Some tips for finding statistically valid sample data at every level of your campaign.
Small PPC (define) marketers have it tough. I get a ton of calls from people asking me if my firm can help them manage their small (under $5,000 per month) campaigns. I respectfully decline and often steer them to one of the technology or service providers focusing on the small business market. Some small businesses want tools to help them manage their own campaigns. Most, however, want to know that a professional is handling it for them, because small business marketers believe search marketing to be difficult, and (depending on whom you ask) they may be entirely right.
Regardless of whether the small business chooses to manage its own paid search advertising campaign or to have it managed "professionally," the reality is there are hundreds of thousands, perhaps millions, of businesses spending under $2,000 on PPC search and online yellow pages listings each month. These small business marketers face some unique challenges relating to their search spend. One big challenge they face is actually shared by larger-spending advertisers with very broad keyword sets and low data validity at the keyword (or perhaps even ad group) level.
Most of us have it easy. Spending sufficient funds on PPC means that we can watch conversions from our power keywords flow in on a daily or hourly basis. These conversions make it easy to calculate the appropriate bids for keywords given our ROI (define) or profit objectives, because we're generating a statistically valid sample of data. The challenge with low spending accounts in general is that statistically valid sample data takes a long time to generate at every level of the campaign -- from campaign to ad group, down to the keyword (or phrase) level.
With a bid at a specific level and an average position at a particular range, only three possibilities exist: the bid is too high, too low, or just right. How can one know if the data is missing or statistically suspect? One can't, not really. But there are some solutions.
Even if you do all of these things, you probably won't be changing bids nearly as often as a larger spending business would, so you may find that the bid landscape is swirling around you. Therefore, your bid velocities (speed of changing bids) are fairly low on a comparative basis. Eventually, as you learn more about what is working, your bids will align in the approximate correct range.
Dealing with data scarcity is a matter of tradeoffs. The more keywords for any low budget, the longer it takes to move individual keyword bids to an optimal level. Conversely, high keyword click concentration can help speed up the process.
I hope some of the above has helped you deal with the issue.
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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.
Hong Kong, May 5-6, 2015
Gartner Magic Quadrant for Digital Commerce
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Paid Search in the Mobile Era
Google reports that paid search ads are currently driving 40+ million calls per month. Cost per click is increasing, paid search budgets are growing, and mobile continues to dominate. It's time to revamp old search strategies, reimagine stale best practices, and add new layers data to your analytics.
May 6, 2015
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