Cloud Business Models

Cloud business models are all built on top of cloud computing, a concept that took over around 2006 when former Google’s CEO Eric Schmit mentioned it. Most cloud-based business models can be classified as IaaS (Infrastructure as a Service), PaaS (Platform as a Service), or SaaS (Software as a Service). While those models are primarily monetized via subscriptions, they are monetized via pay-as-you-go revenue models and hybrid models (subscriptions + pay-as-you-go).

Origin Story

In 2006, the term “cloud computing” picked up, as tech giants like Amazon and Google were vastly investing in bringing applications on the web; with fast deployment and continuous updating, this model became viable not only at enterprise but also at the consumer level. And it gave birth to new business models built on top of the cloud, such as IaaS, PaaS, and SaaS
(Image Source: Google Ngram)

Back in August 2006, at Search Engine Strategies Conference, in a conversation with Eric Schmidt hosted by Danny Sullivan, the former Google’s CEO pointed out,

What’s interesting [now] is that there is an emergent new model, and you all are here because you are part of that new model. I don’t think people have really understood how big this opportunity really is. It starts with the premise that the data services and architecture should be on servers. We call it cloud computing – they should be in a “cloud” somewhere. And that if you have the right kind of browser or the right kind of access, it doesn’t matter whether you have a PC or a Mac or a mobile phone or a BlackBerry or what have you – or new devices still to be developed – you can get access to the cloud. There are a number of companies that have benefited from that. Obviously, Google, Yahoo!, eBay, Amazon come to mind. The computation and the data and so forth are in the servers.

And he continued:

And so what’s interesting is that the two – “cloud computing and advertising – go hand-in-hand. There is a new business model that’s funding all of the software innovation to allow people to have platform choice, client choice, data architectures that are interesting, solutions that are new – and that’s being driven by advertising. The reason that I said “don’t bet against the Internet” is an awful lot of people are still trying to do stuff the old way. They’re still trying to build proprietary protocols, they’re still trying to not build standardized protocols. They’re still not trying to solve problems in a simple and extensible way. But when somebody does it right – let me give you the example of mashups, which are taking over the world by storm. It happens very fast. And that’s the power of the Internet.

While the term picked up traction from there, even though the term and potential of this technology were already understood in 1996, when a group of executives at Compaq already had forgone that most applications on the web of what they called “cloud computing-enabled applications.”

Even though, as we saw above, it would still take ten years, for this technology to pick up at scale. And by 2020, cloud computing would become one of the most profirable industries, and units of tech giants like Amazon (with AWS) Microsoft (with Azure), Google (with its Cloud), and IBM.

Not only that, cloud computing enabled the birth of an entrepreneurial ecosystem, and hundreds of companies, both in B2B and B2C that leveraged the cloud to build valuable products and services.

Consumers’ companies like Netflix, Spotify, YouTube are all built upon the cloud. Other enterprise-based organizations as well.

Classification of Cloud-Based Business Models

Cloud-based business models are usually classified as:

  • IaaS: in the infrastructure as a service, the cloud provider usually offers networking, storage, hosting, and virtualization. In this way, the customer can leverage a cloud-based infrastructure without building it internally, therefore avoiding the cost, complexity, and time required with that. In a way, the IaaS customer can leverage a complex infrastructure without building and maintaining it and using it on demand.
  • PaaS: in the platform as a service, the cloud provider also offers the platform to build applications for customers/users. Therefore, users will have all the tools needed to build these applications. Also, the customer gets a whole set of tools on-demand, without having to build them, while the client will manage those applications and related data.
  • SaaS: in the software as a service, the provider offers also applications and data management, so that the final customer can get service on demand.

Technological Infrastructure

Depending on the type of cloud-based business model, the company might have a complex or less technological infrastructure or platform. Perhaps, a SaaS service might well be built on top of existing IaaS and PaaS. Therefore, only do the part related to the UI and UX development for final users/customers.

Other cloud-based infrastructures can be extremely complex. Companies like Amazon AWS, Google Cloud, Microsoft Azure, and IBM Cloud (which are the major players) took years to develop and enabled an entrepreneurial ecosystem of companies built on top of them. A whole set of SaaS companies are built on top of those cloud providers.

Commercial Use Cases

The commercial use cases covered by cloud-based business models is vast. From B2B/Enterprise companies offering big data analysis, business intelligence, inventory management, and much more, to B2C companies offering streaming services, social media platforms and more to final customers.

Revenue Models

While business models built on top of the cloud are usually driven by a subscription (as they run as an on-demand service), in reality there are several revenue streams used:

  • Subscription-based.
  • Consumption-based (pay-as-you-go).
  • Advertising-based.
  • Hybrid models.

Read More: IaaS vs PaaS vs SaaS

Connected Business Frameworks

Customer Lifetime Value

One of the first mentions of customer lifetime value was in the 1988 book Database Marketing: Strategy and Implementation written by Robert Shaw and Merlin Stone. Customer lifetime value (CLV) represents the value of a customer to a company over a period of time. It represents a critical business metric, especially for SaaS or recurring revenue-based businesses.


AIOps is the application of artificial intelligence to IT operations. It has become particularly useful for modern IT management in hybridized, distributed, and dynamic environments. AIOps has become a key operational component of modern digital-based organizations, built around software and algorithms.

Machine Learning Ops

Machine Learning Ops (MLOps) describes a suite of best practices that successfully help a business run artificial intelligence. It consists of the skills, workflows, and processes to create, run, and maintain machine learning models to help various operational processes within organizations.

Continuous Intelligence

The business intelligence models have transitioned to continuous intelligence, where dynamic technology infrastructure is coupled with continuous deployment and delivery to provide continuous intelligence. In short, the software offered in the cloud will integrate with the company’s data, leveraging on AI/ML to provide answers in real-time to current issues the organization might be experiencing.

Continuous Innovation

That is a process that requires a continuous feedback loop to develop a valuable product and build a viable business model. Continuous innovation is a mindset where products and services are designed and delivered to tune them around the customers’ problems and not the technical solution of its founders.

Technological Modeling

Technological modeling is a discipline to provide the basis for companies to sustain innovation, thus developing incremental products. While also looking at breakthrough innovative products that can pave the way for long-term success. In a sort of Barbell Strategy, technological modeling suggests having a two-sided approach, on the one hand, to keep sustaining continuous innovation as a core part of the business model. On the other hand, it places bets on future developments that have the potential to break through and take a leap forward.

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