Omer Khan [00:00:09]:
Welcome to another episode of the SaaS podcast. I'm your host Omer Khan and this is a show where I interview proven founders and industry experts who share their stories, strategies and insights to help you build, launch and grow your SaaS business. In this episode, I talk to Zach Rattner, the co founder and CTO of Yembo and and AI powered platform that enables virtual home surveys for the moving and insurance industries. In 2015, while working as a software engineer, Zach noticed that computers were becoming better than humans at identifying objects in images.
Omer Khan [00:00:46]:
His wife's experience working at a moving company inspired him to apply this technology to that industry, which struggled with giving accurate quotes and handling logistics due to the complexities involved in in each move. However, building an AI powered product was no easy feat. As introverted engineers, Zach and his co founder Sid had to force themselves to step out of their comfort zone. They made cold calls, visited moving companies in person, and often faced rejection. In the early days, the founders also handled sales themselves.
Omer Khan [00:01:19]:
They attended industry trade shows and conferences to generate leads and build relationships with potential customers. Despite their efforts, the first version of Yenbo's product had limitations in its AI capabilities and user interface, which led to some customer churn. The founders realized they needed to focus on finding early adopters willing to work through those initial challenges and continuously iterate based on that customer feedback. Through their determination and hard work, Yenbo gradually gained traction.
Omer Khan [00:01:50]:
Today, the company serves customers in about 30 countries, processing hundreds of hours of video daily and generating high seven figures in annual revenue with a team of about 70 people. In this episode, you'll learn how Zach and Sid validated their idea despite facing rejection and discomfort, and what strategies they used to overcome these challenges. Why setting realistic expectations about your AI powered product is crucial for maintaining trust and and preventing disappointment among customers. How Yambo overcame skepticism by educating customers about advancements in technology and focusing on early adopters eager to try new solutions.
Omer Khan [00:02:29]:
We talk about why handling sales yourself initially, even as a technical founder, is essential for gathering direct feedback and refining your pitch. And how attending trade shows and creating engaging demos can help generate leads and build relationships with potential customers, even in underserved markets. So I hope you enjoy Zach, welcome to the show.
Zach Rattner [00:02:52]:
Hi Omer, happy to be here. Thanks for having me.
Omer Khan [00:02:55]:
I'm so glad we finally did this. If the listeners knew like how long it's taken us to get this thing scheduled and kind of reschedule, it's quite an achievement. So thank you for making the time today.
Zach Rattner [00:03:09]:
For sure. If something's important, it's worth Doing?
Omer Khan [00:03:11]:
Yeah, totally. Do you have a favorite quote, something that inspires or motivates you that you can share with us?
Zach Rattner [00:03:16]:
I do. I am a big, big fan of the band Radiohead, and they have a lot of good lines where if you digest what they're saying, it's not always immediately apparent. But there's a line on the album Kid A, this one's optimistic. This one went to market and. And it talks about all the hosts of things in general that can go wrong. But I feel like as a founder, being optimistic and still going to market anyway is something that kind of gets me out of bed in the morning.
Omer Khan [00:03:44]:
Yeah, love that. So tell us about Yenbo. What does the product do, who's it for, and what's the main problem you're helping to solve?
Zach Rattner [00:03:52]:
Sure. Yenbo is a computer vision company. We are about 70 folks across the world, about half in the US, half out. And we provide computer vision services to moving companies and property insurance companies. So in both of these markets, if you want to get a quote for something, it's traditionally very labor intensive. Someone has to schedule some time, ring your doorbell, walk around, note down every item that's being moved or every item in the policy if you're getting insurance. And what we provide is a computer vision workflow where you can send your clients a link.
Zach Rattner [00:04:26]:
They can record quick videos of each room in the house, and then the AI identifies what's there, pulls out key attributes for moving. Volume and weight are pretty key. And then we provide that information back so you can have an accurate quote with the real photos of the items being serviced in there. So our business model is to sell to the service provider. So we sell to moving companies and sell to insurance companies, but we provide the whole suite of software where they use it for their end users.
Zach Rattner [00:04:53]:
But the end customer gets it for free, effectively, because our client is the company that's providing the service. Great.
Omer Khan [00:05:00]:
And give us a sense of the size of the business. Where are you in terms of revenue, Customers, size of team?
Zach Rattner [00:05:07]:
Sure. So we have customers in about 30 countries across the world. Probably 70% of our business is in North America, but do have a sizable presence in Europe and Asia as well. We have every day we're processing a couple hundred hours of video. Those can be quick little 20, 30 seconds recordings of each room, all the way on up to longer calls for live video chats. And in terms of revenue, we're in the high seven figures.
Zach Rattner [00:05:36]:
And probably every day we see like on order of a couple thousand inspections being done across the whole Product suite. Cool.
Omer Khan [00:05:47]:
You mentioned you're a team of about I think 70 people. What's the general makeup of the team? I mean with the AI startup do you kind of lean heavily towards people working on the technology or do you have a big sales team or how's kind of the general setup of the team?
Zach Rattner [00:06:04]:
Yeah, so we are yambo AI. We are engineering company. I'm an engineer by training. My co founder, the CEO also is an engineer. Our team is about half engineers. The other half we have operations, customer success, go to market folks. We found that's really key because at least in the business world we're not selling something that's necessarily fun or a game. We want to provide a delightful user experience. But being implementation experts is really key.
Zach Rattner [00:06:35]:
So that's why we have a pretty big team that understands the client workflows and we sort of become expert management consultants almost that we're not just trying to sell software, but we're explaining, here's how you can take cutting edge 21st century technology and, and bring it back to these traditionally underserved by tech communities. And that's why we've ended up having kind of about 5050 engineering versus not just nature of the business that we're in.
Omer Khan [00:06:59]:
Cool. And you know, you guys were founded in 2016 and you were an AI company before everybody was trying to be an AI company. Right. So tell us about like where you came up with the idea for this business.
Zach Rattner [00:07:17]:
Sure. So rewind the clock a bit. It's maybe 2015 or so and there is this academic benchmark, it's called imagenet. And if you're not familiar with it, you can think of it like a thousand way multiple choice Test. So the ImageNet competition would have universities and corporate research labs submit source code to compete in it. And the way it works is you hold up a picture and you'd ask what is this? Of course a human can do that relatively easily.
Zach Rattner [00:07:43]:
But the challenge would be out of a thousand or so potential categories, how do you make algorithms that can identify. And what happened around that time was humans were no longer better than computers at identifying objects and images. The best algorithms beat a college educated human. And what I saw happen then was seemed like the entire Silicon Valley zeitgeist was pointing at self driving cars and drones and these very competitive markets, super ambitious problems to solve. I mean even now as many years later, still not solved.
Zach Rattner [00:08:21]:
Self driving cars still have edge cases, failure scenarios, we still have steering wheels on our cars. And what I wanted to do was find an industry that was not going to see that advancement in technology coming and then just provide an amazing user experience so that people would be able to realize the benefits of the tech. My wife was working at a moving company, so that was kind of the genesis where I had the tech background. She was working at a moving company, she was working in logistics.
Zach Rattner [00:08:49]:
So if there was an issue and maybe a 12 foot truck was sent when you should have sent a 16 foot truck, it was her job to pick up the phone, figure out where do you get the larger truck from and kind of manage all the downstream problems. And the more we learned about the space, the more I realized it's not for lack of trying. It's just really difficult to provide an amazing experience because there's so many details you need to get right.
Zach Rattner [00:09:11]:
In a typical home when you're moving, you may have 300 or so items and all of them can be a little bit different. So how do you plan for a move? How do you make sure you have the right number of boxes on the truck? Seems like kind of simple, but if you bring the wrong number, you have to come back the next day or go and pick up some more when you're supposed to be on the job. So it's just a very difficult problem to be able to solve.
Zach Rattner [00:09:34]:
And that's why it seemed like ripe for computer vision to come along and help.
Omer Khan [00:09:38]:
Okay, great. So you've got the technology and you're seeing it applied in some of the kind of places you mentioned. But you're seeing also these problems in kind of more like day to day world with moving companies. And you're thinking, why do people have to go out? Why can't we use that same technology to solve this type of problem? What did you do to go and validate the idea? Did you, I mean obviously you spoke to your wife and that's kind of one insider that you're getting some information from.
Omer Khan [00:10:20]:
Did you start to try and do the whole kind of thing like line up interviews and go and talk to people running moving companies?
Zach Rattner [00:10:28]:
That's exactly what we did. I think one of the cool parts of the moving industry is it is super fragmented. I think there's 7,000 or so licensed movers in the US all the way, like large companies, all the way down to two guys in a pickup truck. And what we did was we first to validate. You could tell I'm an engineer. We wanted to see how big of a problem is this really. So I went to the Better Business Bureau and they have rankings of complaints that have Been filed by industry.
Zach Rattner [00:10:55]:
And we just pulled the data down. Turns out movers get complained about more than lawyers, more than diet supplements, and more than airlines. So we figured, okay, there's something here going on. And then we wanted to zoom in and see what exactly is it about moving companies that people complain about. And we looked at Yelp reviews, Google reviews, BBB complaints, and did some rudimentary data analysis on the keywords that were being used.
Zach Rattner [00:11:21]:
And what we found was people generally complain if you break their things, if you quote incorrectly, or if you don't show up on time. So we're a software company. We can't necessarily help with the showing up on time part because that's a physical thing, but the prices being incorrect was something that we learned was really an issue. So then from that, we're able to go call multiple moving companies.
Zach Rattner [00:11:47]:
And again, cool part about it being a fragmented space is I can get hung up on a bunch, and that's okay because there's so many fish in the sea. So we did some cold calling. I randomly showed up to a couple that didn't go over too well. You usually just get escorted out of the building, but in the beginning days, you got to do things that don't scale.
Omer Khan [00:12:04]:
So how did you kind of, you know, we were chatting and you were saying, look, I'm an introvert. I'm an engineer. How hard was it to just walk into these places or start cold calling? And once you get those first few rejections, did it kind of make it harder or did that just kind of smooth the kind of the wheels for you and kind of just get you into. Get you into the flow of doing this.
Omer Khan [00:12:35]:
I'm just trying to understand what was going through your head or how easy or hard it was to go and just talk to these people.
Zach Rattner [00:12:44]:
Yeah, it gets easier. I would say it never got easy. I remember the feeling in the pit of my stomach when you park the car, you're in the office, and even if they agreed to meet with you and opened my phone for the 18th time looking for an excuse to not have to do it. So there's a certain amount of convincing myself that I had to do more of a mindset change, where this is an impediment to progress.
Zach Rattner [00:13:07]:
If I want to see if this thing is going to work, and I don't want to just have a fantasy in my head of one day running a company, I'm going to have to get over this. And yeah, you have some embarrassing situations that come up, but I think if something's really important. You can convince yourself that it's worth going through the pain to get through it.
Zach Rattner [00:13:27]:
And I think in a lot of things in business and in life, I mean, you practice a bit, you get better, and maybe you fudge one or two, but we would also work that into the system. So if you have a really important client and you really want to do a pilot with them, or you really value their feedback, put them fourth or fifth on the list so you can get some reps through the system. All learning is good learning. So just you can kind of be prioritizing along those things.
Zach Rattner [00:13:52]:
So I would say it wasn't necessarily easy. I still don't think I'm the best person in the world at doing it. But the goal is to be good enough to get to the next level. Not perfect.
Omer Khan [00:14:02]:
Yeah, it's a good attitude. Okay, so when you weren't being escorted out of the building and you managed to get these people's time, whether it was on the phone or in person, what was the reaction when you tell them that we're going to build this AI solution to do these virtual home surveys? Were they excited about the idea?
Zach Rattner [00:14:28]:
It was a very polarizing suggestion. There was about half of the folks that we would talk to would say, if you can do this, you would completely revolutionize the industry. This is incredible. Can I buy it now? Sign me up. And then we didn't have it working yet, so we made a wait list for those folks. The other half, though, were skeptical and they would just say, yeah, right. If this could have been done, it would have been done by now.
Zach Rattner [00:14:52]:
And that's where as an engineer and as a founder, you usually want to have some secret that you know that most of the market doesn't know. But you got to remember that imagenet thing had happened. So I knew computers are better than people at identifying objects and images, but that's a big, radical, fundamental sea change. So it made sense that people didn't quite understand yet. So for those folks, we didn't say no forever. We just didn't continue following up with them.
Zach Rattner [00:15:19]:
They maybe aren't an early adopter, kept it in the CRM and put a note on it. And if you're specific about the objections, and if they mention, hey, this is never going to work, you can follow back up a year later when you have it working and say, hey, would you like to try it out? Here's a link, free of charge. We'll happy to walk you through a demo. But yeah, it was very polarizing. People would immediately fall into one of those two categories.
Omer Khan [00:15:44]:
How long did it take to get to a point where you felt confident enough that there was an opportunity here, there was a startup potential, and that you guys were going to invest more time in building this product?
Zach Rattner [00:16:00]:
Yeah, it took about maybe two, three months to convince myself that if the tech existed that there would be a business there. We were also, for the conversations that went well, we were experimenting with different business models. So we even negotiated pricing and did these non binding letters of intent. I mean they're not really that they don't carry any legal weight, but they would help us articulate if such a thing were to exist. Is $100 an estimate. Too much is $10.
Zach Rattner [00:16:28]:
So we got it to the point where we had a list of clients that had basically agreed to pay a reasonable rate per survey and do it assuming you're able to do XYZ abc. So that took a couple months. The next question that came after that though is is it possible to do what we were signing up to do and what these people are expecting? And that part took a couple of years to get really, really resolved.
Omer Khan [00:16:53]:
One question about the letter of intent, how did you frame that with these customers? Like how did you get them to sign something?
Zach Rattner [00:17:01]:
So we did it as a wait list. We realized we're not going to have infinite capacity. I mean, gmail took what, 10 years to get out of beta. So we figured, hey, when this thing does exist, I'm not just going to open the floodgates to everybody. I'd like to take one client on, then three more, then five more. So we pitched it as expressing interest in reserving a slot in there.
Zach Rattner [00:17:23]:
So there was no cash, no upfront ask immediately, but it was if you're interested and you'd like to be on this list, would you be open to monthly check in calls? And here's what the pricing would be. But again, you don't have to pay anything till it actually exists. And what we found then is you get the right kind of customer. When you do that, you get someone who sees the potential of the technology, who wants to be first to market and everyone else.
Zach Rattner [00:17:49]:
You'll need to build out more features, add more bells and whistles down the road. But you want your early adopters to be unapologetic supporters of what you're doing. And that process kind of helped filter those things out. If they started nitpicking about SLAs and uptime and can you translate into this language, they're all reasonable concerns, but just not for customer number one. So we would note the concern, park it and then go look for somebody else.
Omer Khan [00:18:13]:
And did you actually get them to sign a piece of paper or e signature or something?
Zach Rattner [00:18:17]:
Yeah, we actually did Adobe fill in sign again, it was one page and it said, I think it was something to the effect of like if Yumbo had an AI powered virtual inspection solution that could identify objects from a customer's video, then we would be interested in paying 10, 20, 50, 100, whatever dollars per survey for it. It was like very, very short and brief, but I think the point was to be able to articulate the value enough. And then also you're not really negotiating so you can be a little bit more abstract with it.
Zach Rattner [00:18:49]:
So we'd say, would you pay $1,000 a survey? They'd say never. You kind of learn how they're thinking about it, the expected ROI that they want to get out of it. And that really helped when we're building the product to understand what is meaningful, what moves the needle for my customer. Because we don't want to just extract a bunch of cash from our clients. We want, want to help them go grow, win more business and then participate in some of that upside.
Omer Khan [00:19:11]:
Yeah, I think that was a really smart thing you guys did. When you do these types of interviews and people say that sounds great, it's tempting just to stop there and say they love it and when we come back with the product, they're going to pay.
Omer Khan [00:19:29]:
But I think to get to that last mile and actually have them sign something, even though, as you say, you know, not legally binding or anything, there's another level of commitment or a data point that you're getting that they're interested enough to be able to, you know, willing to do that. Right. So I think that was really smart. The other thing you said was it took a couple of years or a few years for actually for us to actually build the product that we wanted to. Was there something in between?
Omer Khan [00:20:08]:
Did you come back with a first version or an MVP with these guys? How long was it between the time that these customers or potential customers were signing these, Lois, to the point where you came back and put something in front of them that they could start trying?
Zach Rattner [00:20:23]:
Sure, yeah, it was about a year or so from LOI sign to here's a login, probably about two or three years to the point where it was enough to be a viable business. And this, I think was really key. And for any listeners who are thinking about applying AI or machine learning to your end to end products, I Think this was a really key finding was if you expect the AI to be perfect, there will always be scenarios it doesn't quite work in. AI is fundamentally probability based, even a human, right?
Zach Rattner [00:20:57]:
If I ask you like, hey, read the text on the spine, what book is this? People aren't going to be perfect at reading it. So if you make your use case so high stakes that it needs to be perfect, you're going to have implementation issues. So what we did was we understood the customer's problem really well. They spend a lot of time burning fuel, sitting in traffic, wear and tear in the vehicle.
Zach Rattner [00:21:20]:
It's not a particularly awesome customer experience to have a handwritten list of items and then sometimes the prices change, you don't quite know why. So we had an intellectually honest value proposition which was still intact if the AI wasn't perfect. So what I mean when I say that is typical home may have 2, 300 different items. If our AI could only detect 5, 5 or 10, we were still saving time and we were giving pictures of the actual items that were there in the move.
Zach Rattner [00:21:51]:
So the mover may have to go through and do some review and spend some time. It's not completely automatic, but they are providing better documentation, they're increasing their win rate. They can go into geographies, they don't physically have boots on the ground in. And there were enough reasons that someone would want to do that that it was okay, that the AI wasn't perfect. And that gave us a reason to exist another day.
Zach Rattner [00:22:15]:
And then over time we were able to say, hey, this product that we put together, the AI can detect 10 items, then 50, then 60, then we kind of gradually worked our way up, but we were really careful not to set the wrong expectation that it was going to be a completely driverless, self driving car, no steering wheel, and you can just go anywhere in the world by the click of a button on day one because that would have set us up for failure.
Omer Khan [00:22:39]:
How did you guys fund the business?
Zach Rattner [00:22:42]:
For the first few years we did an early seed round with some angel investors and kind of bootstrapped that way. AI is really expensive, just the compute is a lot. But we tried to not get too hung up on raising gobs of cash and doing a bunch of crazy things. So we did make sure that like the first dollar we took in was actually revenue. And then from there the investment was always to accelerate and to develop the product further and to make the AI better.
Zach Rattner [00:23:14]:
And I think that was really key where we never really got too detached from reality. That we wanted to make sure that the product that we're offering is valuable to our customers so that we see it as like an accelerator, but you have to already be on the right track and heading in the right direction. But we didn't want to just take venture dollars and then go figure out what to do next because that's a very inefficient way to operate.
Omer Khan [00:23:36]:
Yeah. Okay, so you go back to those customers about a year later, give them a login and then what happened? You'd been talking to them about this vision of how AI and this product could, could make their lives better. And some felt it was, revolutionized the industry. What was the reality of that first version of the product?
Zach Rattner [00:24:06]:
It was bumpy, it was rough. So I think our AI could detect maybe 10 or so items really well. We had no full time product designers, no one with psych backgrounds. So the user interface looked like it was built by a backend engineer, me. Um, so we had, we had some churn problems. We had bad expectations where people were expecting it to see behind closed doors, work in the dark, just stuff that is like literally never going to happen. Um, but like the promise was there and the right group of customers got value.
Zach Rattner [00:24:41]:
So some people came and then left, but other people came and then expanded. And what we found was certain clients were able to expand the geographies they operated in. It's traditionally very expensive to open a new satellite office as a mover, you have to rent a new warehouse, trucks, crew, all these kinds of things. But with Yambo, you can buy Google AdWords in a new geography and quote the jobs and then not really actually drive out there unless you win it.
Zach Rattner [00:25:06]:
So what we saw is people were able to decrease the cost of expanding their business. People will be able to service leads after hours. If someone's working 9 to 5, they may not be home to walk around and answer the door, but you could text them a link, they could do it at their own convenience. So what we found was the initial archetype of a customer that did well in the early days had one of those initial pain points.
Zach Rattner [00:25:32]:
And then as the technology got better, as we added on more features, we were able to broaden the applicability. But what we found was that we needed that initial group where they felt some kind of pain point that our product at that point in time could serve. We don't like selling technology that's going to be valuable based on future performance.
Zach Rattner [00:25:52]:
It's like if you sign in and you get a login, you should be able to do something today that's valuable and wasn't the easiest, but we were able to find that group of people, then expand from there.
Omer Khan [00:26:02]:
Yeah, I think that it's not just finding people with the pain, but like you guys were doing. It's also about finding those early adopters, people who are more motivated or just kind of more inclined to use this type of technology or to try things versus the people who have the pain. But the minute, you know, they type in their password wrong and can't log in, it's like they're game over. Right. They're not interested anymore. That's not your first ideal customer initially anyway.
Zach Rattner [00:26:37]:
Yeah. And if you legitimately don't have capacity to serve everyone, then you can ask qualifying questions. And we've had a couple clients that were asking to be in the earlier cohort because it's just human nature. Right. Who would volunteer to be second? Everyone wants to be first. But there were some folks who just mentioned, hey, I don't think you're going to get what you want or what you're expecting to get if you go live with us on this day, I think you should go into the next group.
Zach Rattner [00:27:01]:
And sometimes people bristle, but at the end of the day, you got to do what makes sense. And I just didn't want people to sign up with expectations that I know I couldn't live up to. Because then you're going to get a cancellation notice the next month when the renewal comes up. Right.
Omer Khan [00:27:16]:
So you said it was bumpy initially. Obviously over time the AI got better, the product got better. That story about your customer's wife that we talked about, when did that happen? Just tell us a story. I'm trying to figure out. Was that very early on?
Zach Rattner [00:27:38]:
Sure, yeah, this was early on. So the Yambo product for moving someone scans a quick 20 second video. The AI summarizes it into some images and then shows what's there. So if you want to scan this room, you'd see tv, printer, book cartons, needed to pack it. And this particular room that we scanned was pretty busy. There's a lot going on, maybe 80 or so items. But the mover who was testing it out, his wife was standing in the room and she was kind of stretching like this a bit.
Zach Rattner [00:28:07]:
And our AI accidentally tagged her as a surfboard, which is not a kind of problem that a human would ever make. But if you're AI and you're just seeing lines and shapes and colors, that person bent like this, you can kind of see why. But those are the kinds of problems that I think a lot of AI companies face, where from a technical standpoint, it's not really like a different kind of failure than calling a sofa a love seat, but from a sociology standpoint, it's dramatically different.
Zach Rattner [00:28:40]:
And those were the kinds of things that we had to go back and actually became a barrier to adoption, as the AI would detect like 80 things correct. And everyone wants to talk about the one or two mistakes it would make. Also, we found laundry baskets in bedrooms were often being called barbecue grills, because usually barbecue grills are covered. You just see fabric over some contours. But you and I, as humans know you don't really keep a barbecue grill in a heap on your bed in your bedroom.
Zach Rattner [00:29:08]:
So we had to build out in the early days. Our AI team called it ugly hacks. I called it our common sense engine. And we'd say things like, if you see refrigerators in the bathroom, they're probably white panel doors. Just call it a door, don't call it a refrigerator. And we had all these ugly hacks just to make the AI not make stupid mistakes, because those are the kinds of perceptions you're not associating your brand with trust if you make glaringly obvious mistakes. So it was kind of like he brought it up in jest.
Zach Rattner [00:29:38]:
It was funny. Took him maybe two years to stop bringing it up as a joke. Um, but it did actually make us reevaluate how we were being perceived. And the, the product did change as a result of that.
Omer Khan [00:29:48]:
Okay, obvious. So obviously you're, you're improving the AI technology and you've got these wonderful hacks in place to, you know, help you make it through to, you know, the next level, you know, next kind of wave of improvements that you're going to roll out. What did you do to manage expectations with customers when they're excited about the technology? And you said it was pretty accurate, but they were picking up on the 1, 2, 3 things that it didn't recognize or do a great job with. So how did you manage that situation with customers?
Zach Rattner [00:30:27]:
It was not a one and done thing. It's what you do every day. So in our sales decks, we made sure that we pitched it as something that saves time but does not eliminate a human. We put in a lot of energy and effort. I don't feel great waking up in the morning building Terminator technology. So we made a point to say, hey, these are commission based salespeople. You can close more jobs, focus on growing your business and being intellectually honest about this.
Zach Rattner [00:30:53]:
Actually, if people Say that's not going to happen, then ask them why, figure out why and then come up with proof points and show that it's able to to improve the top and the bottom line. So I mean people do always bring up individual mistakes here and there, but I think it's machine learning, it's probability based. People understand that. But by having that core value prop around, okay, maybe we did call a sofa a love seat or a wife, a kayak or a surfboard or something.
Zach Rattner [00:31:20]:
But you got a quote out and the person came to your website at 7pm when no one was in the office. Would you have preferred that they just shopped around somewhere else and you would have lost the business? So we kind of made sure that people were understanding it the right way. But then also every time they were right, we'd make sure that we'd catalog it, we'd know we had telemetry.
Zach Rattner [00:31:39]:
So if the AI was getting corrected, even if you never said anything, we would still know because like any AI product, you always want to be iterating and always want to be improving.
Omer Khan [00:31:48]:
I want to talk a little bit about sales getting to that first million in ARR. Both you and your co founder Sid are engineers and many founders in that situation would try to get a salesperson or some kind of growth marketer or whatever on board as quickly as possible so they didn't have to talk to customers or try to sell anything. You, you guys were pretty deliberate and you decided that you were going to do the selling even though you had no experience.
Omer Khan [00:32:27]:
Why did you do that and kind of what was the experience for you?
Zach Rattner [00:32:32]:
Sure, I think it made sense for the time and place we're at today. We have sales folks, they're better than I am at it and I don't necessarily miss those days. However, in the early days when you're selling nascent technology, you, the market doesn't quite understand it yet. You don't even quite 100% know is it going to be perfect, is it going to work, is it going to be viable or not. I didn't want to have another layer in between on hearing that feedback and getting those objections.
Zach Rattner [00:32:56]:
And I think it goes back to those early days when I was telling you when we were looking at the better business reviews, we were talking to prospects is I got told directly this is important to me, I wouldn't pay for that. And we decided until we got to a million in arrangement, I didn't want to be trying to outsource because I don't know what works or not if I bring someone on and they can't close any deals and they come back and say the product doesn't work.
Zach Rattner [00:33:17]:
I didn't have enough history with it to really understand what's right, what's wrong. So I don't think I was the best salesperson. I would pretty much cave when any objections came up. And maybe despite ourselves, the product was good enough, we were able to get to that milestone. But when you're still setting it up, you want that direct feedback line. And if I build something that I think is going to be amazing and it's not, I don't want it to take two weeks to filter back to me.
Zach Rattner [00:33:43]:
I want to just be told directly from the customer what's working and what's not. So I think in that kind of environment, it was pretty clear when it was time to hand it off. I mean, a million is kind of like an arbitrary number. But what we saw was the process was starting to become repeatable. We started to look at things like cycle time, how long does it take to close a deal? What are the common questions that come up? What are common payment or pricing objections, all these kinds of things.
Zach Rattner [00:34:11]:
I wasn't really learning anything new by doing it anymore. So that was a good sign that it was probably time to grow up, let somebody else take that over, and then hand it off.
Omer Khan [00:34:20]:
How are you generating leads? How are you finding these customers?
Zach Rattner [00:34:24]:
So the moving market is very networked. So we found trade shows worked really well for us. If I have an office in San Francisco, you have an office in New York, where we're not really competitors. Like, if someone's moving across country, I may hire, I may have my crew, go pack up the home on the origin, and then your crew goes on the destination. So what we found was going to these trade shows where all these folks are at, and then referrals around.
Zach Rattner [00:34:48]:
You have a happy customer, you're able to improve their top and bottom lines. Finding out who do they tend to work with, and kind of working that angle has worked out pretty well for us. But I think it just comes down to finding who's hungry for the value you're providing and how do you bring it to them. And what we found for us is movers are all over the world, but when you have a conference, everyone's in one room. So that worked out great for us.
Omer Khan [00:35:10]:
Yeah. And it turns out that events and trade shows have turned out to be a great growth channel for your business. It's something you still do today. I think that I'd love for you to explain how you were setting things up in a booth and helping people experience yambo rather than just telling them about it. But I think it's also funny because in your book, which we'll talk about in a couple of minutes, the first thing you talk about is having a booth at an event. And it was like 900 bucks.
Omer Khan [00:35:49]:
And it's like, do we really want to spend $900 on a booth? And that's the reality for many early stage startups. That's a lot of money. But it turned out to be a good bet and a great way to meet customers and generate sales. But, yeah, just tell us about what was that booth experience like, what were you doing?
Zach Rattner [00:36:12]:
Sure. So year one, you're absolutely right. Sponsorship was $900. I'm an engineer. I did the math. I said, I can sit at the bar and buy $9 beers for 100 prospects and it'll be the same as getting this booth. We didn't have the product yet, so we did that second year. The product was a bit more mature. The venue actually changed the rules and says, you can't just freeload in the bar area unless you have a pass.
Zach Rattner [00:36:34]:
So we did get the booth there, and what we were finding is people were generally interested but skeptical because a lot of these folks have been doing surveys inside people's homes for 20, 30, 40 years. So to come along and say, oh, I have AI, that does it. People would kind of roll their eyes and say, yeah, right. So our booth was very simple. Again, I never designed a booth before. Probably wouldn't pay me to decorate a room or anything. But we had that idea in mind around people are going to be interested but skeptical.
Zach Rattner [00:37:02]:
So what we did is we flew out to the event was in Florida. So I'm in San Diego, fly across the country, took an Uber xl. The big, like, minivan comes, picks you up. Went to TJ Maxx and just bought some furniture. We got a sofa chair, a love seat, a lamp or a little nightstand. A lamp. And the booth was just putting the furniture there. And when we told people what we were doing, they would say, oh, really? And I just hand them a phone.
Zach Rattner [00:37:28]:
I'd say, yeah, point it at the furniture and you'll see the results right away. And they'd go and they'd do that and then, like, their faces. It was cool. It was like you're a magician almost. Their faces would light up and then they'd start objecting. Well, of course you picked that furniture. So I brought the receipt and I said, no, look, this was purchased like 45 minutes ago. When I was putting this demo together back in my office, I had no clue what I was going to find.
Zach Rattner [00:37:51]:
I just wanted to see what would fit in the Uber. And what we found is that, like, being able to do it live and be real shows that it's. You're a credible person and that you're not pitching vaporware and that, that kind of experience. We've had a couple trade shows like that in the early days where there was one time we even paid for it. We were in the black before we even came back home because we closed enough deals just from. From that on the spot.
Zach Rattner [00:38:14]:
Convincing, but I just think it's being intellectually honest, being able to be willing to do it live. And it comes back to our engineering roots around we're a technical company and we stand behind what we do. And is it the best way to get sleep the night before? Absolutely not. But it makes for a really convincing demo just to do it real and do it live.
Omer Khan [00:38:32]:
Yeah, that's great. Show me. Don't tell me. Right, that's exactly what you were doing. Love that. Okay, we should wrap up. Let's get into the lightning round. I've got seven quick fire questions for you, so whenever you're ready. What's one of the best pieces of business advice you've received?
Zach Rattner [00:38:50]:
Just get started. You don't really know what you're going to get told until you actually do it, so don't convince yourself in your head. Just get started.
Omer Khan [00:38:58]:
What book would you recommend to our audience and why?
Zach Rattner [00:39:00]:
I think Zero to One by Peter Thiel is a good fundamental exposition on startups and how to change an industry and disrupt the world. I think any founder should read it if they haven't already.
Omer Khan [00:39:12]:
Great. And then we also got to mention your book. You wrote the book called Grow Up Lessons from an AI Startup.
Zach Rattner [00:39:19]:
I got one right here.
Omer Khan [00:39:20]:
Awesome. So people can. We'll talk about where people get that in a second. But how did you find the time to write a book?
Zach Rattner [00:39:28]:
A lot of little things. I was disciplined. I didn't binge. I was disciplined. I booked 90 minutes each morning before the workday. Sorry, 6 to 7:30 in the morning. And I did three days a week because I figured five is too ambitious and it took about a year. But what I was finding was there was just so much happening in the AI space. I felt like I had things to share. I was repeating myself a lot to new managers who were hiring things along those lines.
Zach Rattner [00:39:53]:
So I wanted to take the time to package it up and share it with a wider audience.
Omer Khan [00:39:58]:
Yeah, love it. What's one attribute or characteristic in your mind of a successful founder?
Zach Rattner [00:40:05]:
I would say resilience is key, is that anyone can conquer the world on a good day. But to be told no, to have a setback and to be able to brush your ego aside and figure out what you're going to do about it. I think that's what separates true founders from people who are just interested in startups.
Omer Khan [00:40:21]:
What's your favorite personal productivity tool or habit?
Zach Rattner [00:40:24]:
This is going to sound really low tech, but my to do list is I email myself and I use Inbox zero. I've tried every other tool on the planet but it's just so hard to beat and I'm in my inbox all day.
Omer Khan [00:40:33]:
Anyway, what's a new or crazy business idea you'd love to pursue if you had the time?
Zach Rattner [00:40:38]:
I think there's a lot of non tech areas where AI can be impactful. I would love to open an art gallery powered by AI or one of these industries where they traditionally haven't been served. But you can take a new and interesting angle on it. Again, I think I got time to write a book. I don't think I have time to do that today, but maybe 10 years from now we'll see.
Omer Khan [00:40:59]:
What's an interesting or fun fact about you that most people don't know?
Zach Rattner [00:41:02]:
I spent five years living in Vermont and I grew up with two llamas and it's one of those things you got to show, don't tell. So I had to go back to my parents house last Thanksgiving and scan some photos because nobody believed me. So I had to be able to have photos I could send out.
Omer Khan [00:41:17]:
That's funny. And finally, what's one of your most important passions outside of your work?
Zach Rattner [00:41:23]:
I've got a family, got three kids all under the age of six, so don't have a ton of time left over after hanging out with them but love the outdoors. Was just out in a cabin in the woods with them last week and I just think spending time with family, hanging out, doing probably boring things that you wouldn't want to talk about on a podcast, but meaningful and fulfilling things with close friends and family.
Omer Khan [00:41:47]:
I got to say you always struck me as a very chilled guy for somebody working on a startup and having three kids under six, that's a lot of stress there.
Zach Rattner [00:41:58]:
It's a learned skill. Yeah, I think me freshman year in college was super not chill then you just kind of learn that you learn to trust your problem solving skills as you get older is that it's not like I've seen it all before, but I know how to handle it if something comes up. Yeah.
Omer Khan [00:42:11]:
Okay, great. So, Zach, thank you so much for joining me. And also it's your birthday today, so happy birthday. I appreciate your making the time today. If people want to learn more about Yembo, they can go to Yembo AI that's Y E M B O dot AI. If people want to check out your book, they can go to growupfastbook.com or find it on Amazon. We'll include links in the show notes and if folks want to get in touch with you, what's the best way for them to do that?
Zach Rattner [00:42:42]:
Probably the easiest is find me on LinkedIn, Zach Rattner. Or you can type in Yambo. It's not hard to find me, but I'm on there almost as much as I'm in my inbox. So feel free to send me a note.
Omer Khan [00:42:50]:
Sounds good. Thanks man. I appreciate you making the time. Great conversation. Congratulations on everything you guys have accomplished so far and I wish you and the team the best of success.
Zach Rattner [00:43:03]:
Thank you so much, Omer. Happy to be here.
Omer Khan [00:43:05]:
Cheers.
