As we discussed previously, there are many classifications of data that are commonly used in this industry. We previously gave a broad overview of all the major types: Public, Consumer, and Regulated. In this article, we’ll be exploring the world of Consumer Data in greater depth.
As we discussed before, Consumer data is defined by the way it’s gathered and how it’s used. Consumer data is usually gathered from subscription services, retailers, surveys, and other consumer behavior tracking services. The data is gathered with the consumer’s consent and sold in bulk to an aggregator who compiles a database from multiple sources. Have you ever clicked, “I agree” at the end of a long Terms of Service agreement? You may have just agreed to share your information with a company that’s looking to aggregate and sell your data.
Once the data has been aggregated (collected from multiple retailers, subscription services, surveys, etc.) it is put into a single database which a marketer can use to locate potential customers.
These consumer marketing databases have basic personal information (like name, DOB, address, and phone number), demographic information (gender, ethnicity, number/age ranges of children, household income, and home value), property information (square footage, number of bathrooms/bedrooms, rent vs own, mortgage lender and amount, gas vs electric heating, etc.), and fields labeled “lifestyles, likes, and interests.” The lifestyles, likes, and interests give the marketers information about the consumer’s buying habits, hobbies, reading habits, and even what kind of credit cards they have.
All of this information can be used by marketers to target a very specific demographic of customer. For example, if you own a women’s sporting goods store, you may want to send advertisements to women and married men who are interested in fitness, golf, football, and soccer. But because your store sells higher end equipment and only in central Ohio (go bucks!), you may want to focus on Ohioans whose household income is over $250,000 per year and have at least two credit cards.
It’s important to note that not all the information in these databases is collected directly from the consumer. Some of the data is “inferred” information – that is information that you never shared but the aggregator and retailers were able to figure out based upon other factors in your profile. For example, if you shop at a large toy store chain, they may track the age groups associated with the toys you buy. They do not know for certain that you have a 3-year-old at home, but based upon the number of Peppa Pig products you’ve bought in the last few months, they’ve got a pretty good idea.
At martin data, we work directly with some of the industry’s best consumer marketing experts. Feel free to reach out to one of our sales associates for more info!
