Data Monetization Business Models
Formulating the right monetization model lies at the heart of commercial data strategies. Defining the right model requires true clarity on the value drivers surrounding the production and consumption of targeted data and analytics. Key questions and dynamics to explore include:
- Who benefits from the data or analytics and what will it help customers achieve
- Is this a core or supplemental offering in our product portfolio and what are the potential impacts to existing product and service lines
- How does this offering evolve and what will drive pricing or value changes
Though still in its early stages, new data monetization models have emerged in the business-to-consumer and business-to-business worlds. Up and coming models include:
- Performance Ecosystems (B2B)
- Product Performance Insights (B2C)
- Packaged Insights (B2B and B2C)
In a Performance Ecosystem, a network of B2B members improve individual business performance because network members securely contribute data towards the creation of aggregate views and insights. With the Product Performance Insights monetization model, usage data from consumer product or service is tracked and analyzed to give users insights into performance, reliability, and activity patterns. Aggregated to protect privacy, the manufacturer can offer further data solutions to the same market or to entirely different market segments valuing the insights.
Agreement on a data monetization model is critical for the achieving the the right software solution. It provides critical guideposts on fundamental needs around architecture, deployment model, security standards, integration, and visualization. In turn, knowing the monetization model empowers the technical teams with the confidence to act with speed during the development process.