How the cloud has transformed vendor business models

The steady rise of the cloud in the enterprise has been a game-changer, overhauling how companies run operations both internally and externally.

But the versatility of the technology has also had a major impact on how enterprise vendors sell their services, as customers want to scale and adapt their cloud models and expect their vendor to support them along the way.

Discussing what this means for the cloud industry, and indeed how it continues to prosper as a whole, is Martin Moran, EVP of Global Selling Services at ServiceSource, in our Q&A.

TechRadar Pro: How exactly do you value and quantify the business benefits of the cloud?

Martin Moran: With cloud computing becoming so pervasive and commonplace in our day-to-day lives and businesses, everyone has differing opinions on how to quantify the true value of the cloud.

On its surface, the cloud brings economies of scale that can be quantified through traditional metrics such as cost savings and performance improvements.

These accrue both to customers, who have an unprecedented range of options and the commercial freedom to exercise these at will, and to vendors who are able to make changes to their applications and have these immediately available to customers with no painful migration processes.

However, the real benefit of the cloud is the ability to do things that you couldn't otherwise do, and the unprecedented agility it affords.

The cloud allows for unprecedented aggregation of data across an industry, which can serve as the basis for "machine learning" and "prescriptive analytics." SaaS providers offer customers something that they simply can't do themselves.

Even if they had access to their own data and computer scientists, they don't have access to the breadth of representative data from multiple sources.

The whole promise of big data and the improved conclusions companies are able to draw from being able to process and interrogate truly vast amounts of disparate information is only possible due to the cloud.

In short, because of the cloud, we are in an early phase of the next generation of enterprise applications, where machine learning across large data sets enables better business decisions for the enterprise SaaS users.

An example in the consumer space is Amazon's recommendation engine, which customises the browsing experience for returning customers based upon their previous purchases, items in a virtual shopping cart, or items that have been rated and liked.

Amazon uses prescriptive analytics to tailor the experience for one individual based on analysing the patterns present in the enormous amount of data they gather across their entire user base.

It subsequently becomes more "intelligent" based on these choices and usage patterns – adding intelligence to proactively push previously unconsidered choices greatly enables better cross-selling performance.

Better still, so long as the choices are relevant, they are typically not 'dissatisfiers' to the customer experience – a key problem with conventional up and cross-selling techniques.

Best of all, there is little incremental cost in pushing these options to customers and thus the economics of conversion are much more favourable to the vendor – they are able to learn more about customers whilst selling more product.

So, how does one measure the value of the cloud? Clearly it can be measured in traditional terms of cost reduction, increased revenue, and customer loyalty due to improved service levels. Personally, what I find the most exciting is exploring the new ways big data and prescriptive analytics enables us to better serve our customers that simply weren't available to us before the cloud.

TRP: Why is a subscription business model becoming the future for cloud-based business? What benefits does it bring?

MM: I think the starting point for this question is that we should recognise that subscription business models are not new. They have been with us for quite some time. We can reflect on how in our own lives we have been using subscription models for many years.