If aliens landed and read my LinkedIn feed, they would conclude the world economy runs on SaaS. It does not, and the gap matters more than it sounds.
Most of what I see about sales structures, KPIs, pipeline process, marketing, tech stacks and lessons learned carries a SaaS vibe. Some of that is the algorithm and the people I follow. But the effect is real: the operating playbook that gets shared, copied and sold is a SaaS playbook.
So I went looking for the actual number.
The number is smaller than the feed suggests.
When I ran this down in 2022, cloud services revenue was roughly $332B, of which about $122B was SaaS applications. Against a global economy estimated around $94T, that put SaaS at something like 0.15 percent of the pie, and cloud services overall at about 0.3 percent.
Those figures have grown since. The order of magnitude has not. Even if that analysis was off by ten times, SaaS remains a small slice of global economic activity, and a much smaller slice of the mid-market companies I actually work with. Manufacturers. Distributors. Financial institutions. Healthcare services. Construction and industrial services firms. Companies that sell things, install things, service things and renew contracts that look nothing like a monthly subscription.
Every one of them is running a go-to-market motion designed for a business model they do not have.
Where the SaaS playbook breaks.
The funnel assumes a product that sells itself.
SaaS funnels are built around self-serve trials, product-qualified leads and a buying process the customer can complete alone at 11pm. If your product requires a site visit, a spec, a quote, a credit decision or a licensed installer, none of that applies. Copying the funnel gives you stages your reps cannot honestly move a deal through, which is how stage data goes bad in the first place.
The metrics assume subscriptions.
Net revenue retention, logo churn and CAC payback are excellent metrics for a subscription business. Applied to a company with project revenue, seasonal volume or multi-year replacement cycles, they produce numbers that are technically calculable and operationally meaningless. I have watched leadership teams argue for a quarter about a retention figure that did not describe anything their customers actually do.
The stack assumes product telemetry.
A lot of modern RevOps tooling is built on the assumption that you can see the customer using the product. If your product is a pump, a loan, an implant or a crew on a roof, your signal comes from service records, field data, order history and the people who talk to the account. That is a different data architecture, and buying the SaaS-shaped tool does not create the signal you are missing.
The org chart assumes a CSM.
The customer success function exists because subscription revenue has to be re-earned continuously in-product. Most non-SaaS companies already have people doing retention work under other names: account managers, service managers, branch leads, relationship managers. Adding a CSM layer on top of them usually creates a coverage argument, not a retention program.
What is worth stealing from it.
This is not an argument to ignore what SaaS operators have figured out. Much of it is genuinely better than what came before, and it transfers cleanly:
Recurring revenue as a goal. I prefer it, and most business models have some version of it available: service contracts, managed services, consumables, maintenance agreements. SaaS companies simply got there first and got serious about measuring it.
One revenue number instead of three departmental ones. That is the real lesson of the last decade, and it has nothing to do with the business model. I wrote about it in why revenue operations is replacing sales and marketing.
Instrumentation as a default. Deciding up front what you will measure, and building the system to capture it, rather than reverse-engineering reporting from whatever the reps happened to fill in.
A short test for which playbook you need.
Ask four questions about your largest revenue stream. Can a customer buy it without talking to a person? Does the revenue recur without anyone re-selling it? Can you see usage between purchases? Does your cost to serve scale with headcount?
Answer the first three yes and the last one no, and the SaaS playbook fits. Answer them the other way and you need a system designed around your buying cycle, your service history and your installed base. The work we do is mostly that: taking an enterprise platform that was configured from a SaaS template and reshaping it around how the business actually sells.
The failure mode here is the same one I described in how legacy infrastructure kills new ventures, only running in the opposite direction. There, a widget company tried to sell software the way it sold widgets. Here, a widget company tries to sell widgets the way a software company sells software. Both fail for the same reason: the model and the motion do not match.
The takeaway.
There is a second point in here, and it is more personal. I experience what I call FONK, the fear of not knowing. I see concepts in my feed I do not feel competent in, the anxiety builds, I buy books that stack up in the corner of my room, and my wife develops her own anxiety about the stack. A bad flywheel.
Perspective fixed it. A small number of people post content, and the content they post describes a small slice of the economy. If your feed is telling you that you are behind, check the denominator before you rebuild your revenue engine around it.
What does your feed reveal?
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