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Big Data and Software Pricing

By February 24, 2013Article

Value-based pricing —  the holy grail of pricing strategy for companies seeking to optimize customer revenue contribution — is not an easy undertaking. Software executives have long experienced difficulty pricing their on-premises software on value delivered, due to a lack of deep insight on how products are used after they are sold.  

But what if software executives had access to the customer and product data that makes such insight possible? With Software as a Service (SaaS) products, they often do. 

SaaS products have access to usage data typically not available for on-premises installations, which gives hosted products unique advantages when it comes to incorporating customer value into the pricing model. A combination of product usage data, customer feedback and transaction data stored within the application can be used to derive valuable insights around product usage and value.

These insights can in turn be used to refine pricing models and customer segmentation strategies to more closely align with the value received from using the software. Incorporating these data sources into your pricing strategy requires the technological sophistication to capture and manage large volumes of structured and unstructured data sets, the analytical expertise to derive insights, and a management model that enables dynamic decision making based on the insights gathered. 

Conventional SaaS pricing methods have typically failed to leverage the wealth of information available to help determine optimal pricing. Subscription prices for SaaS products are often set based on a planned three- or five-year return of the license and maintenance revenue of their on-premises counterpart. For example, the Adobe Photoshop CS6 one-year subscription is $19.99/month, while its list price for license is $699 — essentially a 2.9X multiple over the annual subscription price. 

Other approaches typically involve establishing an initial price point based on an assessment of the total cost of ownership of a competitive SaaS or on-premises solution. While these strategies take into account factors such as cost, competitive and substitute price points, none of these approaches get at the true value of the service being provided to the customer. That is where Big Data can be leveraged. 

As a vendor of SaaS products, there are multiple data sources you can leverage to help align segmentation and pricing with the way that the product is used — and therefore, valued — by the user. We categorize those data sources and provide examples on how the data can be leveraged in the table below. The illustrative example shows the detailed use of these data sources for optimizing pricing for an enterprise software vendor. 


Waterstone big data graphic

Successfully executing on a data-driven pricing strategy requires technology sophistication to capture and manage large data sets, analytical expertise for insight development and a flexible management and operating model to translate the insights into specific pricing changes.

Developing Big Data capabilities requires investing in new skills, tools and processes. Fortunately, SaaS offerings usually already capture relevant data, and the ability to creatively mine the data presents a compelling opportunity to enhance your pricing strategies, better understand customers and ultimately optimize revenues. 

Dhaval Moogimane is a partner at the Waterstone Management Group, a strategy consulting firm that works exclusively with investors and management teams of technology companies. Dhaval focuses on helping clients capitalize on disruptive technology trends to create and scale new platform products and solutions. Contact him at 

Hubert Selvanathan is a principal in Waterstone’s San Francisco office. He has 17 years of operating and consulting experience in software and IT services. He focuses on helping launch, scale and optimize new technology offerings and business models. Contact him at 

Apurba Pradhan is an associate in Waterstone’s San Francisco office and consults on growth strategies related to new offering design/launch of software and services. Additionally, Apurba has 10 years of operational experience in product development and marketing. Contact him at

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