80. Matterport’s Sweet Spot is Spatial Data for Enterprise at Scale
The sweet spot for Matterport is spatial data for enterprise at scale. Then, if you add Matterport's recent acquisition of Enview, which is a company that teases out those analytics of three-dimensional models at scale, once Enview puts the tools and solutions in place for Matterport, that is the single greatest use case for Matterport.
The sweet spot is spatial data at scale for enterprise.
Let me see if I can give you an example. If you're a facilities manager and you have 150 different commercial office spaces across the United States, for that matter, across the world, and you're tasked with, "hey, what if we put in this light bulb versus this light bulb in all those three by six boxes that have the fluorescent lights, how much money would that cost?
How much money would that save? What would be the energy efficiency?" Whatever questions that get queried.
Well, the old-school way of doing that is, you'd send an email to the 150 different counterparts at each one of those buildings and say, "hey, Jim John, those fixtures in the ceiling that are three by six, that each have four fluorescent light bulbs, how many do we have in that 100,000 square foot location?" They say, "well, I don't know. Let me go walk all these floors and count these fixtures, and I'll get back to you." That is a Herculean manual task done old-school.
Now imagine, you have a Matterport spatial data, digital twin, of all those 150 buildings, and you have this powered by Enview solution, and you're able to say, "okay, here's the object I'm looking for with AI. Go find all those three by six light boxes in 150 buildings, tell me how many boxes do I have by building and total?" That should be a 10 minute exercise that would otherwise take weeks and tons of people time, and totally inefficient.
Now, let's go count fire extinguishers and let's go count windows because we have this inefficient glass. If we go put this other type of glass in, we'll be able to save energy by 50 percent. But, we need to know how many windows that we're talking about in 150 buildings.
Go count the windows. That's an example of Matterport in the best, highest use case, where it can add the most value to enterprise, and charge the most money. That's all about software, that's all about recurring revenue. Has nothing to do with what device that I use to capture the data?
We didn't talk about it. But if you were to ask me, I would say, "in the long run, Matterport should be out of the camera business." They shouldn't be making any devices. They should be out of Capture Services (On Demand). They shouldn't be running a labor-intensive business.
They should just be the essence of what is the best, highest use case for Matterport, and that's spatial data meets enterprise at scale. Everything I look at, I tend to evaluate in terms of quadrants. I think about it in terms of my career over time. Did I like working for that company?
Did I like who I worked for? That was in Quadrant four. I was happy, and the company was happy. Quadrant 1 in the lower case was, I was unhappy and the company was unhappy. That's metaphorically what we're talking about. Let's get in the right box.
If you take all the different use cases for Matterport, if you were telling me about residential real estate, obviously, Matterport doesn't really add a lot of value in terms of spatial data and it takes a long time to capture, and all these things.
I'll put it in that lower box where it doesn't add a huge amount of value versus competitors. Matterport probably can't charge as much for it. By the way, they can't sell a lot of add-ons over time for it. Now, this top quadrant box, which I would describe as what is the highest use case for Matterport?
Things that involve spatial data that matter for enterprise. That's a sweet box up in this top right corner. That provides a ton of value to enterprise, and that is something that Matterport can charge a lot of money over time as recurring revenue.
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