Digital How-to

Digital Marketing Guide: How Do You Slice and Dice Your Target Audience When Buying an Ad?

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Kathryn Koegel
Kathryn Koegel

How do you slice and dice your target audience when buying an ad?

You can buy online audiences based on familiar demo targets you might have used in other media: men 18 to 34, women 25 to 54, etc. You can also buy by product intent, which is especially effective online, where people go to research a significant purchase -- for example, when cellphone companies buy cellphone intenders (people who have looked at cellphone-related content online) or auto companies buy auto intenders who've checked out car-review sites.

You can buy audience-targeting inventory from ad networks, exchanges and digital-service providers -- some of them do the data modeling themselves or use the services of companies such as Blue Kai and eXelate.

Can I just target by audience without regard to the site? Or does context matter?

When you buy by audience-targeted inventory, unless you buy direct from a publisher, you will typically not know in advance what sites the buy will be placed on. Ad networks often use audience targeting to get more value out of midtier sites (sites in the ComScore 250 or above). If a network has inventory from top 100 properties, it is typically sold "blind," as that site does not want any confusion with its own sales efforts.

If you want to know the sites that ads are placed on, but want to buy audiences, top sites typically use audience targeting to extend the value of their non-contextual inventory. An example: Big newspapers often sell out of content areas like finance and their home pages, while they have plenty of inventory left in hard news. The value of those impressions goes up if they can associate demography to it or some sort of recent product intent.

Context does matter, as any advertiser will tell you. If a person is engaged with the content (rather than merely clicking through), it typically has a positive impact on the advertising in terms of both association with the content name (I saw that ad on The Wall Street Journal!) and the mere fact that the ad stays up there long enough to get noticed.

Contextual inventory on name sites has the highest value of any inventory online, with audience-targeted inventory falling somewhere in the middle in terms of both cost and effectiveness, followed by run of network or untargeted inventory. (Note: Be wary of what I call the false context of "content farms." There are entire entities set up to spawn low-value content that is optimized for search engines. This content is written to answer simple questions for commonly searched terms and hot news topics and was developed purely as a platform for the advertising -- not to meet any information need.)

Everyone says they can sell audiences. How do I know who's legit and who's a snake-oil salesman?

As much as we want to believe that technology solves all, in the world of online inventory, a lot of it comes down to trust and personal relationships with sales reps. Some advertisers use tools such as AdSafe and DoubleVerify to determine whether placements for impressions bought through networks are delivered into appropriate sites. When I was working on an October Ad Age report that covered the topic, most agency personnel interviewed said it was a test-and-learn process. If they were sold garbage once, they never went back. That report has a checklist in it of questions to ask before working with audience sellers.

How do I know that my ad is reaching the right people?

Since so much inventory online is sold on a DR basis (even brand marketers run campaigns to drive to their branded sites, download coupons, etc.), if the campaign delivered the view-throughs, click-throughs and conversions desired, then it worked regardless of who those people were.

But for campaigns that are truly branding and aren't seeking some kind of a direct action associated to the impression, you can run various diagnostics, such as ComScore's Campaign Essentials product, which uses a match-back system. In tests they have done for agencies, they have examples of inaccuracy in female targets due to issues such as computers with multiple users or flawed registration data used from false ages submitted (teens lie to get access to various types of content and use their parents' birth dates. What a shocker!). Some of these campaign tests showed more than 40% of impressions falling outside the target audience.

How do I know it's a real person I'm targeting and not a computer?

Remember that New Yorker cartoon of the dog surfing the web, captioned, "On the internet, no one knows you're a dog"? The same is true for online dating and audience targeting. The data are based on cookies -- software tags -- placed on a computer browser. Each cookie is supposed to represent a person, but it could be three (there are 4-foot-tall humans in my household who use my work computer to go on sites such as Amazon, Lego.com and AmericanGirl.com and pick up all manner of cookies there). I am also counted as three people, though I can attest to the fact that I do not have three heads: I use two computers plus the browser on my phone. The incidence of over counting from cookies is getting worse due to the multiplicity of devices connected to the internet. IPads probably take this to a new level: How many people have touched your "tab"?

What does retargeting mean?

Retargeting means you're using cookies to send targeted ads to someone who previously displayed some kind of intent. For example, I almost purchased new ski jackets for Christmas from Campmor and also looked at them on Lands' End and The North Face. Magically, I have been getting ads on just about every site I frequent tempting me with ads for Campmor's end-of-season sale. Privacy advocates tend to find this creepy. For me, it's a decent deal and a good example of reaching a person with relevant advertising, but I did wish that Campmor capped its frequency a bit sooner. I couldn't take a full 30 days of seeing those ads.

What about people who opt out of targeting? Can I still reach them?

People who block third-party cookies (ad-network cookies) are still reached, you just don't collect any attributes about them.

What if someone has installed an ad blocker -- am I still paying for that impression?

If someone has installed an ad blocker, they are not getting an ad and you are not paying for that person. If someone has blocked third-party cookies, they still get an ad, it just doesn't transmit any information back -- but you pay for it. For a very articulate defense of why people should not block ads or cookies, go to the website ArsTechnica.com, which is the thoughtful IT person's guide to the universe. ArsTechnica did a test to see how many of their users were blocking ads and found that 40% of its very tech-savvy audience was doing so. (It then pointed out the connection between the delivery of the content and the advertising. The less revenue sites make online, the fewer journalists who can make a living doing this.

How does online ad targeting compare to targeting in other media?

I've worked in the big three of media (TV, print, online) and all have problems with overpromising. There is no ad-targeting perfection in any media -- all research has its flaws. Magazines are bought based on a sample of people recognizing logos of the magazines (which constitutes readership). TV is based on a sample of households and average commercial minute, but not the actual ratings of the commercial. The internet does give you data on actual delivery of the ad, but not the placement. Audience buying makes it easier for mass brands to achieve reach and price efficiency online and is delivering value to those who use it well.

What's more important than picking apart online methodology is the evolution of TV ratings and projects underway to get closer to some kind of cross-media measurement standards. The big push now is extending TV-audience measurement into video consumed on other devices. We'll actually know about reach of that ad beyond the box, and at the same time agencies will be penalized for making terrible commercials and rewarded for the good. What a game-changer that will be.

ABOUT THE AUTHOR
Kathryn Koegel is chief of insights at Primary Impact and author of five Ad Age Insight Reports on mobile marketing in 2011, including one on location-based services, out today, and the 2011 edition of "Benchmarks and Best Practices for Mobile Marketing," out March 7.
Kathryn Koegel is chief of insights at Primary Impact and author of five Ad Age Insight Reports on mobile marketing in 2011, including one on location-based services, out today, and the 2011 edition of "Benchmarks and Best Practices for Mobile Marketing," out March 7.

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