Looking back over the history of online behavioral marketing, progress has not traced out a straight line. Yet the trend has been consistent, working toward an online experience that meets each consumer’s individual needs and preferences far more precisely than broadcast messages aimed at lowest common denominators.
The trend toward precision delivery of individualized information is driven primarily by advertisers’ continuing urge for improved ROI. This sentiment is documented most impressively (but certainly not solely) in the results of a study released April 19 by a task force of 16 leading advertising agencies, aptly dubbed the ROI Council. According to the study, nearly half of all advertisers and agencies have begun altering campaigns to improve their returns on investment, and an overwhelming majority thinks the emphasis on ROI analysis is likely to keep increasing.
The same trend is also fueled by consumers’ own penchant for ducking unwanted advertising when they can. No one will be surprised that a majority actively resist advertising, as reported by a Yankelovich survey released in mid April, but many will be startled to discover that almost three out of four consumers would pay to skip or opt-out of marketing messages, and that 56 percent claim to disdain products that over-expose them to marketing and advertising messages.
But there is hope for advertisers: fifty-five percent of those surveyed by Yankelovich still claim to "enjoy advertising" in and of itself.
To keen observers, this situation calls out for more accurate and comprehensive information targeting -- precisely the direction in which we have historically been progressing.
Already, behavioral marketers are adept at tracking and identifying consumers’ individual interests, and own the technology to serve up just the advertisements likely to fit closely with an individual’s interests. At first this could be done only on individual publishers’ sites. But with the advent of behavioral targeting networks put together by companies like Revenue Science, Claria, aQuantive and TACODA Systems, behavioral targeting is now able to follow a consumer across many different websites.
By serving the right ad at the right time, advertisers can demonstrably increase their favorable impact on consumers, sometimes by as much as 30 times or more. The net result is markedly higher advertising rates for publishers combined with better ROIs for advertisers. This win-win success is part of what drives the increasing acceptance of online advertising, which is already offering one of the highest ROIs of any medium, and feeds advertisers’ and publishers’ growing preferences for behavioral marketing approaches.
The next step will be for behavioral marketers to begin tailoring content as well.
By late Spring 2005, Claria intends to begin using its database of consumer behavior (and the insights it draws from ongoing analysis of that data) to modify individual visitors’ experiences on certain smaller publishers’ websites. Once the system is operational, each user on a web page will be served different content elements, as well as different ads.
Claria plans to expand on this capability, too, perhaps before the end of 2005, by integrating its own technology with the content-serving systems of major portals. The result will be seamless individuation of content and advertising across the vast majority of a consumer’s online experience.
So far, Claria offers this kind of tailoring on affiliated publishers’ sites only for the 40 million or so consumers who have opted in to its advertising-supported software. But when integrated with the major portals, the reach of this technology should expand significantly. (While privacy is always an issue, Claria is careful not to collect any last names, emails, mailing addresses or other personal identifiers.)
Experts recognize that the key element in people welcoming targeted information is to meet their requirements for extra value and relevance. In practice, this most often boils down to selecting information in line with their current needs and interests.
To understand why, consider a person looking to buy a computer. He will often buy one or more computer magazines as an aid in learning what’s out there. As he flips the pages, he doesn’t consider the ads intrusive, but helpful and relevant information. Similarly, a person looking for a new automobile will often go online and research various types of vehicles. As she works through the stages of her decision cycle, she will appreciate the savvy advertiser who offers the most relevant information and helps her make a better choice.
Yet once the computer and the car are purchased, the game changes. Now the post-choice consumer sees the very same content and advertising as intrusive, unwelcome, and even annoying. Serve up too many, and you may well whip up some significant backlash.
People interact much the same way with content. We may be heavily focused on a story like Terri Schiavo’s for a few days or week, and then much less interested in any such information as the matter winds down. Inevitably, we shift our focus to more immediate or important concerns now looming in our future.
When sophisticated individuation is commonplace for content, sites will normally start by providing stories that reflect an initial set of choices made by the individual as he or she first opts in to the service. But the underlying technology will track and analyze the individual’s information preferences day to day, week to week, and month to month, watching not only where you click, but how long you stay, and how each information resource you review fits with others you have visited. As time goes by, the system will continually infer and update your list of interests, making it likely that the next round of ads and content will be more relevant than previous ones.
Like a coded message, the information gathered from an individual’s online activities can be unscrambled into a detailed picture of the individual’s current commercial interests, the elements of their consideration set, and how far he or she may have progressed through his or her typical decision cycle.
Once the picture is made clear, advertisers can intelligently target our car-buying consumer, for example, at several key stages of her decision cycle: first when she’s interested in an overview of cars, then when she narrows down to SUVs and minivans, sometime later when she focuses on specific brands and models, yet again when she begins considering the relative merits and trade-offs among various features and options, and one final time when she is ready to make a purchase.
Of course, computing power is not infinite and for quite a long time it won’t be practical to track every parameter for every online information consumer. But that’s very much a part of the vision and the direction in which behavioral marketing is taking us.
For those concerned, no one is forcing this kind of technology down the throat of consumers who are fearful of losing their privacy. Many studies, such as the 2004 Survey from the Ponemon Institute, “Understanding America's Perception of Internet Advertising and Consumer Privacy,” show that a very large portion of online consumers are comfortable providing personal or even “private” data about themselves in return for access to more relevant and tightly targeted information. And the Yankelovich study found 55 percent of respondents "willing to pay a little extra to get only the kinds of marketing and advertising that [they] prefer to hear and see."
Advertisers and marketing professionals should recognize we’re in the midst of building an online environment that removes any need to mindlessly throw the same ads or content at large numbers of people every day, wasting as many as 95 percent of the impressions in hopes of reaching the 5 percent of consumers who are prime prospects. Instead, tools now (or soon will) allow sophisticated marketers to carefully read a person’s current needs and desires for information, and in response to fire off ads as accurately as a rifle shot.
The march of progress has advanced behavioral marketing from a shopping center model where advertisers simply serve up more relevant ads, through a research capability where search engines can prune their results lists based on individual interests and preferences, and now with a dynamic content model we can each experience as unique individuals, instead of cookie-cutter members of a cohort, demographic, zip code, or class.
In a few more years, terms like "personalized" and "behavioral marketing" may disappear entirely from advertising lingo, as all advertising and content, including product placement, becomes highly personalized and targeted to each of us via automated inferences about our up-to-the-minute interests and priorities.
