By Brett Konen on April 8th, 2020
The key to avoiding wasted ad spend? Audience targeting. If you’re not using these data-based tactics to reach the best possible audience for your ads, you’re throwing away a portion of your ad budget—maybe even most of it.
The good news is that audience targeting isn’t rocket science—it isn’t even an art form. It’s a simple, data-driven method of increasing ads’ likelihood of conversion by showing them to the right people. Here’s how it’s done, why it works, and how to use it in your own ad campaigns.
What Is Audience Targeting & Why Should You Use It?
Audience targeting is a technique used by digital marketers to ensure that their ads are shown only to the people most likely to want what they’re selling. It’s accomplished by using available data on individual characteristics, interests, and behaviors to select (or “target”) the viewers who will see a specific ad campaign.
As a programmatic ad agency, we often have customers who come to us thinking they know their target audience. In general, the people who actually end up purchasing their products are completely different. Audience targeting ensures that we don’t waste money on advertising to the wrong people. This extends campaign budgets and improves conversion rates for digital ads. Additional benefits include the ability to cater your messaging to different audience segments or stages of the buying funnel, which will also increase the likelihood of conversion.
There are three key elements of audience targeting.
Demographic audience targeting
This type of targeting hinges on demographic data, such as age, gender, education level, income bracket, race, marital status, and occupation. If you wanted to show your e-commerce site to women over age 50 who make $100,000 or more a year and have a college education or higher, you would use demographic targeting.
Psychographic audience targeting
Psychographic or interest targeting selects ad audiences based on their interests, activities, opinions, values, personality traits, or lifestyle choices. Showing ads to people who commute by bike would be a form of psychographic targeting.
Behavioral audience targeting
Behavioral targeting uses data on an audience’s digitally “observed” behaviors, such as websites they’ve visited, other ads they’ve clicked on, or items they’ve purchased in the past. To show ads for an organic skincare line to people who’ve bought other organic products, you would use behavioral targeting.
The categories above can be used on their own to address broad audiences or combined in order to create more narrowly defined segments.
Using Data to Find Your Target Audience
So, where does all this audience targeting data come from? And how can you start using it to improve your own ad campaigns?
There are three types of data sets you can use for audience targeting: first-party, second-party, and third-party data. Each type has its own benefits and drawbacks.
First-party data is data your brand has collected itself. This can include information on past customers; contacts, leads, and prospects; social media followers; email newsletter subscribers; or website visitors on desktop or mobile. Some of this data is readily available—for instance, in your POS or CRM. In other cases, you may need to take additional steps to collect the data—to track web visitors, for instance, you’d need to enable a tracking pixel on specific pages of your website.
First-party data is generally the first line of data used for audience targeting. This is true for a few reasons:
- It’s unique to your company, meaning others can’t market to these same segments unless you let them.
- You don’t have to purchase it.
- It’s generally more accurate than third-party data.
- First-party audiences have already shown interest in your brand, meaning these are people with a high likelihood of conversion.
That said, first-party data sets are often relatively small, and they don’t allow you to grow beyond your existing audience. For these purposes, you need second- or third-party data.
Second-party data is someone else’s first-party data. It may be given to you by a contact in the industry, shared through a partnership, or bought through a data exchange.
Second-party data is used less often than first- and third-party data, but it can be a good way to broaden your audience while still maintaining data set quality and exclusivity. It may also be cheaper than third-party data depending on the sharing agreement and amount of data you’re looking for.
Third-party data is collected, segmented, and sold by data providers. These data sets may be bought through public data exchanges, demand-side platforms (DSPs), or data management platforms (DMPs).
Third-party data is best used for rapidly scaling an advertising campaign. Though it may not be as targeted as first- or second-party data, third-party data allows you to find and reach whole new groups that go far beyond what your first-party data would allow on its own.
How to Apply Audience Data to Your Digital Ad Campaigns
To use audience targeting in your own ad campaigns, you’ll first want to broaden your target audience using a combination of the options explained above.
See also: How a Programmatic Ad Campaign Is Optimized & Measured
Then, when your campaign has launched, you’ll want to adjust its parameters using your campaign KPIs to concentrate your budget on the portions of your audience with the highest conversion rates. This process is called optimization.
Where to use audience targeting
Audience targeting can be used across all modern digital ad platforms, including programmatic (e.g. The Trade Desk ), paid search (e.g. Google Ads), and paid social (e.g. Facebook, Instagram, Twitter, and LinkedIn). Programmatic ads can be served to your target audience across all channels, including display, mobile, video, connected TV/OTT, native, and digital audio ads.
Google, Facebook, Instagram, Twitter, and LinkedIn all have relatively simple interfaces to let you select the audience attributes you’d like to target, and can easily be managed in-house or through a digital ad agency.
With more robust programmatic ad tech platforms like The Trade Desk , you’ll be choosing from a far wider selection of data, and you may be faced with selecting from several data sets that seem to target the same attributes. In these cases, it helps to have a feel for which providers offer the highest-quality data. If you work with a dedicated programmatic ad agency, your campaign manager will be well-versed in different providers and the quality of their data.
Combining data sets to build custom audiences
The most effective audience targeting efforts use first-party data together with second-party or third-party data (and sometimes both) in order to reach a wider variety of potential new customers.
If your first-party data showed that your audience was primarily Millennial males with an interest in extreme sports, for instance, a third-party data set might also let you reach all young men in the U.S. with a known affinity for Red Bull videos.
What are lookalike audiences?
Combining first-party data with second- or third-party data is also how advertisers build “lookalike” or “act-alike” audiences. This process involves matching characteristics of your first-party data with the same characteristics in third-party data to identify prospective customers most similar to your existing ones.
If you have enough first-party data, you can maximize chances of conversion by building look-alike audiences from people who have moved furthest down your sales funnel (e.g. building a lookalike audience from your most frequent purchasers, rather than people who simply viewed a product page).
Other Targeting Tactics to Combine With Audience Targeting
There are many different ways to target an ad campaign, but for most campaigns, audience targeting is the best place to start to avoid wasted ad impressions. Once you’ve determined your target audience, you can incorporate any or all of the following tactics to further improve your campaign.
Contextual targeting involves selecting the context in which viewers should be shown a given ad. This may mean choosing the type of content an ad should accompany (e.g. recipes), the topics or keywords it’s most relevant to (e.g. home cooking), specific websites where it should appear (e.g. BonAppetit.com), or an app it should be shown in (e.g. the AllRecipes app).
Geofencing & geotargeting
Geofencing uses GPS and IP address data to show ads to people who visit, have visited, are near, or live near a particular location. By drawing a virtual geofence around a location, ads will be served to anyone browsing the web via desktop or mobile in that area. Geofencing may be useful to target specific neighborhoods, businesses, or events.
Geotargeting also uses location-based data, but involves targeting specific populations within a given area. An example of geotargeting would be showing an ad to moms living in a certain zip code.
Retargeting uses data on people who have already visited your website, been added to your POS, engaged with your ads, or taken some other relevant action. With this data, you can choose to show either the same ad or a new ad to that same person in hopes of securing a conversion by repetition, a special offer, or improved messaging. Retargeting may take the form of cross-device targeting, such as showing a mobile ad to someone who has already engaged with your display ads via desktop.
Regardless of how you choose to leverage the techniques listed above, a targeted ad campaign will virtually always perform better than an untargeted campaign. Which targeting tactics do you use, and which have you found to be most effective? Share your insights below, or get a free professional opinion on them here .
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