Yes. Let me start with Canada, because it's pretty simple, and then I'm happy to describe what we do in the U.S., which is far more complex.
In Canada, we match name and address and telephone number, because these are telephone directory listings and we have a phone number for every record.
We append census data to that based on geography.
We would take your census file, which is at a geographic level, and then we would append census characteristics to the individual record. If someone were using it for direct marketing purposes or telemarketing purposes, they would have more information about the individual than just their name, address, and phone number. That's a fairly simple process.
In the U.S. and in other countries, we will match names and addresses. We will match telephone numbers when we have them. When we're not dealing with directories exclusively, we may have records that do not have a telephone number on them.
We would use the highest, most accurate information we have available in the record. Part of our matching algorithm—I think it's something that any good data company that collects and assimilates data from multiple sources needs to do—is to have quality standards related to the data integration or data matching.
For instance, take an initial; my name might come in from one source as “J.” Glasgow, or it might come in as “Jennifer” Glasgow. If I lived in an apartment building, I might have the street address but be missing the apartment in one record. We would go through a data hygiene process to try to standardize and clean up, to the degree we can, any inconsistencies in the address or misspellings of maybe street names or other things like that. Then we would match records together to try to determine if we have information about the same person or household from multiple sources that could be integrated together to build a composite of information.
That's how we get, as the earlier member discussed, up to 1,500 different data elements on one individual and household.