The Economics of Product Differentiation: Why SaaS Stops Scaling in Mature Markets

Established for almost twenty years, Software as a Service (SaaS) has been hugely successful, allowing vast numbers of organizations to utilize standardized tools hosted on the cloud. The entire premise was built around the ability to use the same codebase, delivering solutions to thousands or millions of customers and producing economies of scale. However, although SaaS has been developed to a very high standard, custom software development is now one of the fastest-growing areas of today's digital economy, as organizations are increasingly outsourcing their development to agencies rather than using SaaS solutions, where applicable.

This trend may seem counterintuitive; shouldn't the software industry be moving toward greater standardization, rather than moving in the opposite direction? The principles of economics support the opposite case. By drawing upon theories of product differentiation as outlined in the works of both Chamberlin and Dixit–Stiglitz, we can articulate a strong rationale for why SaaS is limited in its market potential, particularly as the market shifts away from mass demand toward the long tail of highly specialized product needs.

Economies of Scale and Limits on Standardization

The economies of scale in SaaS depend on large fixed costs and very low marginal costs. Building out SaaS platforms is costly, but once built, adding new users costs almost nothing—nearly zero. For instance, Salesforce's recent gross margin of approximately 78% reflects the classic economic characteristics of being able to achieve scale through efficiency.

Conversely, the economic structure of SaaS inherently creates disincentives for customization. It is cost-prohibitive to create customized solutions for users with niche workflows or non-standard data structures because the increase in marginal cost versus the increase in revenue produced is disproportionate. Supporting a niche workflow or a unique data structure diminishes the standardization of SaaS platforms that makes them feasible.

Using the Dixit–Stiglitz monopolistic competition model, firms can assess how many varieties of niche offerings are viable with respect to fixed costs, marginal costs, and consumers’ ability to pay for that level of differentiation. The optimal point for firms is very different from the level of differentiation required by the business community, where companies have different processes.

For SaaS firms, therefore, the rational business model is to stop horizontally scaling functionality and instead scale vertically by acquiring more users, rather than pursuing new initial or extended forms of customization.

There is a Long Tail and Growing Demand for Weird Software

As more and more businesses adopt digital technologies across different industries, they are also evolving from traditional digitalisation (used primarily for communicating with employees via email, CRM, payroll, etc.) to supporting very specific operational needs and functionality. This is known as the "long tail" effect: once a company has addressed its common or "big" problems, the many smaller or niche problem solutions that have yet to be addressed will continue to exist across thousands of different niche sectors.

The data supports this. According to data provided by BCG, over 70 percent of enterprise software development projects conducted today use some form of custom development or integration. By 2027, according to predictions made by Gartner, 65 percent of enterprise applications will need to have custom components built in, even though there are currently equivalent SaaS applications.

A real-world example of manufacturing workflow systems illustrates this point.

As a result, manufacturers with highly specialized manufacturing workflows are likely to hire software development agency teams as opposed to using a generic SaaS platform, which does not provide specialized features (for example, a platform for home goods safety testing that requires a specific product testing sequence).

As manufacturers implement customized solutions for their production lines, they may also find that doing so allows them to increase the overall efficiency of their manufacturing operations.

Real-World Example 2: Financial Risk Modeling

Banks and hedge funds utilize their proprietary systems and models to remain ahead of the competition. With the growth of Software as a Service (SaaS), however, the value of these proprietary systems and models has diminished because SaaS vendors provide all necessary inputs and a consistent methodology for all their customers. As a result, more financial companies are now developing their own custom analytic environments instead of purchasing an authoritative off-the-shelf risk solution.

One of the main factors contributing to this trend is the increasing cost associated with modifying an organization’s SaaS risk product versus developing a new, customized analytic model that is unique to that organization.

Economic Forces Behind the Shift Towards Custom Development

Three key economic drivers exist behind the current wave of customization:

1. Diminishing Returns to Standardization
2. Increased Value of Differentiation
3. Economic Asymmetries and Tacit Knowledge

Diminishing Returns to Standardization Once a single Software as a Service (SaaS) provider can cover 80 percent of "mass" use cases, the cost to serve the remaining approximately 20 percent of use cases increases significantly. This is illustrated by the marginal cost curve taught to students in microeconomics classes.

Increased Value of Differentiation As industries continue to mature, firms compete less on basic operational efficiencies and more on their proprietary or unique processes, information structures, and workflows. Differentiation is becoming the new core strategy for these businesses.

Economic Asymmetries and Tacit Knowledge Many processes are too complex to be formally codified into a generic SaaS feature set. As a result, many firms have been driven to create their own custom tools to better reflect their organizational expertise.

Effects on the Global Economy

This transition marks the next level of digital maturity:

• The growth of SaaS for typical, non-industry-specific use cases will continue, but it will eventually reach a plateau.
• Custom development will continue to grow rapidly, as companies strive for competitive advantage.
• Hybrid solutions that include SaaS technology along with extensible custom modules will provide a middle ground between purely SaaS-based and purely custom systems.
• The labor market will increasingly reward developers who can create systems that are unique or domain-specific, and the economy will continue to transition from mass-market standardized product offerings to monopolistic competition, where differentiated products, rather than standardized ones, provide value.