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Three Effective Tactics for Content Targeting

  |  May 21, 2010   |  Comments

In today's paid search environment, there's a myth that content targeting doesn't convert measurably for advertisers. Let's dispel that myth.

I admit it. Along with about 90 percent of AdWords advertisers, I was once a card-carrying member of the "Content Targeting is Scary, Kind of Like a Toyota, Club." At SES New York one year, using the best analogy any boy can come up with (a car analogy, in other words) to describe the quality of the semantic matching and feature set in content targeting, I showed a photo of a 1978 Ford Pinto. It was, to paraphrase Ralph Nader, unsafe at any speed. You could blow through a wad of cash with nothing to show for it. It's not exactly fun to watch a carefully built, profitable campaign dive into the red in a short period of time, which was common when lower-quality placements were rampant.

But times have changed. Perhaps content targeting may never be a Maserati, but perhaps we don't want that. Instead, we're looking for something more along the lines of the Arlanda Express train in Stockholm.

In this column, I'll dispel the myth that content targeting doesn't convert measurably for advertisers. I'll also address three effective content targeting tactics that work well in today's paid search environment.

Let's start with some background on content targeting, which is now formally called "placements" by Google in the ever-shifting vocabulary of digital advertising. Content targeting is the term that has often been used for text or display ads triggered by relevant keywords chosen by advertisers, matched with content pages around the Web (in Google's case, with publishers participating in the AdSense program). Now, there are multiple "flavors" of "placements" in the Google AdWords platform; the other main flavor is "managed placements," where you directly choose the sites your ads are eligible to show up on. As with the search advertising platform, the ad-serving mechanism is algorithmic and auction-based.

Google's Data Revisited

In 2008, Google produced a white paper reviewing a huge number of accounts, showing that costs per acquisition from content targeting were in the same ballpark as for search. In spite of that, quite a few advertisers are unlikely to believe the findings apply to their business. Some commenters on the forums dismissed the results in spite of the huge data set they're based on.

Certainly, it's possible that one might not see the same results for the business that matters: one's own. That's possible for a number of reasons. The question that must be asked is: are disparities in results caused by poor optimization and a failure to adopt key techniques in using the content targeting program, or are they a result of specialized business models "behaving badly," or at least not behaving like the mass of typical accounts under study?

In my view, it's primarily the former. There's no question that accounts need care, feeding, and specialized knowledge. Some business models are more challenging, but it's a mistake to think that Google's data, or your neighbor's data, are somehow skewed. Only in rare cases is your business so exceptional as to be totally unlike the other businesses making use of AdWords.

To convince myself of that, I went through a selection of randomly-selected accounts at my agency's portfolio. (I blogged the data here.) The CPA (cost per acquisition) figures are sometimes better and sometimes worse than they are for search. However, we very rarely encountered CPA's that went so far through the roof - for instance, paying a CPA of $490 to acquire a customer buying a $100 sweater at a 20 percent profit - that we couldn't make good use of the content targeting program. It was that kind of performance that left a bad taste in many advertisers' mouths back in the Ford Pinto era." For some sizeable businesses, content accounted for over 30 percent of the sales and lead volume, at a comparable CPA. And yet some companies still keep this channel turned off entirely based on past experiences, slow initial performance, or unfamiliarity with its mechanics.

It's time to revisit key tactics that are working today, apparently much better than they did in the past.

  1. Handy on-the-fly management: Performance stats are now easily accessed under the Networks tab. The beauty of the new Google AdWords interface is that you can address performance by ad group if you like, or really save time by checking out, say, a 90-day date range across a whole campaign or even the entire account. Sort by cost or click volume, and cut right to the chase. If a source publisher doesn't look right, you can exclude it, or pull it out into managed placements and bid it down. Another exhilarating tactic is to identify your winners, pull them out into managed placements, and bid them up. This is a lot easier to accomplish than ever before.
  2. Specialized ad group structures: Because the legacy of AdWords was to tack content targeting's functionality onto the existing keyword list of your ad group (the one initially and primarily designed to target people searching on Google Search and partner search engines), past targeting methods tended to be imprecise. For many businesses, the automatic matching technology works better with a tight, small ad group comprised of niche terminology that doesn't cast too wide a net, and only contains a short list of five to 10 phrases. In building separate ad groups for content using this technique, now your targeting methodology focuses on the positive impact of precise meanings and keywords, as opposed to the defensive methodology of low bidding or pausing targeting efforts that were inherently too diffuse. True, such tight ad groups may not generate much volume. So you might need to build 25, 50, or 100 of them. It's not for everyone, but it's working. Based on such a structure, you can also do a much better job of tweaking based on performance data.
  3. Make use of view-through conversions data: In addition to last click attribution, AdWords now reports whether a display (content) ad led to a conversion indirectly. Especially if you're experimenting with display ads to raise awareness, you can factor view-through conversions into your decision as to whether or not to keep some content targeting experiments running. You can also factor this intelligence into what you're prepared to bid.

In future columns, I'll explore the pros and cons of the automatic matching and managed placements flavors of content targeting; why there are more "winning" fits between publishers and advertisers today; and the state of demographic and behavioral targeting. Good luck!

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ABOUT THE AUTHOR

Andrew Goodman

Goodman is founder and President of Toronto-based Page Zero Media, a full-service marketing agency founded in 2000. Page Zero focuses on paid search campaigns as well as a variety of custom digital marketing programs. Clients include Direct Energy, Canon, MIT, BLR, and a host of others. He is also co-founder of Traffick.com, an award-winning industry commentary site; author of Winning Results with Google AdWords (McGraw-Hill, 2nd ed., 2008); and frequently quoted in the business press. In recent years he has acted as program chair for the SES Toronto conference and all told, has spoken or moderated at countless SES events since 2002. His spare time eccentricities include rollerblading without kneepads and naming his Japanese maples. Also in his spare time, he co-founded HomeStars, a consumer review site with aspirations to become "the TripAdvisor for home improvement." He lives in Toronto with his wife Carolyn.

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