Convex, Commercial Services, and Data Clouds
the next generation of industry cloud architecture
It’s finally time to give credit where credit is due. Plenty of what has come before in this mini-series on industry clouds has been inspired by conversations with Charlie Warren, the CEO and co-founder over at Convex. Convex is building the industry cloud for commercial services.
And the early results are in and they’re fantastic. Commercial services is an incredibly complex segment, run by a mixture of massive companies and regional SMBs. Convex is signing them all.
To understand why Convex is signing a large swath of customers in the space and continuing to accelerate, it’s best to talk briefly about the industry itself.
The Commercial Services Landscape
As one can grok from a previous piece I did on field and commercial services, the commercial side is dominated by large OEMs and servicers. There’s lot of nuance here, OEMs might have an entirely owned services arm, but often you’ll see independent firms that are are multi-faceted. They may emerge in the building construction stage, they may be contracted in Convex’s case, there’s usually a whole other group that are involved.
These independent service companies are not vertically integrated and focus far more on the design, installation, and maintenance of equipment and systems.
But here’s the real kicker and why Convex is proving important: Commercial Services is undergoing an implicit digital transformation because it is undergoing an explicit revenue transformation1
Here’s a good example from an interview Convex did with one of their customers, Jay Byers from Schneider Electric:
“It’s the same story for Schneider as it is for a lot of other companies: when we go to install a widget on a site, we want to attach services to that widget. We’ve seen that we have thousands of sites out there that we’ve installed which, for a variety of reasons, may have atrophied over time or be dormant customers. Our goal is to expand and saturate the install base more.
Think about the experience of going back and trying to find intelligence on these buildings. It’s probably changed, and we need technology to be able to supplement [our existing intel]. The only way that we’re going to be able to get to 2X in three years is by investing in technology and using it as a force multiplier."2
It’s not just services and installation anymore, with the rise of smart buildings and IoT devices, service companies are adding SaaS elements. The quest for margin expansion, the intense commodification pressures, and the need to be far more efficient means the industry is suddenly looking for an industry partner.
After all, if you want to look more like a tech-enabled servicer, your tech stack better be top notch.
That’s where Convex comes in. The industry needs more data, more ways to use their data, and a better platform to leverage it in industry specific workflows.
And that data and platform is exactly what Convex is providing.
The Convex Platform
To state a truism:
All commercial services take place at a building. Certain services might be on the periphery of a building like landscaping, but nonetheless a building that wants to beautify itself is involved.
Thus, most sales and marketing teams wanting to be more efficient need far better ways of analyzing what buildings are worth servicing and which ones aren’t.
Building doesn’t fit your ideal building persona? Time lost.
And even in the case where you find a building that does meet your criteria, there’s another huge challenge: buildings don’t sign contracts. People do. And that building may be owned or managed by someone in a completely different Iocale.
And say you decide that this building is worth your while, are you sure that it’s going to be profitable to undertake? Do you have other buildings you service in the area? Or is it in need of an entirely new service team?
What if you first approach the desired Company you want to target and then need to understand their building portfolio? Again, all commercial services take place at a building.
In the past, this has meant that the ideal sales rep in commercial services looks a bit like Trevor Rainbolt: the guy who can pinpoint an exact spot on the map from like 3-4 details on the picture.
Pinpoint the right type of building, find the owner or manager, and also ensure that that it makes sense for your company to service.
In brief, Trevor Rainbolts don’t scale. You can’t really operationalize someone’s innate talent for spotting the proper and profitable buildings on a map. Marketers need the law of large numbers, too.
But the key problem is that none of this geospatial or even building intelligence data really existed in a usable form for commercial servicers. So Rainbolts reigned.
Convex the Company
Even before fully conceptualizing this specific issue, Convex cofounders Charlie and Blake knew something was up in commercial services. Charlie’s a Detroit native with an affinity for software in the industrial world; what he calls “the backbone of the global economy.”
And as they started to land on the challenges that commercial servicers were facing in the revenue org, they started to dial in on the data problem in more detail.
It wasn’t clear that simply building a vertical CRM first would provide excess value. After all, the foundational problem wasn’t a workflow issue, the large players were using CRMs and that still wasn’t doing the trick.
Instead, they wanted to fix this data and insights gap, largely stemming both from data silos inside of the servicers as well as a huge lack of tooling around the rest.
The way to tackle it? Unite all disparate data sources and rethink entirely how to surface the right insights.
And at base, this means making the building the core data primitive. And Convex’s first product, Atlas was born.
Underlying the specific vertical challenge is a general data challenge that vexes many a data scientist. How should you model many-to-many relationships in a way that’s suitable for use? In this case, there are many buildings, each with many different possible owners and managers, and many other data points that a commercial servicer would find useful to link. The real heartbeat of Atlas is thus a data schema and ingestion pipeline responsible for all the data transformation and structuring needed to aggregate GIS, owner, and property data into one useful tool.
This gives servicers three really powerful unlocks:
Base level of intelligence on the building, company, and person level
Their own data which is structured into highly actionable insights
Resulting workflow software that drives high adoption
Bringing in these data streams in turn gives access to previously untenable insights. For instance, find a property you are interested in serving? Instantly, you can know other buildings around, if you’ve serviced some properties owned by the same group, and if those properties had problems.
Atlas isn’t simply dialing revenue teams into new lines of business. It’s dialing them into higher-margin business.
And as companies discover more and more about what sort of insights Atlas can serve, Convex gains penetration into all sorts of GTM adjacent teams.
Industry Diagonals and Market Expansion
As Convex has grown, word has gotten out. There’s plenty of subverticals that also need these kind of services
Convex has picked a surprising amount of customers in the roofing industry, for instance. And even though that isn’t exactly the target buyer Charlie had in mind starting out, they absolutely love the product.
When word starts to spread amongst industry participants that you didn’t predict, you suddenly start to wonder how much time and energy to spend building features or additional products for a subvertical. After all, in building an industry cloud, there’s always a danger of overfitting. And as Convex starts to plan out their second, third, and fourth act, strategic questions emerge around how to unify as many of these subverticals within the platform, while not overpromising or overfitting for any particular client.
In Charlie’s opinion, when building an industry cloud, you can welcome new diagonals so long as they are directly close to the existing portfolio. That’s a gray line, but one I think Convex has done well. Work with buildings? Then bingo, Convex can help. But they aren’t going to be onboarding solar servicers that work on rural utility scale installations anytime soon.
And this too, points to how well Convex is setting themselves up as an industry partner. They have a long term vision, but also are aware of where they may not be adequate for niche needs. Rather than overcommit, they’re happy to take the patient road and win all aspects of commercial services over time.
After all, Convex is busy at work figuring out where to continue to add value. So where do you begin when you have all this data?
The Second Act
Charlie has studied Veeva closely, especially around developing additional product lines. Veeva with their second product went into a seemingly unrelated part of the life science companies. It wasn’t so much a momentum play. Instead, it was far more about finding additional wedges inside of these large companies to partner.
In Charlie’s words, for your second act “you might want to set new criteria that take you far away from your current target customer.”
Beyond some of the Peter Gassner rationale here, there’s a really nice calculus in Convex’s case. First, the industry has found it really hard to transform in line with its goals. That may be felt most heavily on the revenue side, but it’s universally impacting everyone.
That parlays nicely into social proof that Convex has cultivated with Atlas: they know how to meaningfully partner in innovative ways. In an industry that has not had a transformational partner, new wallet share is willing to open.
Lastly, in many ways Convex’s initial platform mirrors Veeva’s second product, Vault.
Vault after all is both infrastructure and a product. It’s a tailored hub for all hosting important documents and data streams for different departments. Convex has already built that muscle, built integrations into important sources of truth for the industry, and can move quickly to create new products on top of the architecture when they have the right product. That gives them huge leverage to expose new analytics, new workflows, and more to different segments of the company.
Building for Decades
In slow moving industries, often the right strategy is to simply take the long view. Sure, there are short term metrics to hit, but trust-building takes time. And trust-building is fundamental to building and implementing the sort of products that customers find incredibly valuable.
Charlie is in this for the long run. His long term plan is to run Convex as a public company until he’s in his 60s. And that perspective means that Convex thinks in decades. What matters next is picking areas where they can gain additional wedges into the company and then proving out massive value.
Data and the next wave of industry clouds
A couple years back, Emergence, one of the only venture firms that invested in Veeva, wrote a fantastic blog on the next wave of industry clouds. Emergence led Convex's Series A and you can instantly see why. Their thesis? Build around a data stack.
“These startups vertically integrate deeply within an industry to ingest data from vertically specific data sources, pipe that data into industry tuned data schema, and subsequently pipe that data out into industry-specific applications or analytics engines. An industry cloud data company can tackle the long-tail of niche, vertical-specific systems and vertical-specific data problems that don’t make sense for horizontal companies to target.”
My hunch is this line of thinking only gets more powerful with the coming transformation in software as a result of AI.
But even before then, there’s massive value creation. Deeply synthesizing industry data gives you a real claim on rebuilding the application level with deep data enrichment. It would be one thing for Convex to lead with a CRM, it’s another for them to build the pipes and platform upon which to architect a “smart CRM” infused with insight. In many ways, this is also the path taken by Tekion.
Industry data sources are powerful when combined in a platform yet the platforms are deeply hard to build. To get to a useful state, you must spend plenty of time understanding the proper industry schema and separating signal from the noise. But all that work does give you a moat - especially as you start to touch more and more data.
Charlie thinks moats are really hard to come by with decreasing costs in software and plenty of companies competing at the workflow level. But what if you bypass the workflow initially? That’s the best move the next wave of industry clouds may make. And, Convex is sure going to find out.
Charlie and I both don’t love the digital transformation jargon, but alas it’s what AWS has left us with for now.