Last year I worked with a large company that provided data to the healthcare space, primarily pharma, which is commonly referred to as real world data (RWD) and consists of patient clinical and claims data. What I found is that this solution is either sold by the Therapeutic Area (TA) or is custom-priced by project.
I found TA as a price metric to be problematic because it did not align well with value. Not all TA’s had the same potential commercial value for example. Nor were TA’s from competing variables directly comparable in terms of data depth and quality.
So my question is: what would be a better price metric?
I am pretty sure you did a formal value model for this, were there variables in the value model that could be used as pricing metrics? Or is there some way of bridging from the variables in the value model to variables that could be used in the pricing model?
In regard to the use of Therapeutic Area, this is kind of like a market segment isn’t it? So the principles used for pricing for segments could be applied here.
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Would be curious what the value model revealed.
Data is tricky. I feel like the easiest axes for monetization are volume, depth, or time (e.g., real time vs delayed).
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If the product team is set on selling as a TA solution rather than a DaaS model where as the data is the commodity then you will have to succumb that each client will be custom priced. For me, TA’s are a solution based product. It sounds like a segmentation solution is needed to divvy up the TA’s to a higher degree. In my experience RWD is priced by the data type rather than the TA.
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Chris,
More context: It is a DaaS model. However, top 20 customers often buy a “pan-therapeutic” license, i.e. for everything - and although there is a list price for this, it is heavily negotiated.
The issue comes when other customers want to buy a slice of data - and that slice often corresponds to one or more TAs. From what I understand, no two TAs slices are exactly the same because there are filters for different criteria, like demographics and amount of data. So as you would expect, those prices vary quite a bit.
We hired a competitive research firm and they gave us fair market pricing benchmarks per TA. I should point out this is for structured data. Unstructured data is true differentiator and we were able to recommend value pricing for that.