Net New Data
I joined a customer interview session for one of our portfolio companies today.
I'm looking to move house, and this company is building an AI-native property platform. The session was talking through all the steps I'm going through in the process, and all the considerations running through my mind, with a view to identifying areas where AI could bring additional customer value.
One of the areas that was most appealing to me was the concept of net new data that could potentially be generated and synthesised with AI.
An example would be the potential to extend a three bedroom house to add a fourth bedroom. The data that underpins the extent to which that option is real - for example whether or not similar houses have had planning permission, how much it would cost to do it, how long it would take, and so on - is so scattered across the internet, the chances that I would pull it together myself until I was very serious on a property are effectively zero.
But knowing it in near real-time brings a whole new set of properties into my consideration set. The non-observable attribute of 'plausible extendibility' enriches that listing for buyers like me. In theory, that makes the property more desirable because it has a deeper demand pool than previously thought.
It's this kind of net new data creation that has the potential to be pretty compelling. Particularly in transaction/marketplace contexts, the more information can be uncovered, the better the market accurately prices the asset. Stealing an edge on that information advantages could be a very compelling value seam to go after.