Your attribution model may be missing key information. Consider these scenarios.
Nearly every search dollar currently spent on Google, Microsoft adCenter, and the other engines is based on last click attribution. This method works well - at least from the perspective of justifying search spend levels to management. Recently, however, the buzz around attribution of media "beyond the last click" has been all the rage. However, attribution models that allocate credit away from search without re-evaluating the ROI targets for a campaign can result in a significant loss in profit. Here's why.
At best, most marketers are baking into their attribution models digitally delivered media types that, for reporting purposes, share a common cookie pool. Unless the only marketing you are doing is search and Web display, your attribution model is missing far more information than it actually has to work with. Here's what may happen in this scenario:
If this sounds familiar, then the risks of imperfect attribution models have been driven home already. If not, let it be a lesson to you regarding the unintended consequences of attribution models.
At this point, you are probably asking yourself, "What's the solution?" since clearly other media and marketing (earned media and paid media) are in fact helping influence consumers to decide that your brand, product, or service should be the one they buy. When your media and marketing influences search behavior, the first thing you should know is which keywords are spiking up the most. Generally, the keywords we've seen spike most heavily as a result of effective marketing and media are the brand keywords (product names as well as your domain and company name). Usually these keywords should already have a high enough reserve price on the bid that they won't be impacted by a modest shift of attribution to other media. However, I've seen many instances where brand keywords are insufficiently bid (perhaps because the bids are set based on a seat-of-the-pants method, rather than algorithmically by the marketer or agency), or budgets for campaigns overall are insufficient to allow for surges in search behavior.
Also, if you spend media dollars elsewhere or devote significant energy to earned social media marketing, then you should revisit your ad creative and landing pages. Don't send all brand or product users to their respective existing home pages when that traffic should be otherwise routed to specific landing pages that resonate with the messaging being pumped though your other media, perhaps because of incremental media spend, social media buzz, or PR.
For example, Apple, Best Buy, and J&R all were running PPC ads against "iPad" when I did a search here in NYC, but they were apparently not taking into account the fact that this week many iPad searches will be related to information on the iPad 2. Clearly, one should be treating iPad searchers differently this week due both to media being spent and marketing buzz (earned media).
Search marketing shouldn't sit in a silo, but attribution isn't the only way to look at search media in comparison to other media. Search is an altogether different beast, because other media and marketing drive search behavior.
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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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