Gizmodo identified 32 brokers selling data on 2.9 billion profiles of U.S. residents pegged as “actively pregnant” or “shopping for maternity products.” “A Gizmodo investigation into some of the nation’s biggest data brokers found more than two dozen promoting access to datasets containing digital information on millions of pregnant and potentially pregnant people across the country. At least one of those companies also offered a large catalogue of people who were using the same sorts of birth control that’s being targeted by more restrictive states right now. In total, Gizmodo identified 32 different brokers across the U.S. selling access to the unique mobile IDs from some 2.9 billion profiles of people pegged as “actively pregnant” or “shopping for maternity products.” Also on the market: data on 478 million customer profiles labeled “interested in pregnancy” or “intending to become pregnant.” You can see the full list of companies for yourself here. In all cases, these datasets were sold on what’s known as a “CPM” or “cost per mille” basis—which essentially means that whoever buys them only pays for the number of end-users that are reached with a given ad. Depending on who was offering up a dataset, the price per user ranged from 49 cents per user reached to a whopping $2.25. The datasets offer information on some 3.4 billion people in total, though how many unique individuals those data cover is unclear, as the datasets obviously overlap. Multiple brokers are likely hawking the same information, as half the world does not live in the United States, and half the world is not pregnant. Their sources do differ, however. Some brokers were gleaning this information directly from pregnant people who had agreed to have their data shared through these channels when they signed up for coupon sites or downloaded a given app. In other cases, these companies were doing exactly what Target had done all those years before: instead of collecting data from end-users that were explicitly saying they’re pregnant, the brokers instead modeled a core base of potentially pregnant users with internal data analysis…”