Business Breakdowns
· Brett Larson
[00:00:00] S1: There's deep learning and edge learning, as I mentioned, deep learning first. So traditional rules based vision is great for a lot of things, but not for things very subtle or nuanced tasks with a great deal of variation. Those sorts of tasks, you still usually have a human performing them because frankly, it's just hard to quantify them to then program them. Maybe an example of that would be inspecting a phone case for very subtle defects. There's obviously a wide variety of colors and there's just an endless list of potential defects. So scratches, dents, blemishes in the paint, and they're very small, very nuanced. And then there's also usually a scale of what's acceptable and what's not, where a human would be able to look at it and pretty quickly discern that. But it's very hard to program a machine to be able to do that, especially at obviously high speeds. But with deep learning, instead of programming it, you teach it with very large data sets and very large image sets. These are good phone images. These are defects. These are acceptable defects. And the machine learns what is acceptable and what is not and is able to accomplish that task, just to quantify this a little bit. So there's currently still 30 million people in the world doing visual inspection. And that's something that humans actually aren't great at. They can do it quickly, but they get fatigued and they miss things. That's a big opportunity. Another example would be something like deboning chickens, where every chicken's different, it comes down the line a different orientation, the wings are somewhere different. It'd be impossible to quantify and program a robot to be able to grab the right places. But with deep learning, that's an application that they can now do deep learning. The implication would be potentially new applications for machine vision. Edge learning is the other end of the spectrum and it's probably more financially tangible for the investor community right now. These products, they come pre-programmed for specific applications but then they're trained with just as few as five to 10 images. So it's essentially very easy to deploy relative to traditional rules-based vision. You can usually get an application up and running in a few hours. So the major implication here is that Cognex can now sell to less sophisticated customers.
· Brett Larson
Again thinking about where they've historically focused on the top of the pyramid. And they can do it with a much less technical sales force. So broadening their customer base below where they've typically served. So now they have the product and Cognex is currently making a Salesforce investment called the Emerging Customer Initiative. And it's really taking the Keyence playbook. These emerging customers, salesnoids, they call their employees cognoids, their salespeople, salesnoids, they're hiring young salespeople instead of technical applications engineers. They're arming them with these new edge learning products that are really easy to implement and, and they're going after these less sophisticated customers, more SMB types and even less sophisticated tasks within existing customers where those exist. And then it's a much more formalized selling playbook that tracks the KPIs. Just like Keyence, they're getting compensated on both their selling activity as well as their commission. Last year Cohort One of these salesnoids hit the field and they did 80,000 customer visits, added 3,000 new customers to a base of what was previously 30,000, had accretive gross margins and they exited the year at about a million dollars a week in sales from that first cohort. The second cohort entered this year in 2025 and hopefully we'll do a bit better just from lessons learned. Obviously they're now competing in Keyence's bread and butter target customer set. So they are running into them sometimes with these customers being vended. But the majority of the time these customers have never used machine vision at all. I think it's more like 60 to 70% of their sales have been people that have never had a camera in their factory. Obviously the financial implications here are they're trying to grow their customer base from 30,000 to hundreds of thousands over time, which could be obviously revenue opportunity and then at accretive gross margins and reduce the customer concentration as well over time.
· Matt Reustle
[00:00:00] S0: The customer base, I think you painted a picture just in terms of the various applications and who might use them. But what does it look like in terms of a customer, whether it's a contract, whether it's a sale, the ramping of that contract or sale and then what the stickiness is once you build something out?
· Brett Larson
[00:00:00] S1: The stickiness of a customer is quite high once you're on the factory floor and the people that are managing the floor are familiar with the software used to program the cameras and it's usually more or less standardized, especially for some customers where they for the sake of simplification they don't want a bunch of different machine vision vendors out there and the associated software. It's a CapEx sale and they have, as I mentioned, historically been focused on the top of the pyramid customers. So they've been tied to the large CapEx build outs of companies like Apple and Amazon and that obviously comes in a wave and then it's more of a question of stacking new S curves and when the next waves and CapEx is going to come. But the customers themselves are generally quite sticky. Maybe this is a good segue into the different end markets and we can start with consumer electronics. It's interesting because that end market's tied to the CapEx spending around new consumer electronics or features. There was a tailwind from the adoption of cell phones and then there was the tailwind from Apple building out the iPhone manufacturing. At one point Apple was as high as 20% of Cognex's sales which is pretty incredible. It's now probably down to more mid to high single digits range. There was another big tailwind when OLED came on the scene and that was with Samsung. So looking forward it's interesting to think about if there will be new form factors or changes to the existing ones for consumer electronics tied to things like LLMs or if there's AR or VR is going to take off ever or if humanoid robots are going to take off. Basically if any of those things were to be manufactured at high volumes that would fall right into Cognex's sweet spot. Sophisticated customers, big manufacturing capability and consumer electronics in 2024, 17% of sales and longer term they expect that market to grow. Mid teens is the target. Logistics is the largest end market. It's 23% of sales. At peak it was 30% of sales and Amazon was up to 17% of Cognex's sales. Obviously there was the well publicized down cycle in that end market. They did return to growth in 2024 they grew 20% and that's the long term target for that end market is if they can grow 20% and Amazon probably is back around that high single digits to 10% range in terms of a customer.
· Brett Larson
In Cognex fashion, they're stacking new S curves in logistics, which is really interesting. So they're taking the vision tunnels, which they've really honed with Amazon to new customers and new geographies. And those non-Amazon customers are growing very quickly. And then they're also identifying other applications outside of barcode reading, things like vision inspection to see damaged boxes coming down the line or damaged labels, make sure there are labels, even things like dimensioning to do, estimating of your shipping costs and things like that. So they get their foot in the door and then they find additional applications within the end market. And that's the story of logistics. At the moment, Automotive is the second largest market at 22% of sales. In theory, EV battery should be a good tailwind for them. Cognex has solutions. The transition just frankly necessitates a bunch of CapEx, whether it be new automotive lines, but also battery facilities that otherwise would not have been the case if it was just new models, internal combustion engine models. But frankly the growth just didn't come through last year as people had expected it to. Automotive sales were down mid teens in 2024. It's not expected to be a good year in 2025, but it shouldn't be a deep decline like 2024 at least. And long term, the target for this end market is 10% growth for Cognex, two other quick ones. So semiconductor is probably about 10 or 15% of sales now. They're selling primarily to the semiconductor capital equipment manufacturers. And the growth outlook there is positive at this point in time. And then the other 20 to 25% is general factory automation and keeping an eye on PMI there primarily. It's been historically long down cycle for industrial manufacturing and that's been felt by Cognex in that part of their customer base.
· Matt Reustle, Brett Larson
[00:00:00] S0: Is there a average useful life in terms of the equipment that they're installing? Are there replacement cycles for the equipment as well? [00:00:00] S1: Ideally when a customer puts the camera in the factory, they're hoping it's going to last for 10 to 20 years. So there's not really a regular replacement cadence. It's more about you get the customer in your installed base and then they'll be doing brownfield CapEx on existing lines and that'll create revenue opportunities for Cognex. Every now and then there'll be these greenfield opportunities with those customers or just new end markets and new customers. And that's what drives the growth of the industry over time. [00:00:00] S0: On the software side of the business is that an actual revenue driver for them. When I think about how much they will make from the sale of equipment, is it all recognized in year one or is it spread out with some type of software component? [00:00:00] S1: The joke I say is that Cognex doesn't adjust out their stock based comp which is great for a company that's essentially a software company. But you get stuck with the cyclicality of an industrial company as a trade off. So it's all an upfront sale. The software is tied to the hardware CapEx.