UP060: Perceive // using spatial recognition to measure consumer behavior in the real world

In All Episodes, SaaS, upside by jayclouseLeave a Comment

view episode transcript

Everett Berry 0:00
It used to take maybe years to train a neural network. And with these new techniques it could take, like, months. Since then it’s gotten, now you can train a neural network of that size in, like, two minutes.

Jay Clouse 0:14
The startup investment landscape is changing, and world class companies are being built outside of Silicon Valley. We find them, talk with them, and discuss the upside of investing in them. Welcome to Upside.

Eric Hornung 0:41
Hello, hello, hello, and welcome to the Upside podcast, the first podcast finding upside outside of Silicon Valley. I’m Eric Hornung, and I’m accompanied by my co-host, Mr. Ancient-Baths himself, Jay Clouse. Jay what’s going on, man?

Jay Clouse 0:56
Oh, man. Yes, you remembered!

Eric Hornung 0:59
You really, like, shoved it in my face. You talked about it a lot. So I had to remember.

Eric Hornung 1:03
Friend of the podcast Mallory and I just went to Chicago. I’m back in Columbus now. But we went to Chicago for a long weekend. And one of the activities that I plan — she planned almost the entire trip — but I planned a couple of things, one of which didn’t happen, and the other that did happen is this ancient baths trip that you’re talking about at Aire, A-I-R-E.

Eric Hornung 1:24
It looks like ‘air’ with a silent E. That’s what I’m going with.

Jay Clouse 1:27
I listened to a YouTube review of it, and they kept saying Aire, but not quite. They said it better. I’m failing in some way, but I can’t figure out how. It was awesome. So great.

Eric Hornung 1:39
So the, you failed at saying the name, but you succeeded at actually going to the place and enjoying yourself. You got a massage. Is that what happened? I don’t really know what happened. Explain to me.

Jay Clouse 1:48
Yeah, so these baths , which claim to be Roman and Greek baths, I believe, there are a bunch of different experiences that you can enroll into. You choose your experience in this space, and the one that I chose for Mallory and I was a couple’s experience. And we had a 45 minute massage, followed by almost two hours of exploring something like five or six different types of baths in the space, different temperatures, different salt content, there were steam rooms, there was ice plunges. It was awesome. And Mallory has never had a positive massage experience in her life, which is more of a commentary on me as a boyfriend than anything else. But she loved it. Absolutely loved it.

Eric Hornung 2:34
Do you think there’s a video floating around of you guys floating around? Like do they have…?

Jay Clouse 2:37
I don’t think so.

Eric Hornung 2:38
No. No experiential kind of campaigns going on inside the bathhouse?

Jay Clouse 2:42
They might. I was not aware of any cameras in the space. I didn’t see any of them. You are not allowed to have your phone in the bath itself. It was awesome. It was just like, you, you really lose…I mean, they have on the marketing materials like, time does not exist here. You lose track of time. It’s just a really, relaxing, dim, awesome experience.

Eric Hornung 3:04
It sounds like you are delighted. And today’s guest is all about delighting customers of retail. So this is my stretch to get us to today and get you out of thinking about your massage.

Jay Clouse 3:15
It wasn’t even a stretch. It was, it was a slam dunk.

Eric Hornung 3:19
Slam dunk that I hit off the back of the room.

Jay Clouse 3:22
Speaking of good experiences within physical spaces, today we are speaking with Everett Barry, the founder and CEO of Perceive. Perceived is a consumer behavior analytics company for non digital or physical spaces using 3D cameras and artificial intelligence. The company was founded in 2015. It’s based in Indianapolis, Indiana. Finally diving into our neighbors to the west. Eric, we’re going to get some, we’re gonna get some buzzwords on this. We’re going to talk about AI, we’re gonna talk about machine learning.

Eric Hornung 3:53
As you know, whenever I hear the terms ‘machine learning’ and ‘AI’ — oh man, Jay, I’m going to swear here –my bull detector goes off. So I’m going to come in a little skeptical, but I just want to hear about the background. What, what is, what is really happening behind the scenes, behind the two big buzz words of the day?

Jay Clouse 4:11
Well, in an effort to soothe your bull meter, Perceive has raised $1.2 million in grants, most of which came from the National Science Foundation in the form of an SVIR grant. So I’m guessing there’s some hard science involved here, Eric, and I’m excited about it. We get a little excited when hard science comes on the podcast. And applying it to the real world physical spaces. I don’t know what the future of physical spaces is, I don’t know if they’re on the rise, on the decline. It seems like they’ve been on the decline for a while, but I’m not sure what the latest is.

Eric Hornung 4:43
I can tell you one thing. They will exist.

Jay Clouse 4:45
That’s true. Alright guys, well, we’d love to hear your thoughts on this interview as we go through it. Feel free to tweet at us @upsidefm or email us hello@upside.fm. We’ll get into interview with Everett. Eric, how many people have you assisted in hiring?

Eric Hornung 5:01
I used to do some interviews back in the day hiring for a business fraternity. And now I do some interviews hiring for my full time job. So I’d say I probably had a part in hiring or bringing on at least 100 people.

Jay Clouse 5:15
How many of those people did you do the work of actually finding to bring into interview?

Eric Hornung 5:19
It’s way too much work, Jay, I don’t, I don’t do that. That’s too much.

Jay Clouse 5:22
It’s a lot of work to find high quality talent to come in and interview. And our friends at Integrity Power Search help you do just that. They are the number one full stack, high growth, startup recruiting firm between the coasts. They partner with venture capitalists, private equity groups, and CEOs to build amazing teams for the world’s most disrupting companies. Eric, in 2012, Integrity Power Search has executed over 600 searches, and they’re on track to do more than 200 in 2019 alone. That means high quality candidates in front of you that you can interview without having to source them yourself.

Eric Hornung 5:53
600 sounds like way more than 100.

Jay Clouse 5:55
Way more than 100, and think about all the hours saved not finding those candidates yourself. So if you guys are interested in working with Integrity Power Search, you can go to upside.fm/integrity to learn more about their team and how they can help you with your hiring.

Jay Clouse 6:16
Everett, welcome to the show.

Everett Berry 6:18
Thanks, guys. Great to be here.

Eric Hornung 6:19
On upside. We like to start with a background of the founder. Can you tell us about the history of Everett?

Everett Berry 6:25
Sure. So I grew up in Indiana, went to Purdue, and I studied computer engineering there. And specifically, I worked on an area called multimedia systems, which is kind of video images and how you build large systems that handle various kinds of media. And in doing that, I started working on a project where we were looking at live streaming cameras from all around the world, and also on Purdue’s campus. Purdue has this interesting thing where, at least when I was there, they had live video feeds for a number of spaces like labs, kind of union common areas. So I started writing programs to look at these video feeds and try to pick out, like, how many people were in the feed, how long was the line for coffee, how crowded were labs or dining areas. And from there, I kind of took the engineering track all the way into product, and then eventually, the CEO and founder role of Perceive.

Jay Clouse 7:27
it seems obvious to me that a lot of those video feeds are probably set up for purposes of security. Were there are other reasons that there are live video feeds that you were tapping into?

Everett Berry 7:36
I don’t know why they are publicly accessible. I think it’s probably just the university setting. And, and I should say they’re accessible within the internet. And I guess I should also say, I don’t know if this is still the case. But regardless, it kicked off a string of interesting thoughts for me and the folks I was working with back then. And it led us to start thinking about what else we can do with these feeds that might be commercially useful.

Eric Hornung 8:04
How did you come about writing software to be like, this is a human? I’ve always been fascinated by that.

Everett Berry 8:10
Yeah, so it’s a very challenging problem. Actually, that’s part of the thing that attracted me to it. The core problem is actually one that we also experience, which is that it’s sometimes hard to tell what’s a person and what’s not a person. And if you’re far away from someone or even if you’re just looking at a video feed, the trick is to kind of come up with some useful approximations. For example, like in a retail store, almost all the moving objects are people, right? There’s no horses or things running around. So you can do some, you can do some engineering things. And I think I really just enjoyed the problem of saying, well, could we get 90% people and 92% people? And there’s, yeah, there’s a variety of tracks. It’s a whole massive field. And actually in recent years, it’s become much, much easier, which is one of the reasons I think this company is possible at all.

Eric Hornung 9:05
Why has it become easier?

Everett Berry 9:07
So there’s been a number of breakthroughs in AI and machine learning. And a lot of people are familiar with this by now, but just to recap, in 2012, this new style of training came out, which allowed people to not only accurately detect things on kind of a big data set of images, like you could detect a tiger on a boat and that sort of thing. But the key thing was, you could take that network that we trained and apply it to other images and video that we hadn’t seen before, and it would still work, which was which is called transfer learning, which was actually a massive breakthrough. And so we we no longer had to write basically a custom thing where we would say, okay, maybe a person is six feet tall or five feet tall and roughly this shape and size. We could actually just give these algorithms pictures of people and objects, and the algorithm would figure out internally what it felt those people should look like. And so that has made this whole field of computer vision, it’s called, just much more accessible in recent years. And I think that’s also why you see an explosion of companies in this area, including Perceive.

Jay Clouse 10:13
Talk to me like I’m even dumber. So this 2012 new train that came out, is that something that somebody else had trained and they said, hey, we’re opening this up and making it open source, you can use it? Or is that a new breakthrough in computing in general?

Everett Berry 10:29
It was several things. We could probably be here for a long time. The basic idea was the graphics cards in your computer, which you might use to play video games, or actually to, its handling all of the streaming of this, this podcast and the video associated with it. Some researchers were able to use those to run a neural network, which made a previously very difficult problem much more, much more attainable. So for example, it used to take maybe years to train a neural network. And with these new techniques, it could take like months. Since then it’s gotten, now you can train a neural network of that size in like two minutes on a, you know, reasonably powerful computer. So there was a big breakthrough there. And the other piece was there was some sort of, like, algorithm or maybe design improvements to the way that we built the software that, the way that we taught these networks what a person look like, that made it work much better. So those two things combined in 2012 was sort of this watershed moment in AI. And it’s what’s led to essentially everything that followed. We still use more or less the same techniques now than we did that were developed back then.

Eric Hornung 11:44
What’s the biggest unsolved problem in computer vision right now?

Everett Berry 11:48
Yeah, so that is a great question. I would say it is, for me, the largest unsolved problem — and there’s probably some debate about this — is recognizing what’s happening in video. If you take a single image, you can run that whole thing through and decide what’s in that image, like, there’s a face or a boat or person. If you take a sequence of images and you’re trying to decide what’s happening, like is someone driving, are they walking, is a, you know, person shopping? That problem is still not, we still don’t have a good way to solve that. And so for me, that’s, that’s the largest central problem. It’s actually the thing we started with that perceived way back when it was more of a research company. And that’s where we go from there. There’s, I’m sure many people would have different answers to this, that question.

Eric Hornung 12:37
You know, remember that like, passing the basketball thing, the video and the gorilla like walks by in the background, because humans have like a problem focusing on multiple things at once? Do computers have the same limitation?

Everett Berry 12:49
No, so it’s one of the things that makes Perceive I think just a fascinating company to work on. And one of the things that makes us so exciting, what makes our products exciting, is that if I asked you to watch video for a long time, or I asked you to pick out the gorilla and on the first try, you would, you would struggle with it. And this is, our brains are not meant to do some of these tasks. They’re not meant to stay alert for a long time. Even as I’m talking with you guys, I’m actually looking all around the room and thinking about 10 things. And I probably couldn’t even tell you what I said two sentences ago. So computers don’t have this issue. And that’s one of the great things about computers that we’ve used for files and internet and all that. And due to those breakthroughs I was just talking about, we’re now able to apply it to things like watching video, which is super, super powerful, and is leading to just a huge number of products that are actually saving people a lot of kind of grudging work. It’s not a fun job to sit and watch video for hours and hours and hours a day.

Jay Clouse 13:51
I have one more kind of basic question before I dive deeper into Perceive and your story there. We’ve talked about AI, we’ve talked about machine learning, you went to Purdue to learn multimedia systems. How did you start to learn how to use things like neural nets? Was that part of formal education, or was that personal interest that you had to dive into some of these buzz worthy topics that are kind of in the Zeitgeist?

Everett Berry 14:14
Yeah, so I was pretty lucky, I think. When I was a freshman when these things came out, and I started working on this project, when it was kind of the year later, when some the software was more accessible. So it was just a coincidence of time. And if you were in computer vision at that time, that was definitely something that you were at least trying, if not actively, working on. So that was really fortunate. And then I think the other thing that’s been fortunate just how well it all works. I mean, it really does work amazingly well. And so, there’s a lot of questions about AI in general as a society, but I can tell you from an engineering standpoint, it is a massive breakthrough and has worked really well for some of the things that Perceive is working on.

Eric Hornung 14:55
So we’re sitting there, we’re looking at closed caption TV around campus, and we’re saying there’s this many people in the coffee line at the cafe. What’s the next step of that to on the on the way to Perceive?

Everett Berry 15:08
Yeah, it’s a long story. So Perceivev that actually almost more than six years old at this point in terms of conceptual concept and working on it. The next thing we did was we said, in order to bring some this technology the, everyone knows the best way to bring interesting products out is to commercialize them. And so we started looking for ways to commercialize some of the software we’re writing or some the ideas we’re thinking about. And we ended up interviewing a huge number of people in retail and businesses where it seemed logical that like, this kind of thing could be useful. And we settled on a specific set of problems in retail, and then we ended up writing these NSF grants. So there’s this thing called the NSF SPIR grant. And I actually received this week I graduated, so the week I graduated, the NSF was like, here’s a quarter million dollars to go start this company, which was kind of a trip. And that is how, that is how Perceive got got started. I was planning on working on it anyway that summer and into the fall and seeing how far we could take it. But we ended up funding the company right away. And that sort of kick started everything that followed. And so, yeah, very grateful to the NSF that they saw the promise that we were talking about.

Jay Clouse 16:26
If you’re in the shoes of the NSF, and they’re awarding SPIRs, and they get the Perceive application, generally my perspective has been that SPIR NSF grants go towards things that they see as impacting society in a positive way. So what is it about the application for Perceive, because you could see where that, I could, I could see where this is a very capitalistic, commercialized product. So what was the application like, and what do you think they saw on that application?

Everett Berry 16:56
Yeah, sure. So there’s another, you talked about the gorilla video. There’s another video I love on the internet, which is, which we actually incorporated in this TEDx talk we did, where there’s a very busy pool, there’s probably like 150 kids in this pool, and one of them is drowning at the whole time the video is playing, and it’s impossible to see which one it is. You could play the video on loop and probably not see them five times in a row. And eventually the lifeguard jumps in and saves the kid. So, you know, when you think about lifeguarding, that is totally an application of what I was talking about, where you just have this sort of arduous job of keeping track of 100 different moving splashing bodies. And you’re required to be pretty vigilant, pretty alert, and in the end, some kid’s life is may be at stake. With a tool like Perceive and some of the software that we’re working on, you would be able to, first, spot that kid sooner and, second, probably save them before there’s any type of alarm or damage or anything like that. And so the idea of observing the people in spaces that we work in has wide ranging applications. So you can imagine, for example, a, a city street where there’s someone jay-walking and the car doesn’t see them, or any number of sort of emergency situations or safety situations. Another one that we talked about sometimes is a lecture hall where some kids are cheating on an exam. Right? So there’s, there’s a number of societal applications for, for this technology. I want to actually take one side tangent here, which is something I get asked about a lot. We’re not building a technology that is trying to surveil people. And so what we’ve done with the software specifically is built in privacy protections from stripping faces out on the devices to there’s no Wi Fi tracking, there’s there’s no sort of large scale recognition, identification news. But for these applications I’m talking about where there’s sort of unfairness or people’s maybe even lives are on the line, a tool that could assist us and understanding the spaces and people around us would be extremely impactful. So that is where the, the societal impact of this is going. And I think, you know, given that we continue to be successful, we’ll eventually build products for those, for those situations, too.

Jay Clouse 19:24
What was the progression of your own thinking of the commercial application of this? Where did you think it would start? Where did it actually start? Where’s it going? Where did you think it was gonna go?

Everett Berry 19:33
Yeah, so we have pivoted the product twice. And actually, a lot of this has been just a function of retail in general. Alongside my interest in, in computer vision, I’ve developed a very strong interest in retail, and it’s a space that, more than almost any market, has been shifting and changing rapidly. And so when we started, we are working on sort of an old style of retail application where there’s analytics and you try to understand how you can rearrange the store and do these types of things. What we eventually realized was that trying to optimize your space to increase transactions and do these types of things is just a very challenging product to bring to market. And oftentimes the things that you need to do to increase your brand loyalty or increase your purchasing doesn’t really align with what you might get out of the technology, I guess I’d say. And so we’ve shifted a lot into focusing on experiences, delivering great experiences to people, making sure that customers are highly engaged in the space, even if they’re not purchasing. And so there has been a great evolution on just kind of an engineering focus like metrics and, and science vain to more of a product focus around helping these businesses actually solve what is the real problem for them, which is, which is delivering a differentiated experience.

Eric Hornung 20:59
Can you give me some specifics, maybe like a case study or example, that puts that more into context?

Everett Berry 21:04
Yeah, sure. So we’ve worked with a number of retailers over the years. I’ll talk about one in particular, we did some work with a small cosmetics chain. And what we found there was that in cosmetics and natural wellness, engaging the customer is extremely important. Everyone that walks in, if they’re looking for natural beauty products or these types of things, typically, they’re very curious buyers. They want to know what the ingredients are, they want to know where it was sourced, what the founder-product story was, these types of things. And so you can work on moving your visitors along sort of a funnel, where you engage them, maybe you let them browse around, you offer them a demo, you offer them some samples. So we helped a cosmetics chain really optimize the experience that they were delivering for customers, which they wanted to deliver anyway, but then the data showed you know, it didn’t always happen. And so, it’s kind of a very concrete thing. If you look at this space in general, it’s been just been a tremendous year for these types of things. There have been launches like the Capital One cafe, Disney at Target, Story at Macy’s. And all of these experiences are focused on kind of delighting the customer, surprising the customer, making their experience just really a memorable thing. And the assumption is, and I think it’s borne out in the data, that when you do this to customers, when you actually align their interests with yours, this leads ultimately to more loyalty, to higher spending, whether it’s online or somewhere else, and kind of everyone’s happy. And so that’s the type of visitors centric analytics that we’re working on right now.

Jay Clouse 22:45
To go back to this cosmetics example, can you give me like, sounds like the problem was they wanted to engage the customer at the point where the customer may have some interest. Can you talk about what installing Perceive looked like, what it did for them practically, and what the result of that were?

Everett Berry 23:01
Absolutely. So we’ve done kind of a, kind of an interesting thing with Perceive. And that is the sensors themselves, which are commodity, essentially. They click into lighting fixtures. And so there’s actually no drill required or ethernet, or some of the annoying painful parts of installing normal security system. So if you’re a business that has some sort of physical experience that you’re trying to give folks, you more or less just pop them in and then use the software. What the software does is it lets you run these little studies. So there’s obviously a massive world of analytics you could find out is there’s tremendous amount of, you know, interesting things in a space, and everyone is curious. But the software sort of helps you pick a couple key points and design your experience that you want for customers in the software. And then it basically measures whether you’re adhering to that or not. And so you might say, well, we want to approach every customer within 30 seconds, or maybe we want to let them know that for three minutes first or for a reasonable period of time. So you can settle these things up in the software, and then and the pretty amazing part of the technology is that it takes care of all the rest for you. So you can think of, like, watching a video of the store with a stopwatch and a clipboard, writing down what happens. Perceive does that automatically. And gives you all these amazing workflows to help you really make sure that customers are getting an awesome experience.

Jay Clouse 24:28
I’m going to dial this back or dial it in even further. You mentioned this standing in the store and having a clipboard and having a timer. Before we can fully understand how Perceive is changing the current state of the art, can you explain what the current state of the art is that people are doing in these spaces to understand?

Everett Berry 24:46
Yeah, sure. So so you know, good example of this is a museum actually. Most galleries will do a visitor engagement study, or kind of a, kind of a timing-interaction study where they actually follow you know, from a distance, they’ll follow people around and sort of write down how long they spend in certain areas, what engages them, what doesn’t. And they’ll do this for maybe like 50, 50 visitors over the course of a several month gallery. Museum is a good example, because you can imagine there’s there’s sort of different areas that people engage with and etc, etc.. So the same process happens within most retail businesses and other businesses, whether it’s evaluations or they hire an outside firm or something like that. And all of that today is done with basically a clipboard and, and stopwatch and it’s done in a very sporadic way. You know, if there’s no one in the store and that’s your day to be observing, right? You’re just you’re just there. So there’s, there’s a number of sort of inefficiencies in this process and sort of a very small sample of data that, that people are relying on. And the software more or less replaces that for you. It lets you basically run and optimize your store like you would a digital experience. And it doesn’t have to be a retail store. I guess I’d say that it’s, it’s really for any type of showroom where there’s some kind of concrete, concrete thing happening. And so yeah, and then, you know, typically, maybe you, maybe replace the clipboard with iPads, that’s slightly better. And you kind of collect the data and think about what does this mean? And let’s say you want to change one of the things you were doing well. You can never go back and say, okay, well, I want to re observe from a week ago, right? It’s, it’s already been done, whereas with Perceive, you can rerun the study, essentially, you can change the parameters. So it really, it really sort of digitizes the physical environment that you have and, kind of going back to the original mission of the company, it gives you all these, these tools to understand the space and how people are engaging with it.

Eric Hornung 26:47
How does this scale at like for one location? Like, this this can be used at, like, a small boutique, cosmetic shop, but can it be used at, like, a Walmart Supercenter?

Everett Berry 26:58
There’s no technical reason why can’t be used at something like a Walmart. But the experience that a larger store or department stores delivering their customers is different. So with a big box store, probably the number one chain that is, that is the focus and most, most customers, there is price. And everyone in that location is going to buy something. So it’s actually a very different type of analytics to work on. So we largely specialize in things which, where there’s a very tight experience that is supposed to be delivered for customers, very engaging, engaging, and sort of a loyalty building thing that is that is happening.

Jay Clouse 27:37
When we talk about analytics, I know there are some analytics tools — and maybe this has changed over the past four years since I’ve stopped looking at it so closely — but there are some analytics tools that you track these things called events, right, where you specify when this happens, log this as one, this happened. I’ve run into some tools where, if I want to change the event I’m measuring, I can only start recording affirmations on that event after I specify that event has happened. Does perceive record everything and allow me to run queries on everything that has ever been recorded? Or do I have to define my events to start calculating if that is actually happening, if this experience is actually happening as I want it to?

Everett Berry 28:18
Yeah, so the system builds kind of a map of the store or of the environment and everything that happened inside it. And that map exists for all the time that, that the system’s in place. And so if you want to build a new study, or build a new experiment, as we call them, you can do that for the whole breadth of data that, that’s available. And it’s actually one of the most powerful features that, that customers like, is that they’re not, if I want to go compare from a year ago, I can do that. And this is especially salient in a physical environment where things are perhaps changing at a slower pace, and like in retail, probably the most important metric for our location is same store year over year sales. And so we’re seeing some shift away from that. But still, when you want to cover like a long time span of time, that’s, that’s one of the areas where we really shine.

Jay Clouse 29:10
Okay, so before I keep going down deeper, in case it wasn’t clear, can you just share with the audience how you would explain Perceive and the breadth of what it provides now?

Everett Berry 29:20
Sure. And so, you know, speaking of the entrepreneurial journey, this is, this is always evolving, but Perceive’s an experience-analysis toolkit, and it automates most of the functions that you would do with a clipboard and pencil out in a physical experience. And so you can think about somebody like Capital One cafe, or Disney at Target, delivering a great experience to customers where there’s a strong idea of what should be happening in the space. Perceive helps businesses measure and improve that.

Jay Clouse 29:50
I was just in San Francisco a couple weeks ago and was at the Capital One cafe there. For listeners who have not visited, can you explain what that experience is like and why that has come up a couple times now?

Everett Berry 30:00
Sure, well, it’s just a cafe, but it’s, it’s run by Capital One. And so if you want to go there and have a coffee, totally cool, have a meeting. But maybe you want to go there and solve some banking issue and also chill out for a sec. So it’s this whole idea, which I think is really a positive change that we are generally happier as people and more engaged as customers if we are engaging in some experience, and we are having sort of an ulterior purpose for being in the space. And so that’s what Capital One’s delivering. And then obviously, you know, you’d hope that they’re opening checking accounts and that sort of thing.

Eric Hornung 30:40
If I’m a customer of Perceive, what am I, what am I getting? What is, I get reporting I get…give me a little bit more, what am I buying?

Everett Berry 30:49
Generally, the way people interact with the system is they set up experiments, they receive reports and notifications. And we’ve built in workflows to sort of help organizations filter the data to the appropriate people. It’s sort of this, like, you imagine someone again with a clipboard and a pencil, and then they call their boss and say, hey, so here’s what we found, you know, what, what should we do about this? The system sort of delivers that.

Jay Clouse 31:15
Earlier, you used the example of, if I want to approach every customer within three seconds, or let them browse for three minutes first, does the system push someone towards intervention in real time when certain things are happening? Or is it hey, this is what we observed happened, you may want to put a focus on your staff changing this behavior because it’s not meeting expectation.

Everett Berry 31:37
Yeah. So today it is, it is offline. And so I think we will get to kind of a real time situation, and that’s going to enable a whole host of amazing things. But today, it’s sort of available next day.

Eric Hornung 31:50
How does Perceive make money?

Everett Berry 31:52
So we charge a monthly subscription for the service. It’s again, it’s very much meant to be kind of, feel like a software product, even though there’s a lot of deep technology underneath. And then occasionally, we will run kind of custom queries for folks and help them answer custom questions.

Eric Hornung 32:08
How do you price something like this?

Everett Berry 32:12
We think about it like, it’s about maybe 5-10x cheaper than commissioning a study to do this from an outside firm, from an outside marketing firm. And so, if you’re a space, kind of show room or something like that, you’re going to pay somewhere north of probably $100,000, $200,000-$300,000, depending on the scope of study, to figure out all this information. So with Perceive, you’re going to, you’re going to pay a fraction of that and have constant access to the information, the ability to change it, rerun it, all the benefits of software and automation. So that’s how we, that’s how we we think about pricing the software. Generally, it’s kind of a marketing, marketing tool that folks are buying.

Jay Clouse 32:57
When I commissioned a study, am I also paying for them to give me, like, a report to say this is how we break down what we found, or are they just kind of provide the raw data and and the company does the analysis themselves?

Everett Berry 33:11
So I’ve seen both depending — and that is, that is a price differential in these studies, I think, if there’s an analysis that accompanies it. Generally, what we have found is that we’re experts in the data and in capturing and understandings in these spaces, and our clients are generally the experts in working with that. But that said, we do sometimes help them answer custom queries or to fund little things. And that also actually has fed its way into features for the product as well.

Eric Hornung 33:43
Are your customers generally permanent retail shops or shops that exist year round or they pop up shops?

Everett Berry 33:52
Yeah, so we have, we have a few that are, you know, large national chains and then one or two that are kind of more pop ups. It can be used both ways. The pop ups are good and bad because obviously, as a software company, that’s, you want to have a revenue stream that’s kind of consistent. That said, one of the great strengths of the product is that it is a great tool for experimentation. And so, we are still finding our way in this, in this area. But I think, as we see retail shifting into more of a pop up experimental phase, especially in the physical world, we’re going to see a lot more of, we’re going to see a lot more usage around sort of the potential, temporary, easy to set up, tear down nature of the product.

Jay Clouse 34:36
So we have retail chains, we have pop ups, you mentioned museums. What are the other segments of potential customers for Perceive?

Everett Berry 34:45
So this is getting into my kind of read on what’s happening. I think what we saw in retail in the last 20 years was purchasing became a sort of utilitarian thing that was much easier to do online. Much more convenient for customers etc. And so the types of things that people were doing in physical space, and, this is more or less echoing some of the thought leaders and the retail space, is they were using their footprints as a customer acquisition channel or even a media channel. You can imagine if you have 100 million visitors a year, and you have them in the store for 20 minutes, the advertising value of that time is almost infinite. You cannot buy someone’s attention at that scale from an advertising firm. So the physical footprint of retail has changed. I actually think the same thing is happening in restaurants right now. And so there’s a number of interesting companies, some of them, a lot of them are in LA, I think Cloud Kitchens is one, where you’re seeing not only the delivery of the food from restaurants, but the actual, whole vertical making of the food, shifting into a total delivery model where we just receive it out the door, and it’s super convenient, it’s more centralized, you know, a number of good benefits. And then finally you have events which are, are changing from maybe like a pure marketing tool into like a into kind of like a sales tool where, if you have a physical footprint and you host community events, like they do with the Apple Stores, this is an amazing way to get people involved in the product. And so, I actually think that sort of events, restaurants, and retail are all converging into a general space of experiences. And what businesses are going to need to be able to do is measure ROI on that, make sure they’re amazing for customers, and make sure that they know that that channel is working for them as it’s right for their customers. And so, I think they’re, if you look at video analytics companies today, most of the websites — I thnk Phillips is guilty of this too, actually, they have, like, three or four separate industries that they provide solutions for, quote on quote, and I think what you’re going to see with experiences is all of these converge into some of the same things. And then brands are going to put their own creative spin on, on these spaces. And so that’s where I see, that’s where I see proceeds market going. Today, we’re just focused on showrooms, which is you can imagine kind of a retail store, or a gallery of some sort, car dealership. And these are all places where you show off products, people don’t necessarily buy them there, they don’t necessarily have to, but when they’re in there, you definitely want them leaving with the most positive impression of your brand that you can give them. So that, that’s kind of the the now and the later of our market.

Eric Hornung 37:32
You mentioned measuring ROI as a brand, as a business, as someone who’s putting on these experiences. How instrumental are you and actually putting together that ROI data or, like, what data are you giving them to help them with that calculation? And is it all of it or just some of it?

Everett Berry 37:48
You know, the first thing we’ll do is we’ll help them and put basically a cost per square footage into our system. This is actually still an experimental part of the product. And so we are we are trying to Figure out beyond the obvious sort of costs per square footage, which is building operation and, you know, remodelling every couple of years. You know, how do you think about the value of someone getting a great experience in your space? Many brands may not have a great answer for that. Sometimes the answer is just to pick a number, and go from there. Because then you can drive it up or down. And so we are still experimenting with businesses on kind of the right way to deliver this. Generally, we’re experts in the data, staying up to system, helping people really understand what kinds of things are causing what kinds of behavior in the space. And then, you know, they’re experts in their business and their brand. And so we want to sort of meet them in the middle.

Eric Hornung 38:40
How do you quantify a great experience?

Everett Berry 38:43
So generally, it’s going to come down to engagement. And again, this is, there’s a whole sort of psychology line that you could take on this. But we what we generally say is when people are, you know, standing at attention, engaged with an associate, with marketing materials, with some display, they’re engaging the experience. And then how long they spend there is actually depending on what kind of experience you’re trying to deliver. So if it’s a buy online pick up in store situation and they’re there for 10 minutes, that’s actually a bad experience, right, they should be getting in, in and out very fast. If it’s a showroom, and they spend a lot of time physically engaged with the current products, that’s a good indication that they are having a positive experience. One other thing on that is we have a particular technology, which is we are, I’ve actually developed a way to sort of measure the attention that customers are giving the space or or the person inside it. And so, you know, we want to try to differentiate between people that are just they’re like not facing anything or on their phones or something that people that are actively engaged in the experience. And that’s, that’s going to be pretty important for, I think, any analytics in this category.

Jay Clouse 39:49
What’s the biggest win you’ve heard from a customer who’s using Perceive?

Everett Berry 39:53
Yeah, so we, we helped one of our customers save like $50,000 on a new, interactive elements they were adding to their to their showroom that was not returning the engagement that they were expecting. In fact, in fact, actually what we see with interactive and elements is general is that it does require a lot of thought to design good ones and, and sometimes interactive elements become basically non interactive. And so pretty much the immediate thing that people do is they save a lot of money in their marketing budgets, and they allocate it, they allocated more intelligently to things that are really positively impacting their customer experience. And then yeah, there’s, there’s a number of longer term effects, obviously, ROI is always, it’s always something that people are after, but that’s kind of the biggest, immediate, right away one that we’ve seen.

Eric Hornung 40:41
How long does it take to onboard a new customer client?

Everett Berry 40:46
Generally within a month. So the actual install piece is very straightforward. The thing that, that takes a little, that can take a little bit longer is understanding from them is the product right for them. So depending on your level of sophistication and, you know, really the thing that you’re after, we have fallen in the trap in the past, which I think is common with, you know, entrepreneurs of working with clients where it’s more of a nice to have instead of the need to have. So we try to spend a lot of time these days really understanding that the processes inside the organization that are going to lead to them utilizing the tool in a, you know, positive way for them.

Jay Clouse 41:25
How are you finding clients right now? Or how are they finding you?

Everett Berry 41:29
So it’s all been word of mouth right now. We are starting to experiment a little bit, and I think post, you know, post a seed round this will be a bigger piece of it with some more rigid kind of channels and methods. But right now, it’s been sort of network effects and word of mouth.

Jay Clouse 41:45
So you, you got the SPIR 2 grant you mentioned earlier in the interview, and I think you also got the SPIR 2, the follow on, is that correct?

Everett Berry 41:54

Jay Clouse 41:55
What’s the next step for you guys? Is there an SVIR 3, or are you now fully on your own to fund this thing? Like, what does that look like?

Everett Berry 42:04
Yeah, so, so we’ve been kicked out of the nest, so to speak, the thing that we’re doing currently is working on a small angel round, not particularly for the capital, which is obviously, capital is always a concern for a young company, but we are in decent shape there, but we are working, we really want to get some some knowledgeable individuals in the company and people that really have seen this space from both sides, people that have built companies before, or individuals that can contribute in a way in helping us kind of structure future investments. And so we’re running a small angel round right now, and then I expect next year we will do a seed round.

Eric Hornung 42:43
How big is your team currently?

Everett Berry 42:45
It’s myself and three engineers.

Eric Hornung 42:47
And when you say doing the small angel round,that’s bringing people on an advisory aspect, or bringing on more people onto the team?

Everett Berry 42:54
Generally an advisory aspect. We have definitely had various people in their expertise, and we paid them for it. But generally it’s going to be an advisory aspect to start. If folks can really contribute and it’s at, and they can put in, you know, 20 hours a week and, and really produce for us, then yeah, we have done, we’ve also done consulting work.

Jay Clouse 43:13
So the team right now is for engineers. What’s your next big hire? What would really add to that team at this point?

Everett Berry 43:20
Yeah, it’s an interesting question. I would like to hire a sales-focused product person. So someone that can take a lot of the customers that I’m taking right now and work with them and work with our team to sort of build and tweak features that, that just continue to drive home the value of the product. And so that’s the role I occupy currently. There’s a number of great folks that I know that that could do that. But I think, I think we’d want to we’d just want to have a little bit more of a process in place before we, before we start to think about scaling that.

Eric Hornung 43:55
And then one kind of random question here for me. What do you do with all the data?

Everett Berry 44:00
So all the video gets deleted in general. Some customers want to leave it on. And sometimes they post signs. And so we leave that, we leave that up to them. But in general, the video gets deleted by default. The data sticks around as per length of the, of the time that we’ll work with someone. And of course that enables them to go back and run experiments and all that stuff. That’s really the extent of it. It’s kind of, it’s like you have a CRM, and you’ve input all your sales leads in the last four years into it, and they just sit there, right, so.

Eric Hornung 44:30
Who owns the data, you are the client?

Everett Berry 44:33
So the client owns the video data, for sure. Currently, you know, as part of the software model, we sort of lease the rights to use the actual data that we kind of did work to produce, the analytical data.

Jay Clouse 44:45
So Everett, you’re sitting in the Indianapolis IoT lab, I think, if I recall that correctly. We haven’t talked to a lot of companies from Indianapolis. So why is Indianapolis the right place for Perceive to continue to build and grow?

Everett Berry 44:59
So there’s a number of reasons to be here, first of all, if you’re a software company, particularly if you’re building a marketing software of any type. There is a huge amount of expertise in this area in building that type of software. For us, we have access to amazing research universities close by, so Purdue University, University of Illinois, and very strong business universities, so Notre Dame and IU, so it’s actually really kind of a central place to build and grow an engineering operations team. And then, you know, the value is extremely high. I mean, we had a more or less fully staffed AI company for three years on under a million dollars in funding. So that’s, that would be gone within nine months in the Bay Area. So there’s a number of great reasons to have a company in Indianapolis. And I think we’ve been, again, our timing has been fortunate because the startup ecosystem has sort of exploded here over the length of time that we’ve been a company.

Jay Clouse 45:58
Awesome. Well, if people want to learn more about you or Perceive after the show, where should they go?

Everett Berry 46:03
Yeah, so you can always email me, it’s Everett@perceiveinc.com so the domain is perceive-I-N-C.com, which is two E-Is, so heads up to that. And yeah, I’m very fast on email, generally respond, respond quickly. And then you know if you’d like to find out about the company itself, we’re on Twitter, and we also have a website, PerceiveInc.com. And generally, you know, media and that kind of thing gets posted there by our Social Media Manager. So those are all great resources about the company.

Eric Hornung 46:36
How much are those wasabi peas you buy at Kroger?

Jay Clouse 46:39
I think they are about $5, maybe $3.99.

Eric Hornung 46:42
That’s pretty expensive for, for a little snack.

Jay Clouse 46:45
Just a little snack, but you know, the value is there, and I think it’s worth it.

Eric Hornung 46:49
How do you afford that on a podcaster’ss budget?

Jay Clouse 46:51
It’s tough. It’s tough. I gotta dig deep, and I gotta lean on my other business sometimes.

Eric Hornung 46:55
Well, you know what, I think the listeners could help us out here because there’s one thing that they could do that directly correlates with our ability to raise some advertising revenue on this platform.

Jay Clouse 47:05
I think I know where you’re going with this.

Eric Hornung 47:07
Oh, yeah, I’m going to upside.fm/survey. It is our 2019 Listener Survey, and it is a key part of our growth strategy here at Upside so we can keep on telling stories about founders, community builders, and venture capitalists outside of Silicon Valley. And we can get Jay some more wasabi peas.

Jay Clouse 47:26
That’s right. So dear listener, if you would do us a solid, if you would do us a kindness, please head over to upside.fm/survey, answer our 2019 Listener Survey, it should only take a couple of minutes. Myself and my wasabi peas thank you.

Jay Clouse 47:49
All right, Eric. We just spoke with Everett Berry, the founder and CEO of Perceive. At the beginning of the show, you talked about the buzz terms AI and machine learning triggering your BS meter. How do you feel now?

Eric Hornung 48:02
I think the six years of research in an academic setting and Everett’s ability to kind of paint the history of the space, going back to the watershed moment of 2012, gave me a lot of comfort around those buzzwords.

Jay Clouse 48:16
Yeah, a lot of, I think some of the folks who give AI and ML kind of a bad name in terms of just using it as terms, they like to talk around questions and talk a lot but say nothing. And that wasn’t at all the sense I got from this interview. Everett was giving us very specific answers to the questions that we are asking and talking to me like I’m dumber when I requested it, so we get even more specific answers.

Eric Hornung 48:45
I love when people talk to you like you’re dumb. It’s probably one of my favorite things.

Jay Clouse 48:49
Hey, I’m here as an advocate for the listener, and I want to make sure there is no listener left behind.

Eric Hornung 48:55
Wait, are you calling our listeners dumb?

Jay Clouse 48:57
No, no, no, no, no. But, what I am saying is, I don’t know as much about our listeners as I would like, which is why, dear listener, you should go to upside.fm/survey and fill out that listener survey that we mentioned earlier in the show, so we can find out more about you and find out if I need to make myself smarter or if I need to continue to ask questions of our guests to simplify things.

Eric Hornung 49:20
Wow, Jay, what a plug. And we didn’t even plan that.

Jay Clouse 49:24
What a plug. So Eric, here we are in our deal memo, we can talk about Everett as a founder, we can talk about Perceive as a company, the opportunity ahead of it, where do you want to start?

Eric Hornung 49:34
You know, before I get to Everett, I think the company is a little earlier in the commercialization and venture backed fundraising phase than we typically talk to here and Upside, and maybe that’s just the fact that it’s one of these hard sciences models. But when we talked to Everett, I mean, he’s a smart founder, he has a very measured approach, and he definitely knows the space. So when I think about potential shadows for Everett, I don’t have any of him per se. I have maybe more shadows around the idea of a measured approach, smart, thoughtful founder, blending into the grow-at-all-costs, Silicon Valley, venture-backed model.

Jay Clouse 50:21
Well, Perceive sounds like one of these interesting origin stories that came out of university and research there, and is now being commercialized. Has a couple of SPIR grants — you can’t slur SPIR grants, it just turns into SPR. And what we hear from some companies that come out of universities is this difficult process of finding the commercial application that is truly valuable to a commercial partner. And what impressed me about Everett was that he quickly saw the need to do that, and also quickly identified a few different customer types, customer segments that can genuinely find commercial use out of the this product and is now developing it for them and not simply out of a research application.

Eric Hornung 51:05
I love that the big picture focus is on retail. But then you have this kind of little niche off to the side of museums. And it’s not going to ever be a billion dollar business just selling to museums, but it’s almost the perfect customer for them, and it just fits really, really well with what they do.

Jay Clouse 51:25
You don’t hear, you don’t hear museums as a customer very often. I was just also in a museum in Chicago, circling back to the front of the show,

Eric Hornung 51:32
Subtle brag.

Jay Clouse 51:33
Subtle brag, we went to the Art Institute of Chicago, beautiful place. I’m always just so curious about how all of that actually works, you know? Like how close are museums to going under at all times? And maybe the answer is not at all. Maybe some museums are, like, really great sustainable businesses, but it always seems like it’s, it’s this thing that maybe not enough people go to and sometimes some museums, not like the Art Institute of Chicago, some museums really look like they could use some, some cash infusion just to clean things up and keep the lights on. And some of them look pristine and, and amazing. But at the end of the day, I’ve always assumed they are completely grant and donor funded. And I don’t know what that means for companies that have a product that serves that niche, whether they have so much grant and donation funding that they can pay for things like this. But it does seem like this serves a real need for museums.

Eric Hornung 52:29
Well, the good thing is that the three primary markets that Perceive is attacking are retail, events, and restaurants, and those all kind of, according to Everett, are merging into this experience space. So I don’t know that it’s important for the analysis of the business, when we’re looking at the opportunity size and what this business could become, to look deeply into the museum space.

Jay Clouse 52:59
When we get into the opportunity, he mentioned that Perceive is five to 10 times cheaper than commissioning a study from an outside marketing firm. And as we went through the interview is clear that Perceive is a technical solution to what is being done by humans in these, in the form of these studies a lot. And being five to 10 times cheaper and automating that, there’s a clear value prop there that I really like, especially if these studies are $100,000 to $300,000 apiece. You might argue that, well, it doesn’t need to be five to 10 times cheaper if it’s, if that’s what the total cost is. What I’m still a little hazy on is how many of those studies are happening each year, and what that means for a total market size for what Perceive is trying to do.

Eric Hornung 53:10
So yeah, we did a bad job of asking questions about the opportunity size. But something else I was just kind of thinking about in terms of Perceive is how off the rack is this software? Is it just, here you go, or is it very customizable? And my thought is that there’s probably a certain level of customization because he mentioned some customers want to know how long until someone is approached by a customer service rep, and some customers want exactly 3.5 minutes, and he mentioned these clipboards, and it seems like there’s a lot of learning and onboarding time that goes into each client as each client has different needs.

Jay Clouse 54:31
My expectation would be that these studies that are commissioned aren’t being commissioned multiple times per year, and maybe not even every year. So something else we would need more information on is how often is one of these customers purchasing $100,000 to $300,000 study at this point? How often do they wish they could be commissioning that? And now, having Perceive installed and doing the job all the time, I think there’s more value there than we even heard in the interview, I would assume so. But he talked about the direct, immediate ROI for a lot of these companies being that they save a lot of money on interactive elements or different elements of the store that are just not getting the engagement they thought they would. And so it seems like, you know, if, if I’m a store and I’m saving $50,000 on part of the store that I put in I thought was going to be valuable, and it’s not, you can really see the value of Perceive, but it’s hard to, I had a hard time hearing the message, or getting the message across on the website of, here’s why you need this in your space.

Eric Hornung 55:37
Right. I want to hear more about the ROI from Perceive. I want to know specifically what customers are finding valuable and how they’re measuring ROI because, as we think about the clipboards, he mentioned that the people who are doing those analyses are giving recommendations and they are, that, that’s the best value add of having an expert come in. So I think, you know, show me that Perceive is five to 10 times cheaper sure, but show me that it’s also five to a hundred times better. And I think that as they grow and they have that data and they look forward, that’s probably where proceed is heading.

Jay Clouse 56:20
And this gets into one of my shadows on Perceive as a company right now. You ready for this, Eric? Waa…

Eric Hornung 56:26
I thought we kicked the “waa” sound.

Jay Clouse 56:28
Waa. That’s the shadow noise. The team right now is small, very effective four engineers, Everett and three other engineers. Their website, beautifully designed. And you know, as we talk about wanting to hear more of these case studies and see more of the data behind ‘this is what our customers have done,’ I think that is something that somebody really leading a sales or marketing, outward marketing effort, even if it is, you know, b2b, I think that’s something that can be really dialed in with somebody focused on it full time. And as this company looks to grow and expand and raise a seed round, you mentioned that they’re looking for a sales-focused product person. And I hope that that person also, you know, is really focused on messaging and marketing that solution to the customers because I’m not saying I don’t believe that value is there, I’m saying that I think the messaging of how that value can be experienced by the customers can be honed in a little bit more when you don’t have the opportunity to talk to the founder for 45 minutes like we did.

Eric Hornung 57:34
I would agree. Definitely some shadows. But you know, that’s part of the world of when you are pre-seed. There are some commercialization shadows, there’s some market risk. I think that this is a product that, that, when it finds its right customer and it’s right clientele, could definitely boom. I think that the ease of buying on the internet has made the in person experience significantly more important, and companies that grasp that and understand that are going to thrive. And they’re going to want to do it in a data driven way. I think Perceive gives them that ability to use data to drive in-store decisions, that drive engagement and conversion rates to sales. So I see the problem, I understand the problem, I think it’s real, and I think the market, the retail market in general is just massive. So I think that it is a large problem, the real problem, and delighting the customer is something that every retail company wants to do.

Jay Clouse 58:37
So Jay, we kind of talked about this. So I’ll make mine quick. Six to 18 months from now, I want to see more business cases, I want to hear more specifics, I want to learn more about what customers are saying and what customers are finding extremely valuable on the insights developed by Perceive. What are you looking for?

Jay Clouse 58:37
Opposite of a shadow, something I really liked about this interview was there a couple moments when Everett pointed out why this is specifically a good time that has enabled this company to exist. One of them being, as he mentioned earlier, this 2012 watershed moment of transfer learning, the second one being where he sees things trending in terms of physical space and whatpPeople are going to want to do with physical space. So as we’ve talked about recently on the show, Eric, this founder-market, almost, timing fit. That box was checked for me as we went through this, hearing, like, okay, this does sound like a unique time where you started as a freshman studying this, that was the same time that this watershed moment was happening. He’s been working on it for six years, which is the length of time that this field has been relevant. And he has a beat on where things are going.

Jay Clouse 59:45
Very much the same. I want to understand better, what the plan for customer acquisition is, and how big that market market opportunity is if they saturate it really well. Right now he said that acquisition is word of mouth, and as this company grows and scales, they’ll need to create more of a system and a process for onboarding and getting in front of new customers.

Eric Hornung 1:00:08
And I know, this is how we usually end, we usually end with the 6-18 months question. But I got one little piece of insight that I want to drop in here as wellthat wasn’t really a key focus of the interview. But I think that the data collected by Perceive, if they reach scale or reach certain brands, is incredibly valuable. I think about its value to someone like a circle up, who’s a data driven retail investor, who we’ve had on the podcast. I think about the value to hedge funds. There’s the, I forget the name of the satellite company, but the one that scans Walmart parking lots to predict the next quarter’s returns using hedge fund models. I think they actually got bought by a hedge fund. So this kind of data that’s an alternative data source, as our friend Rachel Carpenter from Intrinio would tell us, could be a data source that is extremely valuable for Perceive, should they store it that way.

Jay Clouse 1:01:09
Love it. Alright guys, if we missed anything, let us know. You can tweet at us @upsidefm or email us hello@upside.fm. And we’ll talk to you next week.

Interview begins: 6:15
Debrief begins: 47:49

Everett Berry is the CEO and founder of Perceive, an experience-analysis computer vision software designed to give companies an automated method for analyzing business in a physical space.

Everett began forming his idea for Perceive six years ago during his freshman year in college when he would peruse the campus’s video feeds. Having since received several grants for his company, Everett currently runs Perceive out of Indianapolis and hopes to expand his team in the near future.

Everett discusses his insights on the recent changes in the events, retail, and restaurant businesses and how Perceive is providing companies an efficient and dynamic analysis of their customer experience through video analytics.

We discuss:

  • Ad: Improved methods to sourcing talent and finding new possible colleagues (4:58)
  • Challenges in computer vision, AI, and what Perceive does (8:05)
  • Perceive’s story of becoming a company (14:55)
  • NSF SPIR grant (16:25)
  • Commercial application of Perceive and monitoring customers (19:25)
  • Analytics and company personalization (27:37)
  • Business model (31:52)
  • Events, restaurants, retail, and customer experience (34:36)
  • Perceive’s clientele (39:49)
  • Future growth (41:45)

Perceive was founded in 2015 and based in Indianapolis, Indiana.

Learn more about Perceive: https://www.perceiveinc.com/
Follow upside on Twitter: https://twitter.com/upsidefm
Take the listener survey: https://upside.fm/survey
Check out the Midwest Startup Rankings: https://midweststartups.com/cities/

This episode is sponsored by Integrity Power Search, the #1 full stack high growth startup recruiting firm between the coasts. They partner with venture capitalists, private equity groups and CEOs to build amazing teams for the world’s most disrupting companies.

Learn more about or get in touch with Integrity Power Search: https://upside.fm/integrity