Marginal cost pricing has been a common theme for many computing industry products. The concept is that retail pricing is set in relation to the cost of producing the next units, but not including amortization of any investments in infrastructure.
Almost counter-intuitively, there are many examples of firms selling computing products at (or near) marginal cost (sometimes at prices near zero), yet still producing strong long-term capital recovery and attractive ROIC.
That seems to defy economic logic, but it does work. How, since the investments in infrastructure still must be recovered?
Simply, the firms did not monetize the thing they priced at marginal cost, but instead “monetized what that thing made possible.”
The underlying economics, in computing, are simple: marginal cost collapses faster than average cost. So once a fixed investment is made (processor cycles; storage reads; memory access; bits transmitted; copies of apps), it is possible to price the commodity layer at marginal cost but then recover capital in a complementary scarcity layer.
In other words, marginal cost pricing works when a supplier has something else to monetize, someplace else in the value chain or stack.
The IBM mainframe business sold batch jobs or processor time as a service at marginal cost. But IBM recovered the cost of its invested capital other ways. It’s margins on hardware were high. Its customer lock-in was similarly high.
And IBM was able to sell system engineering and software pertaining to its machines and ecosystem.
So marginal cost pricing for compute services worked because customers could not switch platforms. So financial returns came from other elements of the platform.
Microsoft provides another example. Copies of Windows; Office and developer tools were sold at affordable prices. But Microsoft made its profits from its operating system “monopoly;” developer lock-in; bundled distribution and version upgrades.
So Windows licenses were “cheap” relative to value delivered, with an incremental cost that was effectively near zero, but with profit margins near 90 percent.
What Microsoft essentially monetized was its control of the “standard” for operating systems and the platform.
Google search arguably offers an even-more-compelling case, as the product is available to users at zero cost.
Search queries cost nothing. Neither does use of Google Maps, Gmail, Android or the Google productivity suite.
But with its advertising monetization, Google creates a revenue model based on user attention.
So apps requiring lots of compute infrastructure are monetized other ways. “Compute” is not the product; audiences are.
Amazon Web Services, it can be argued, prices core products near marginal cost (EC2 compute, S3 storage, throughput).
So AWS monetizes risk reduction and reliability rather than compute cycles. “Trust” creates the revenue model while lock-in sustains it.
Perhaps the best example is Open Source, which, by definition, is “free to use.”
Products such as Red Hat are sold at marginal cost (licensing) or the software itself is available at no cost.
The Apple business model might not seem to be a case of marginal cost pricing for hardware, as such pricing is not bound by marginal cost parameters.
On the other hand, the ecosystem software (iOS, macOS, developer tools, some cloud services) actually can be characterized as being made available at marginal cost.
Apple recovers its infrastructure and sunk costs from hardware profit margins, ecosystem lock-in and services.
If computing marginal cost approaches zero, then retail pricing also tends to fall to near zero, while successful firms find other places in the value chain to recover capital investment costs.
Where might scarcity value remain?
Time
Trust
Risk transfer
Attention
Control points
Integration responsibility
Physical manufacturing
Distribution
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