Using segmentation models in search advertising.
If you think of your campaign as one that delivers clicks, you're probably making some mistakes that could cost you revenue and profit. You aren't buying clicks; you're not even buying position. These are just means to an end. You're buying the opportunity to get your message (text ad) in front of people, human beings who've shared something special with Google, Yahoo, Microsoft, or Ask. Each searcher is an individual who volunteers what she's interested in at a specific moment when she clicks that search box.
Though the keyword tells you more about a searcher's immediate needs and interests than could be revealed by anything short of a psychic, each searcher is a person, definable by much more than just that keyword. Microsoft is first among the search engines to provide incremental targeting of searcher segments identified through voluntary user profiles. Profiles aren't an intrusive Big Brother tactic, they're a potential win-win. As marketers, not only do we know who our best customers are, we're willing to pay more for these customers because we're confident, based on all our other customers, that we have a great product or service.
Often, marketers have more than one target market segment, so good campaign structures aren't simply about boosting bids against a particular demographic (the optimal segment). An optimal campaign structure might be one where different campaign segments (based on demographic or other profile data) receive different user experiences. Some of my team's more sophisticated and successful data-driven strategies rely on re-segmentation of the searcher audience into more than just keyword-engine combinations.
Unfortunately, to take full advantage of the profile data in Microsoft's adCenter, some marketers and advertisers with significantly different segments may need to set up strange duplicative campaign structures. This is similar to the hack we had to use for Google to bid separately for AdSense traffic (before Google enabled separate contextual bids). We used to set up cloned campaigns in which the search-only campaign had the higher CPC (define) and the search-plus-contextual campaign had a lower bid. Google would run search listings from one campaign, content ads from the other.
In adCenter's case, data enthusiasts (like my team and myself) get all excited abut bid boosts by age and gender, but we wish it were easy to carry this kind of personalization a step further. The missed opportunity is because a cloned campaign structure is necessary to provide a different experience to a different demographic profile. Some consumers in specific demographic profiles may prefer a different landing page offering a different merchandised product set. Now this can be done using the cloned campaign structures. But that's inefficient and only worth doing on the very highest volume keywords or Orders/AdGroups (given Microsoft's current traffic levels).
Without the aid of a strong set of analytics, it's easy to go a bit crazy when you start thinking about all the possible ways a campaign structure could be set up. Targeting by geography, gender, and age alone creates a multitude of variation possibilities. To get a handle on which segments are worth addressing, break yourself out of the Internet marketing silo and talk to whoever within your company does:
Armed with the knowledge of who your best customers are, you can create not only bidding strategies for these customer segments but, taking it one further, custom user experiences for these segments as well.
AdCenter's research tab can help you determine if a segment is large enough to bother segmenting out. By entering in the keywords you're interested in the "research" tab and reviewing searchers' profile by age, gender, and geography, you'll be able to map those percentages against your key power segments. Any large searcher segments that are also key segments for you are prime targets for a segmentation of user experience plus bid segmentation (bid boosts).
In the other engines, your segmentation models are limited by geography. However, this is a great opportunity if marketers show the engines how we're improving user experiences through segmentation modeling (which creates improved relevance). Yahoo and eventually even Google (which, despite its touted allegiance to relevancy, has sworn off any behavioral targeting or profile-based segmentation) may join in. Everyone agrees better targeting and better user experiences improve relevance. Improved relevance helps the consumer as well as the marketer. It even reflects well on the search engine.
Making ads and landing pages more relevant improves ROI (define) and profitability, but there are process costs from a campaign management perspective and operational costs in developing the personalized buy-flow and landing pages for clients. Higher-spending marketers will be the first to take advantage of segmentation-based relevance increases. Over time, tools for segmentation-based relevance improvement may get better. My wish list includes the engines passing additional targeting parameters into the click URL, extending the methods used in Google's Fast Track and Yahoo's Easy Track.
What's on your wish list of PPC features for 2007? Share them with me.
Want more search information? ClickZ SEM Archives contain all our search columns, organized by topic.
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Kevin Lee, Didit cofounder and executive chairman, has been an acknowledged search engine marketing expert since 1995. His years of SEM expertise provide the foundation for Didit's proprietary Maestro search campaign technology. The company's unparalleled results, custom strategies, and client growth have earned it recognition not only among marketers but also as part of the 2007 Inc 500 (No. 137) as well as three-time Deloitte's Fast 500 placement. Kevin's latest book, "Search Engine Advertising" has been widely praised.
Industry leadership includes being a founding board member of SEMPO and its first elected chairman. "The Wall St. Journal," "BusinessWeek," "The New York Times," Bloomberg, CNET, "USA Today," "San Jose Mercury News," and other press quote Kevin regularly. Kevin lectures at leading industry conferences, plus New York, Columbia, Fordham, and Pace universities. Kevin earned his MBA from the Yale School of Management in 1992 and lives in Manhattan with his wife, a New York psychologist and children.
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