Revenue models—Processing revenues for high-throughput B2B markets

Processing revenues as a revenue model are most common in business-to-business (B2B) markets and depend heavily on high throughput.

Applicable industry

Though a variety of industries use processing revenues, this article focuses on processing in the information and communication technologies sector. Examples from this sector include:

• Online advertising distribution
• Financial transactions such as insurance applications, claims and mortgage applications.

Customer relationships

Usually, the processor has a very close relationship with their customers. The processing functionality is generally integrated seamlessly into the customer’s infrastructure, and this requires credibility and organizational maturity.

Marketing issues related to processing revenues

Processors usually have a relatively small customer base and engage in long and complex sales cycles with an emphasis on proving functionality and compatibility with existing systems. Sales relationships are long-lasting, and the greatest difficulty lies in establishing an appropriate price per transaction.

Operational implications

Processors trade on efficiency and reliability, which is often a function of integration skills.

Financial and strategic implications

Processors require significant up-front investment in order to build instantaneous, scalable processing capability. Processors also require sufficient capital to fund the company through the long sales cycles before break-even is achieved.

Key metrics

Processing companies value these metrics highly: processing cost per transaction and transaction volume per time period.

Modalities

Offline versions of processing revenue models are becoming increasingly common in the cleantech industry as it processes increasingly diverse forms of waste.

Costs and benefits of the processing revenue model

Customers of processing companies appreciate the processing revenue model because it allows them to focus on their core offering, and spares them the trouble of processing in-house. A drawback of the model is that processing companies face significant set-up costs in the form of integration time. Processing companies must develop and document best practices to reduce the difficulty of integration for their customers.