Targeting the Maximum Yield

 

Recently, I read an interesting article about the airline industry in the “Financial Times.” Traditional airlines have faced fierce competitions from a plethora of low-cost flights offered by low-cost carriers (LCCs). Many struggle to stay afloat in this highly competitive environment.

According to the article, the major airlines struggle stems not from their inability to sell seats but rather their inaptitude to maximize target yield effectively. Traditional airlines have employed revenue management systems for over a decade to determine how many seats to allot to different market segments on the same plane. Yet LCCs use a more modern yield method, based on real-time demand. All passengers (business and leisure) pay the same price for the same product. Higher-priced seats are sold only when lower-priced seats are gone.

Contrary to popular belief, the airlines’ goal isn’t necessarily to fill their aircrafts to the maximum but to maximize revenue yield. It isn’t difficult for an airline to fill a plane if the price is right, but maximizing the yield is much more complex and challenging. Different segments result in different profitability and margin levels. To effectively achieve maximum yield, airlines must go beyond generic demographic segmentation and utilize systems that can target real-time actions to adjust pricing.

The airline industry’s challenge reminds me of hurdles we face in online media, specifically within the context of behavioral targeting. Because they’re similar to the airline industry, intelligent targeting and behavioral segmentation hold the key to achieving maximum yield for an online campaign.

Intelligent Targeting Yields Max Efficiency and Return

To maximize revenue and profit, airlines rely on the revenue management system to intelligently allocate sufficient value to the customer segment with the highest yield potential. Because a Tokyo-bound passenger is more profitable than one who’s London-bound one, the system must be able to recognize origin and destination to determine how many seats to allocate to different destinations at their varying fares, and with varying demands and no-show rates.

This is similar to behavioral targeting’s basic concept, which in its utopian functioning state must recognize consumers who demonstrate the most profitable behaviors (e.g., repeat visits, purchases, etc.) that may lead to a campaign’s highest yield and must allocate appropriate impressions with relevant messages to maximize return. Behavioral targeting has the potential to optimize campaigns based on the users’ actions and behaviors, thus allowing advertisers to assess users’ lifetime value.

It’s no secret consumer online actions are becoming increasingly complex. They require greater analytics to decipher their implications so marketers can react to them. Whether we’re ready for it or not, we must move beyond using clicks and single actions (e.g., registration) as metrics. They no longer provide sufficient information for the lifetime value models many advanced advertisers have adopted.

Is Behavior a Media Currency?

Demographic targeting is no longer sufficient to reach multimedia consumers. It’s quickly becoming obsolete in online media as Internet-empowered consumers perform new behaviors that cross age, gender, geography, and other traditional constraints.

This tectonic change in media planning, supported by behavioral targeting’s increasing momentum, poses an interesting question: can behavior eventually become a media currency?

If certain behaviors yield higher revenue returns for companies, can they be monetized and sold by those who provide behavioral targeting? Take, for example, “big spenders,” one of the 16 new segments 24/7 Real Media developed for its behavioral targeting platform. The segment’s behaviors obviously suggest potential higher online purchase frequency to an e-tailer client, so the segment’s value is naturally greater than a generic customer’s. Would it be possible to buy one behavior for a $25 CPM (define) premium and another for only $10 CPM?

If the cost-per-unique concept realizes its full potential, behavioral targeting vendors can theoretically track the entire online population. They can segment it into behavioral clusters that are priced dynamically to reflect external stimuli and events in the macro environment and individual preferences on micro level that can affect behaviors.

What This Means for Online Media

U.S. airline carriers have suffered from tremendous yield erosion because travellers know there are huge variations in fares. Many will spend hours plugging different times and dates into airline Web sites in a quest for the best deal. These behaviors make it very difficult for marketers to predict demand.

Though marketers can’t control these types of behaviors per se, they can monitor and target them with relevant messaging to optimize their revenue yield. As online media becomes more sophisticated and consumer behaviors become more complex (as is inevitable), targeting capability and its strategic usage will become the competitive advantage for publishers and marketers.

The media model is shifting from demographic to behavior, suggesting targeting technologies will become a more crucial success factor in any media campaign. As the concept of “lean marketing” ultimately demonstrates, companies must target by segment yield (meaning lifetime value) rather than segment volume.

It’s rather unlikely media planners will one day run derivative models on behavior-segmented CPMs, but a behaviorally segmented pricing model is quite feasible if a significant portion of the total online population is mapped and tracked anonymously. Sound like a fairytale? Interactive Marketing Partners in Poland claims to have developed an ad-serving system that covers and tracks 99 percent of Poland’s online population.

Reality is closer than you think.

Relax. CPM will still be the unit for online media purchase. It won’t be going anywhere for a while.