Data and business analysis was until recently a support function — it needed business data to be useful, but the data itself was not the product. The analysis was. That has changed. Data is now being presented and sold as the main product.
The Data-as-Product Business Model
The model has three layers:
Data collection as an ancillary service. One part of the business works with an entire industry to collect data, made available as a free or freemium service. Examples: Google Analytics, Walnut app, SwaggerHub. If a good product or service offers a free plan, more often than not the data you enter will be used for multiple purposes beyond the one you signed up for.
Data aggregation and visualisation. This is the marketing function — benchmark visualisations shared across the industry, data reports about competitors. It drives early adoption and gets practitioners talking.
Data access and pricing. This is how the business monetises. By selling access to aggregated, structured data — on a pay-per-use or subscription basis. Examples: SEMrush, SimilarWeb, CIBIL scores.
The Colonial Parallel
What gets my attention is that the firms collecting this data are often based in other countries. Going back 300 years, the British killed the Indian textile industry by controlling raw materials — buying cotton at throwaway prices, then selling finished goods back at premium. The cotton is analogous to data being collected today. The data aggregation and reports being sold back are the finished goods.
300 years back we were afraid of the East India Company. This time around we are welcoming data traders with open arms. Whether we should be more careful about who uses our data and how is a question worth asking.