Just like everything else you buy, data-based products (such as segments, attribution models, targeted media campaigns, or PMPs) don’t just suddenly show up on the shelf at the store. Getting there is a complicated process. But, if you know how it works and what bumps and pitfalls to look out for, you can get the quality you need.

Using the creation of a segment as an example, Jake Moskowitz from the Emodo Institute explains each of the seven steps in the process and shows you how to tell if companies are being responsible with the data that goes into their products.

Step 1: Occur

A data point starts as a moment of occurrence or creation, for example, when a device is seen inside a brick-and-mortar store. But before you can trust that this data point is correct — that this person was truly in a specific store — you need to understand its potential imperfections. For instance, the GPS might not be accurate, like in a mini-mall where stores are incredibly close together. Or, since phones are not tracking users every second, they could walk into a different store or drive away, and the last known location would be wrong.

Step 2: Categorize

The data occurrence that’s collected is raw and doesn’t mean much until it’s categorized. For the occurrence in the brick-and-mortar store, the data point would be lat/long, not the actual name of the store. One must know which store corresponds to a particular lat/long. So. it’s equally important to verify the quality and accurac