Zillow thought they already had enough data and accurate enough models to buy and sell houses profitably. The last two quarters proved they didn’t. In the first quarter they were puzzled by making too much money and in the second they lost a whole bunch

The author is arguing that they should have pivoted from “we already have models” to “we’re intentionally gambling hundreds of millions of dollars so we can build good models over the next few years”. That might be a good strategy for a startup with loads of VC money and no other products, but it makes less sense for a more established company to risk going under on that bet

Their methodology might have been flawed. The author is speculating.

He uses Zillow to explain how datasets – especially the ones with money tied-in – can’t be trusted blindly. Building a high-quality dataset is an expensive endeavour.