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Algorithms, Brand Advertising and You

Audience Buying Isn't Just About the Clicks

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One of the largest advertisers in the country spends tens of millions of dollars a year on Yahoo just on branding campaigns – and they would spend more if they could. They probably should be spending more buying audiences across the web while improving their campaign on Yahoo against all of their marketing objectives. The "math" of audience buying isn't just about performance. The best companies have flexible algorithms that drive branding and help reach new audiences while gleaning actionable intelligence.

Consider a study by KN Dimestore and MediaMath, which found that audience buying raised brand awareness by 26 percent and brand preference by 39 percent, compared to unexposed consumers.

Another study by KN Dimestore and Lotame found a 24 percent lift in intent to recommend a product after consumers had been exposed to online display advertising about it. This was true even when consumers didn't click on the ad – in fact, the study showed that brand awareness was actually higher when an ad was not optimized for clicks.

An ad that tells a story and appeals to the emotions will be more compelling and effective for brand advertising than one optimized for clicks, particularly if it's well targeted. The longer the exposure time of the ad, the better it is for branding, as the viewer is more likely to remember it. Optimizing against these criteria at the kind of scale that only machine buying can makes the right demand-side platform a compelling partner for brand buyers.

Automated buying with smart algorithms can target with more precision than any other means, as well as control where the creative runs on the page, and report in lavish detail so marketers can verify their strategy was executed. For example, an ad can be shown only to new parents in the market for baby products, iPad owners who read financial news, or 18- to 35-year-old men who live in cities and are less familiar with your brand. The possibilities are nearly endless, as a demand-side platform company can target based on many different types of data from a variety of sources: demographic, behavioral, social, interest, in-market, and other types of data. Brand buyers are just as interested in efficiency as any other – so why not use a rifle instead of a shotgun?

Equally important for brand campaigns, smart algorithms can control contextual relevance at the page level, including attributes such as channel, content, and sentiment. So, for example, an advertiser could show an ad for a lightweight stroller for toddlers on pages of parenting sites with a large urban readership that mention toddlers. The advertiser could specify to avoid pages with negative brand sentiment. Or, a demand-side platform company can reach out to those consumers who are most likely to be brand advocates.

A powerful platform can increase the brand efficacy of a campaign by honing in on sites that are more likely to drive purchase intent for a particular type of product. MarthaStewart.com and GoodHousekeeping.com, for example, are sites whose visitors show an extremely high intent to purchase in areas such as food, cooking, home renovation, decoration, maintenance, and organization. In the technology vertical, visitors to Gizmodo and Engadget are frequent purchasers and early adopters of high-tech gear and services.

Demand-side platforms work for branding because they enable brand buyers to reach the right consumers in ways that weren't even imagined only five years ago, and to optimize directly to brand lift metrics in real time. When the logistics of the campaign are automated, marketing professionals can spend more time on the strategy and creative ideas that lead to rich brand experiences. Better scale, better targeting, and better analytics mean better results for brand buyers.

ABOUT THE AUTHOR
Joe Zawadzki is CEO of MediaMath.
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