How a Semantic Layer Impacts Pricing Strategies

In the realm of data monetization, the integration of a semantic layer stands out as a key component in building a pricing strategy. A semantic layer serves as a translator between intricate data structures and actionable business insights, fostering clarity for both technical and non-technical data consumers/customers. The way that data is presented to an end user inherently affects the perceived value of that data. Semantic layers make pricing tiers easy to manage by offering the ability to dynamically provision data content access.

Semantic layers add value to your data.

Consider a scenario where a company is selling data outright to their end customers. The data itself holds value, or else the customer would not pay for it. But if the data is only available via a csv download, the customer will need to spend people-hours to ingest, transform into insights, and present the data before they can take action on it (thereby realizing its value). If instead the data is pre-packaged to answer questions that the customer would typically have, it saves that customer time and money, and is of increased value over a raw file from a data export.

Semantic layers allow for easily managed pricing tiers.

In the same scenario above, one company may pay a basic subscription fee and get access only to the data extract. But another may pay a premium and get access to the governed, cleaned, and insight-laden data that the semantic layer affords. As the company’s datasets mature and become further enriched with new sources, additional pricing tiers become possible - The “Bronze” tier continues to offer a csv extract. The “Silver” tier may offer a basic dashboard with pre-canned metrics presented in an intuitive way. And the “Gold” tier may offer a self-serve interface behind the dashboard for drilling and data exploration, ML-driven predictive analytics, and connections to a data activation layer.