Age and gender are the foundation upon which the great majority of marketing plans and creative are built. In most cases, this information is inferred based on the collection of syndicated data such
as Nielsen or consumers' actual behavior offline (e.g. purchase history) and online (e.g. web browsing history).
These data have been considered so valuable historically that virtually all
companies involved in product marketing and the buying and selling of media have dedicated significant resources to understand and reach specific sets of consumers based on these two demographic
points. They key word here is "historically."
It's no longer efficient or effective to target consumers based on narrow, potentially inaccurate demographic points at a moment
in time when there is much more insightful information available to drive targeting decisions. Acknowledging that there is some "prospecting" involved in many mass media buys, marketers
buying just age and gender never the less run the risk of wasting impressions on uninterested consumers or missing an audience that may be exactly the right customers to embrace, and possibly
evangelize, the message and the product. The new media ecosystem can yield data that enables targeting based on rich, multi-dimensional profiles of consumers, and reduce the risk of waste.
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The fact is, self-selecting interests and actions are more important targeting barometers than age and gender.
Customers also don't behave as you would expect based on their age or
gender. Consumers today have shattered conventional mores, and it is not possible to neatly categorize entire segments of the population. Is the electronics marketer reaching Men 18-34 to sell
gadgets, games and technology? Or are they also considering the suburban Mom who is, in her own right, a serious consumer in this category as well as an influencer for her peers through reviews,
commenting, and blogging? Is the mortgage broker targeting Men and Women 34-49? Or are they thinking about the 24-year old venture-backed entrepreneur who may be exactly the right candidate for a
jumbo loan?
Messaging is being driven largely by traditional media standards, but basing executions solely on targeting by age can be particularly ineffective. For example, the idea that a:
30 spot developed for a daytime television audience will resonate with that audience online is not necessarily a foregone conclusion. It is merely economical. Online messaging affords marketers an
opportunity to tailor messaging in terms of both creativity and offer based on the customer behavior as opposed to an age group.
Ad targeting is not a one dimensional solution for marketers.
Early online targeting based on IP address evolved to incorporate inferred age and gender. The next genesis brought contextual targeting based on adjacency and relevance to market. Contextual
targeting is now only part of the picture, with behavioral targeting, or targeting based on browser history, a key decision-making factor. Later stage targeting can capture actual age and gender when
the user offers it via profile. However, we are still using age and gender, inferred or actual, as a foundation.
Successful marketers understand and accept that their new customers
won't fit into the historically correct box. These marketers will embrace the diversity of all potential customers based on what they tell us through their behavior, interests and actions.
New, highly evolved technology allows marketers to get a deep, nearly 360 degree profile of potential customers. We can combine demographics where available and reliable and the traditional
online behavioral targeting metrics, such as contextual relevance with insights based on the consumers' social interaction with any media.
Understanding who customers are and what they
might purchase adds previously unavailable dimension. For example we have found that people who create content online tend to be more affluent. In and of itself a tentative data bit, but when combined
with factual data on what they're actually doing and how that relates to the content being created, a profile of the user emerges that is far more accurate and actionable than would be available
using demographics alone.