Can brand marketers apply metrics to SEM? Meet BEI.
Brand marketers have an advantage in their ability to maximize the volume of clicks they receive from search engines. But it's not all roses. Brands have it tough using metrics to measure effectiveness and to adjust search engine campaigns. Sure, search text listings have some branding impact. Yet it's far more likely a brand advertiser wants to create a brand experience on its site, not on a search results page. That requires post-click metrics.
That's a dilemma. A marketing professional with a branding objective wants to use search engine marketing (SEM) efficiently. In an e-commerce or business-to-business (B2B) SEM campaign, not all clicks are created equal. Metrics are used to differentiate between the best and less-valuable traffic. Most marketers are forced to "do a study" to compare media effectiveness or different creative executions. Many studies are cosponsored by industry organizations such as the Interactive Advertising Bureau, which coordinated research to examine online media as part of effective overall campaigns, or Dynamic Logic, which employs metrics that compare creative and media. None of these metrics lends itself to effectively measure the differential between keyword/position/engine combinations search engine marketers use.
We need easily measurable data that correlate with branding metrics to make necessary, ongoing adjustments in search engine campaigns. I propose a new metric, based on a behavior mapping strategy, called the Branding Effectiveness Index, or BEI (pronounced "buy"). BEI is a work in progress but has already proven useful in comparing campaign results.
Each marketer's branding needs are unique. Each determines which measurable actions and metrics combine to create his own BEI. The result is a flexible metric that measures branding impact. It won't measure ad effectiveness, rather the effectiveness of a given site on a visitor driven by an ad. A visitor interacts with the brand on the site and, ideally, positively changes the way she feels about that brand. If results aren't positive, there may be serious problems. You probably shouldn't spend on media until your site provides a good user experience.
A site does the branding in this case. So instead of using metrics designed to measure advertising brand effectiveness, we use the following proxies to build our own BEI:
BEI is a flexible, relative metric. It's used to compare campaign elements to achieve optimized results.
To generate your own BEI, set the most valuable measurable action to a value of 1. Other significant actions are assigned a percentage value of that variable, based on importance. For example, if a brochure request is 70 percent as important as newsletter registration, assign it a value of 0.7. All actions are added up and multiplied by their factor. These are totaled and divided by spending to determine BEI.
Any campaign or campaign segment (even a single keyword listing) can be measured by how well it did achieving BEI. Using the example above, 20 newsletter registrations and 10 newsletter requests for a $1,000 spend results in a BEI of ((20*1)+(10*.7))/1,000, or 0.027. If the number of newsletter registrations rises to 40 for a different campaign segment, BEI is 0.047. This value is useful in comparing campaign segments when using the same formula.
If a second campaign with a different set of measurable actions exists, results aren't comparable. A simpler way to think of BEI is as a variable, like a weighted average cost per action (CPA) that incorporates a host of post-click actions. I'm working with statisticians on how BEI might be normalized to allow comparison across various sites. That requires a more complex formula to set "factors" for actions.
Let's look at AdAge's top brands to see what metrics they might use to build BEI.
I'll spare you more examples.
Whether you think BEI is a wonderful new way of combining existing metrics to capture a site's branding impact or the nonsensical ravings of a guy who's looked at too much data, the fact remains Web sites impact brands.
Marketers should plan and adjust campaigns based on brand awareness measurements. My branding clients are glad to have an empirical way to effectively manage their paid search campaigns.
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.
US Consumer Device Preference Report
Traditionally desktops have shown to convert better than mobile devices however, 2015 might be a tipping point for mobile conversions! Download this report to find why mobile users are more important then ever.
E-Commerce Customer Lifecycle
Have you ever wondered what factors influence online spending or why shoppers abandon their cart? This data-rich infogram offers actionable insight into creating a more seamless online shopping experience across the multiple devices consumers are using.
October 13, 2015
1pm ET/ 10am PT
November 12, 2015