[AUDIO VERSION: I also recorded an audio version of this blog post. Click below to listen. Let me know if this is something you find helpful!]
Last week, I wrote about how you could use the “More Demographics” drop-down to target Facebook users based on the following categories:
- Ethnic Affinity
- Politics (US)
- Life Events
The options here are far more powerful than they once were. I encourage you to poke around and discover how precise this new targeting is.
Today, however, I want to start digging into how you can target Facebook users based on actual behaviors. The amount of targetable behaviors available is in the hundreds, so I won’t cover all of them today. But I want to be sure you have a solid understanding of what is possible.
[Note: Some of this may not yet be available to advertisers outside of the US.]
[Tweet “How to target Facebook users by behavior like purchases, car owned, charitable donations and more…”]
The Basics: How to Target By Behavior
Whether you create your ads in Power Editor or the ad create tool (I recommend Power Editor), advertisers will see the “Behaviors” drop-down in audience targeting.
Following are the categories of behaviors that can be targeted:
- Automotive (DLX Auto Powered by Polk)
- Charitable Donations
- Digital Activities
- Mobile Device User
- Purchase Behavior
- Residential Profiles
Click around and you’ll see just how targeted you can get based on behaviors…
Once the Automotive category is clicked, you’ll be shown the following sub-categories:
- New Vehicle Buyers (Near Market)
- New Vehicle Shoppers (In Market)
- Purchase Type
- Used Vehicle Buyers (In Market)
When those sub-categories are clicked, even more sub-categories are exposed.
The amount of targeting you can do based on the type of vehicle someone owns or leases is incredible. As a result, a separate blog post to cover this topic was needed (read it here!).
This information is pulled from Partner Categories. Datalogix, a data mining partner, collects this information when large purchases are made and reports it to Facebook to be used in ad targeting. More will be discussed on this later!
If you were to click the Charitable Donations category, you’ll be shown the following sub-categories:
- All Charitable Donations
- Animal Welfare
- Arts and Cultural
- Children’s Interests
- Environmental and Wildlife
- World Relief
If you were to select “Animal Welfare,” for example, you could target all Facebook users who have self-reported that they donate to animal welfare-related charities. This could be incredibly useful targeting for non-profits looking to reach potential donors who have given to a similar cause in the past.
This data is pulled from data mining partners Epsilon and Acxiom, formerly found within Partner Categories. In most cases, it’s consumer self-reported data from surveys and donations.
If you click on the Digital Activities category, the following sub-categories are revealed:
- Console Gamers
- Event Creators
- Online Spenders
- Online Spenders (Active)
- Online Spenders (Engaged)
- Photo Uploaders
- Small Business Owners
- Technology Early Adopters
- Technology Late Adopters
All of this data is pulled from activities performed on Facebook.
When you click on Financial, the following three sub-categories appear:
- Spending Methods
Each sub-category has more data buried within it…
- Auto Insurance (target by policy renewal month)
- Health Insurance (likely no dependents or likely to have dental insurance)
- Home Insurance (target by policy expiration month)
- Life Insurance Owners
Some of this is self-reported to data partner Acxiom and the Home Insurance info is publicly available.
- Highly Likely Investors
- Likely Full-Service Investors
- Likely Investors
- Likely Self-Directed Investors
This is pulled from Acxiom using a couple of different models, per Facebook…
Modeled based on investment interests, and a variety of additional demographic data and census median data
Modeled using MRI and built from a blend of public, self-reported, buying activity, and census/geo data
- Active Credit Card User
- Any Card Type
- Bank Cards
- Gas, Department and Retail Store Cards
- High-End Department Store Cards
- Premium Credit Cards
- Primarily Cash
- Primarily Credit Cards
- Travel and Entertainment Cards
This data comes from data partner Acxiom in a number of ways:
- Self-reported purchase activity
- Self-reported consumer information from surveys
- Modeled based on property data, investment interests, buying activity, occupation and census median data
You’ll recall that there was also a Financial section within the “More Demographics” targeting. In that case, however, we were targeting based on annual income and net worth.
Mobile Device User
The following options for Mobile Device User are available:
- All Mobile Devices by Brand (target by model owned)
- All Mobile Devices by Operating System (target by specific OS)
- All Mobile Devices
- Feature Phones
- New Smartphone and Tablet Owners
- Smartphones and Tablets
Facebook has this information based on how users access their platform.
Note that you can also target mobile devices within the Creative step of ad creation…
The difference is that with Behavioral targeting, you can target users who own a particular device but who aren’t necessarily on it at the time. With the second example above, you are only targeting users who are using that type of device when targeted.
When the Purchase Behavior category is clicked, a whole world of options is opened up to you…
- Business Purchases
- Buyer Profiles
- Food and Drink
- Health and Beauty
- Home and Garden
- Household Products
- Kids Products
- Pet Products
- Purchase Habits
- Purchase Types
- Sports and Outdoors
- Store Types
- Subscription Services
As was the case with the Automotive category, Purchase Behavior requires a blog post of its own. The possibilities are practically endless!
This data is provided by Epsilon and Datalogix based on actual purchases made.
Click on the Residential Profiles category for the following options:
- Likely to Move
- Recent Homebuyer
- Recent Mortgage Borrower
- Recently Moved
The Recent Homebuyer and Recent Mortgage Borrower data is pulled from publicly available and self-reported information. The Likely to Move data comes from Epsilon and Recently Moved from Acxiom.
And finally, that takes us to the Travel category. Following are the ways you can target people based on where they go…
- All Travelers
- Business Travelers
- Business Travelers (International)
- Business Travelers (US)
- Casino Vacations
- Currently Traveling
- Family Vacations
- Frequent Flyers
- Leisure Travelers
- Personal Travelers (International)
- Personal Travelers (US)
- Planning to Travel (Returned from trip recently, use timeshares, used travel app recently)
Some of this data is available based on information users share on Facebook and travel apps used. The rest of it comes from Datalogix.
Here are a couple of examples of how that data is collected and then users are targeted, per Facebook:
Collected from U.S. Census, warranty cards, registration information, the Department of Motor Vehicles, public record information, survey data, and other offline sources. Data must be validated by at least two sources to be included.
U.S consumer data on where consumers shop, how they shop, what products and brands they purchase, the publications they read, and their demographic and psychographic attributes.
Where Does Facebook Get This Data?
The same rules apply here that applied to the More Demographics targeting.
It will undoubtedly sound creepy to some that you can target based on some of this information. But if you get past the creepiness, this data can be used to generate incredibly relevant — and useful — advertising.
Demographic targeting is based on data from one of two sources:
- Information users provide to Facebook
- Information mined by data partners
The first is easy to explain. Facebook knows a lot about you based on your activities through their platform.
The second has actually been around for more than a year in the US via Partner Categories, but some of this targeting has been moved to the More Demograhpics and Behaviors areas.
Facebook partnered with data mining companies to collect additional information on users for targeting purposes. Whenever you fill out an application or survey or make a large purchase, data mining companies often get access to this information.
As always, advertisers have no access to the names associated with this data. For more on how this data is used, make sure you read this message from Facebook.
How Can Advertisers Use This Data?
All kinds of possibilities! Here are a few ideas…
Automotive: A Toyota dealership targets Facebook users within 25 miles who own a Toyota Corolla that is 4-5 years old. They can even feature a picture of the new model, and direct users to a landing page to set up a test drive.
Charitable Donations: A Democratic political candidate running for office can target Democrats within the area.
Digital Activities: A B2B company with a product that helps small businesses can target those who have reported themselves as small business owners.
Financial: An auto insurance company can advertise their rates to Facebook users in the area whose policies are set to expire.
Mobile Device User: An iPhone app creator can promote an informational ad to iPhone users while not on their iPhone, then target those same users with an install ad when on their devices.
Purchase Behavior: A Pet store can target dog owners with coupons that will be relevant to them.
Residential Profiles: A mortgage broker or real estate agent could target Facebook users who are “likely to move.”
Travel: A travel company specializing in cruises can target Facebook users who are known to take cruises.
Have you started using this information in your targeting? What have you done, or what ideas do you have?
Let me know in the comments below!