The right Ad, to the right person, at the right time.

The right Ad can also be restated as “the right message.”

The right message, to the right person, at the right time.

If you’ve been around marketing for a minute, then you’ve likely heard this cliche before. But if you’ve been around marketing for a minute, then you also know the most important pillar in this triad is: the right person.

Audience targeting is job 1.

Job 2 is the value proposition; what Rosser Reeves called a unique selling proposition. Does the offer have a “USP”? aka, a differentiator.

For this article, we’ll focus on “the right person” pillar. Data targeting.

If you’re trying to sell high-end homes, behavioral data alone won’t cut it because there’s only a small percentage of people that can afford this price point. So demographic wealth targeting becomes a key first ingredient in any attempt to create a behavioral look-alike audience (more on that in a future article).

Pyramid of Priority

There’s a pecking order when it comes to data:

Intent

Behavior

Interests

Demographics

Offline (Sales data)

Intent

At the top of the pyramid is intent based data. The best way to understand intent data is Google keywords. When a user goes to Google and types “best real estate brokers near me”, then you can be pretty sure the person is looking to hire a real estate professional. It’s an intentional search by the user.

Behavioral

Behavioral data is right below intent based data. Actually, behavioral data trumps intent data IF you have sufficient conversions to train the pixel. A conversion is a result; an event or trigger. A pixel is a piece of tracking code that is associated with an Ad account. To put it in plain english, if your campaign is generating a sufficient number of leads (or other key performance indicator), then the platform’s algorithm (eg. Facebook’s algorithm) will have ample conversion events to model so it can bring precision to your campaign—Facebook’s machine is smart enough to learn and find similar consumers that are exhibiting the same behavior as your recent conversions. So you don’t have to wait for intent based users to search and find you… you can literally reach them instead. There’s a name for this: it’s called People Based Marketing.

In the B2B world, it’s called Account Based Marketing. Either way, it’s based on behavioral data. Harnessing behavioral data is for A-players. It’s a way to target people who are showing intent… but without having to bid in Google for it. In effect, targeting behavior is a form of prediction. If this is your first time hearing about this, then you better keep up. Because this is where the heavy hitters play. This is the secret sauce over at Facebook, Google, Amazon and Apple. Their competitive edge is (a) behavioral data and (b) identity resolution. The only problem is, they don’t share it. They are walled-gardens.

Interests

Interest targeting can be rather diluted. As an example, users might like a picture of a high end home in Facebook or Instagram. That doesn’t imply that the person is in-market for (or can afford) a luxury home. With that said, there are 3rd party tools that allow you to “layer” multiple interests in Facebook to help get better targeting.

Note: what is layering? For example, let’s say you’re targeting bodybuilders. If someone has an interest in Arnold Schwarzenneger, that might not necessarily imply that they’re into bodybuilding. Since Arnold has been in many movies, the person might be a movie fanatic and have no interest in bodybuilding. But, if you were to layer the Arnold Schwarzenneger interest with Ronnie Coleman interest and with Lee Haney interest, then where those three circles overlap is an audience that most likely matches the people interested in bodybuilding. By layering two or three interests will increase the likelihood that you’re hitting the proper group—in this case, people interested in bodybuilding.

Demographics

When reaching high-end home consumers, this income/net-worth data set is a key piece to the pillar for… “the right person.” 

For high-ticket services and offers, if your initial seed data isn’t geared at high net-worth individuals, then running Ads can be a drain. 

Not only that, the guy or gal who can afford to buy a $35MM luxury home is probably traveling or on the golf course right now. They’re not searching on Google for “best realtor near me.” They might even have a friend to recommend a broker for them. Worse yet, the person that can afford to buy high-end homes may not even be looking to buy yet… but would be interested in buying (or selling) if he or she was presented the proper information.

This is why there’s interruptive advertising. Interruptive advertising is designed to get your message—your value proposition—in front of your target universe ahead of your competitors; and more consistently.

(and then keep those messages in front of them so you can remain top-of-mind)

For high ticket offers, access to this income/net-worth data alone is priceless.

The problem with this data set is (a) Facebook eliminated income and zipcode targeting in what they feel helps prevent discrimination and (b) there’s only about three or four data providers in the USA which have quality high net-worth individual (HNWI) data and (c) this data can get costly if you’re not a data wholesaler.

The other variable to consider is that most/all of this HNWI data is offline. 

Therefore, you need a reliable mechanism to bring this offline data into the online digital ecosystem. With the expectation that you can achieve a high match rate (aka, a quality sync between the people in the file and those same people matched in Facebook and/or LinkedIn). Along with the ability to maintain an up-to-date data sync continuously.

This is where identity resolution in digital marketing comes into play.

Here at HK®, we segment HNWI data audiences into:

• $18MM+ minimum net worth
• $5MM+ minimum net worth
• $500K+/year minimum salary
• HK® behavioral look-alike

The $18MM+ net worth audience is a seed file of roughly 96,000 people; or more appropriately—”households.”

In Facebook, the match back size for this seed audience fluctuates: as of this writing it’s 350,000 Facebook users for those 96,000 USA households.

(see here)

In LinkedIn, that same seed file matches back similarly—360,000.

(see here)

For the $5MM+ net worth audience, the audience fluctuates, with Facebook typically matching back between 5-8 million users.

(see here)

If you were selling luxury property in Chicago for example, you could geo-fence a 15-50 mile radius around a specific address to layer within the Facebook Ad. This would focus the Ad to people in that audience that also reside within that specified radius.

(see here)

If you’re selling South Florida or Southern California property, you might not geo-fence around the property since potential buyers might be from out-of-state colder climates. 

(or you could choose to test multiple audiences in this instance)

What matters most is your starting data. Data is the new oil.

In a future post, I’ll reveal how you can model a behavioral audience from the original high net-worth individual seed file.

For now, if you’re in need of fast and affordable data like this, contact us.

This is ideal for real estate professionals working the high-end home market: $2M+ values.

Here at HK®, we specialize in linking wealthy people audiences with a luxury real estate company’s brand efforts, and for pennies on the dollar.