Any analysis team would work day and night to justify the reason for their being. There are enough articles being shared on the internet on arriving at a Return on Investment for Analytics (RoIA). However, the main service that any of these teams did was to crunch business data into A-has. This hasn’t changed over the years, and a lot of analysts derive job satisfaction through this very hunt for the A-ha! from their audiences.
The switch to being a core business
Data and business analysis was until now a support function, which needed business data in order to thrive and be effective. Aside from very few models (those that sold business critical data such as ratings, organizational data, etc), the data was never used as the primary product.
There was always a pre-activity and an analysis activity for that data to be useful. However, over the years I am seeing that has changed. Data is now being presented and sold as the main product.
Data as the product
Those of you who know Bloomberg, Hoovers, S&P or CRISIL, would know that data as a product business model works. Now that you know the pattern, let’s take a look at how this business model works.
Data collection as a ancillary service
There is one function of the business which works with the entire industry it is catering to, to collect data. This more often than not is made available as a freemium or free service.
Some examples of this would be – Alexa Certified metrics, Google Analytics, Walnut app, Swaggerhub, etc.
You get the general idea here. If a good product or service is offering you a free plan, more often than not the data you are entering on that platform would be mused for multiple usecases. Not just for your primary use case.
Data aggregation and visualization
This is akin to the marketing function, and most probably gets a lot of early adopters talking good things about the product.
E.g a blogger singing paeans about Google Analytics, an industry benchmark visualization being shared, data report about a competitor, etc.
This way, the inherent value in the data is presented.
Data access and pricing plans
This is how the business is monetizing the data. By selling access to it. Often on a pay per use basis, or a per data point basis. Note, there might be multiple reports given to the user, however the user has to do the analysis on their own.
E.g SEMRush, SimilarWeb, Alexa, etc.
Wait, these are all old products
Yes. They have been around for quite some time. However, I am seeing that other industry are also copying this model. I recently spoke to someone in the pharma industry who was selling aggregated prescription data to pharma companies.
The credit industry has already been doing this for so many years. TransUnion is a perfect example. In India, most working professionals are familiary with their CIBIL scores. What few people realize that CIBIL is a TransUnion company. Similarily, CRIF score (which is an alternative bureau) belongs to Experian.
What gets my goat in this scenario, is that the firm which is collecting data is based out of another country! This firm now claims to own and know the data of citizens belonging to another country.
Shut up and take my data
Let’s go back 300 years or so. The British killed the Indian textile industry by mutilating the weavers who used to make cloth. Then they bought the cotton and other crops at throwaway prices, that cotton is similar to the data that is being collected. The industry grade cotton which was then imported back in India is similar to the data aggregation and reports that are being sold.
The only difference is that 300 years back, we were scared of the East India Company. This time around, we are welcoming the data traders with open arms. Should we not be a bit more aware of who and how our data is being used?