to be clear though, X-Factor is a software platform? Yeah, it's an AI software platform that we've built for about four years now. and we have massive amounts of data that we train against. We have a huge list of both analysts that come in and look at it and look at map cause and effect. And then we test the results over and over and over, making sure that it's not drifting and making sure that it's not giving you information that's not accurate.

23:53And it takes a long time. Really, I think our biggest issue is statistical erroring and being able to get and remove statistical error and where we have some checks and backup checks and all different types of hidden layers that we're looking in real time to see, are we giving this? And now we've implemented probability ratings. So if we can't back it up with running tons of different sum checks about it with certainty, we'll drop it to a 60 % probability rating, which means you need to really look at it and test it slowly. But what we're looking for with X Factor is you can use plain English like you do any open AI to ask a question.

24:38You know, I need to gain 15 % of business off of, without any additional head count, am I best at changing my POV, my win rate, what's happening, my conversational intelligence, which do how often do I need to be listened versus talking which customers are paying the highest ASP and renewing and how are they using my product they if you dream of it that's what I love about it because that was my MO that's what I did in my career to have you know a very fortunate career is I just kept looking and looking and looking for that hidden layer that cheat code that I could a mock and it happened every time i mean it was unheard of my my my ability to perform was not the fact that i hired the best it wasn't the fact that i was the brightest i was far from the brightest on my own teams it was the fact of my methodology of doing things differently and feeling fast and expecting to feel a lot like i wanted to feel at nine of my x factors because then i knew i was setting them right if uh if folks are listening and they want to reach out what's the best way to contact you um you can contact me directly with mike at x factor.io but you can also go to the website we just launched uh earlier this week a free trial where they can just qualify get on and go run it for 90 days.

26:11And it's, it's mind blowing. The information that comes up, I mean, with clients, the first question is always like, no, that's not what my spreadsheets are telling me. Like, well, the spreadsheets have statistical error, but now we put it in the methodology so they can actually go manually look at the methodology that we use to calculate those results. So we've been working through all different ways to gain consumer confidence. and I think that was the biggest challenge because people are so used to just taking the data they have and there's so many different people it's so easy to go create a cloud algorithm and throw it on data but I'm telling you it's fool's gold that's going to have a massive breaking point where people using it and we've seen it in the earlier days where you know AI started getting racist by looking at, you know, ingested material.

27:06It is the same exact thing. If you're looking at your email data, you're looking at your communication platforms internally, people are giving opinions and it's taken it as fact and there's no probability checking and, you know, they're not going to find anything. And so, um, I think that's going to be the biggest challenge and it's going to be a challenge we face today. Every call we get on, you know, somebody, you know, down low in their op stack created a cloud implementation on their dataset. They didn't set up a data lake. They didn't set up test stubs. They didn't set up the ability to run multi-level hidden layer checks to go some check everything.

27:52And therefore it's, it's just fool's gold and they're using another, you know, platform that's going to bring them the wrong way. Now don't get me wrong. It's, you know, you can improve spreadsheets and do it faster, but that's not what we're doing with it. We're trying to get it to be able to take millions and millions of different data sets from one location that's been normalized. And it starts to learn cause and effect. And causal AI is everything. And you can't do that with a person, you know, making$150 ,000 a year. I mean, Anthropics hiring people at a million dollars a year. There's a reason for it.

28:34Mike, it's been awesome having you on the show, and it's been great to learn about X Factor. So just for everybody listening, it's xfactor.io. And if you want to talk to Mike about some of the patterns that he's seen over his career, it's mike at xfactor.io to get in touch. Thanks for being our guest. Thanks, Sam. Appreciate it. Yeah, take care.

29:02Mike Carpenter: Okay. And against all odds, you're still here. Look, if you want more Topline, check out the Topline newsletter at topline.beehive.com. Beehive is spelled weird. It is B-E-E-H-I-I-V.com, topline.beehive.com. Or if you're a video person, because video is great, check us out on YouTube. Topline-media is what you want. Have a delightful day, everybody.