What do you really know about your targeting data? All this information is supposed to focus our efforts and make it easier to reach the right prospects. However, blind attention to targeting
algorithms may be leading us astray.
"Now wait," you say. "Isn't the whole point of targeting getting closer to the customers we want to reach?" Of course that's the
goal -- and no one can say targeting isn't a good idea. However, how good is it in practice? In putting so much emphasis on what targeting data can tell us, we may collectively be ignoring what
targeting cannot tell us and missing big opportunities in the bargain.
For all impressions, you can measure with certainty referring URLs, daypart, and other details like the geographic
location of the IP address that caused the impression. That's what we know we know.
Then there's what we think we know (for only about 20% of the impressions!): Gender, age, household
income, attitudes towards purchasing, and more. Then we use statistics to infer from that targeting data the "guesstimates" for these metrics based on analyzing thousands of impressions and
identifying trends based on the 20% of impressions for which they are accurate. However, do you really know a given viewer is a 42-year old male MBA likely to spend on luxury travel goods and high-end
electronics? Well... maybe. That's what we think we know, based on targeting data alone. It's impossible to be certain based on statistics alone. That's why over-targeting blinds us to new
opportunities.
What about what you don't know you don't know? In the history of sales, explosive revenue growth often happens when a completely unpredictable new audience segment
embraces a product and drives its popularity through the roof. For example, when Hush Puppy loafers became popular again in the late 1990s, it wasn't because the 35- to 70-year-olds who valued
comfortable shoes started buying Hush Puppies again in droves. It was because hip 19-24 year olds discovered the brand, thought the shoes retro and cool, and bought them in droves. What about
exploring new markets that might make use of a product or service in unexpected ways? This is the area of opportunity that requires creativity, insight, and experimentation. I'd call it good old
human trial and error - but we're really talking about trial, error, and success.
Targeting can help you reach the audiences you suspect will respond well to a given campaign, but you
need human ingenuity to take risks and reach out into the great unknown.
If only 20% of impressions can be combined accurately with other data sets to "know" who they are, we
don't have precise knowledge of the other 80%. We allow algorithms to make educated guesses. That's why a truly great media plan will leverage those algorithms, but will also have major budget
committed to exploring new prospects and reaching existing customers through appropriate media placement.
Traditional media planners -- especially when working in concert with subject matter
experts who run vertical ad networks - offer a critical complement to targeting alone. To run an effective campaign, you need to balance automated targeting with the benefits of working with real
people who select sites, know audiences, know design and content quality, and understand the context where that high-impact ad will appear and spark interest for both your existing customers and your
future ones.