Tag Archives: data mining

The difference between shouting to a group and speaking intimately with an individual.

During this tumultuous 2008 election year here in the States one hears the cry, “Drill, baby, drill!” with increasing frequency. And while this cry is about drilling for oil, there is another type of drilling that is changing everything from how elections are run to how soap is marketed. Let’s call it digital drilling.

In the article entitled, “It Worked For Bush“, the story is told of how traditional campaigning was turned upside down by what might be called database marketing…but that term seems inadequately quaint within this context. It’s more than database marketing, it is more accurately digital drilling because it drills down from a huge data cloud right to your doorstep.

“The pollsters also looked in the wrong places. On election day, every exit poll showed a clear Kerry lead. Yet the polls were wrong, because they were wrong in the weightings they gave to different socioeconomic groups and in the assumptions they made about who would turn out to vote. The Bush team had, in effect, destroyed all the methodology on which polling and electoral analysis had been based for the past 50 years.”

Let’s take a look at how this was done,
STAGE ONE:
The ability to digitally store and archive massive amounts of raw data.
STAGE TWO:
The growth in the quantity and quality of multi-sourced consumer information.
STAGE THREE:
The ability to link multiple data islands.
STAGE FOUR:
The analytical power to search and discover new, meaningful patterns and relationships of strategic and tactical value.

This begs the question who did this and how did they do it? TargetPoint Consulting was the company that did this work for the Bush campaign and they describe how, what they call MicroTargeting, completely changes the game:

Why Now?
“In a word: technology. Campaigns have always collected data on their voters, and there have always been mounds of census data, polling crosstabs and voter registration files. Unfortunately, that data was in most cases wholly insufficient to get the job done, or too large and complex for anything more than rough approximations, oversimplified target lists, and statistically insignificant intuition. Technological developments have brought desperately needed depth and clarity to our formerly flat and hazy perception of individual voters.

By using hundreds of data points, comprised of voter information, life cycle information, life style information, financial data, consumer behavior, geographic data, and political attitudes and preferences, MicroTargeting can be used to segment each of your voters into one of a number of mutually exclusive groups, each defined by a unique combination of a host of data points.”

Irrespective of your political inclinations, the issue of digital drilling is an interesting one. And if you are a marketer, the interest is more than a passing one because in a post-broadcast world there is a difference between shouting to a group and speaking intimately with an individual. And motivating them to action.

Digital drilling may help you do that.

Marketing? Automated Serendipity.

Bob Garfield has been railing on about a post-advertising age for over three years now and marketers just may be catching up with that concept.

In his 5,000 word article, a manifesto of sorts, he describes a form of marketing that is far beyond the traditional definition of marketing:
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“”Now we have the ability to automate serendipity,” says Dave Morgan, founder of Tacoda, the behavioral-marketing firm sold to AOL in 2007 for a reported $275 million. “Consumers may know things they think they want, but they don’t know for sure what they might want. They’re not spending all their time hunting for those things.”

Take, for instance, flat-panel TVs. In 2006 Tacoda did a project for Panasonic in which it scrutinized the online behavior of millions of internet users — not a sample of 1,200 subjects to project a result against the whole population within a statistical margin of error; this was actual millions. Then it broke down that population’s surfing behavior according to 400-some criteria: media choices, last site visited, search terms, etc. It then ranked all of those behaviors according to correlation with flat-screen-TV purchase.

In that list, “shopping online for flat-panel TVs” ranked 22nd — 18 places below “consumed ‘Miami travel’ content.” Miami travel?

“Not Chicago travel,” Morgan says. “Not Europe travel. Not business travel. Don’t ask me why. But here’s the incredible thing: No. 1 — and significantly above the others — was people looking at military content. It made no sense. Then I talked to a friend of mine who had been an officer in the first Iraq war. I said, ‘What’s going on?’ He said, ‘That’s easy. The kids in the military are huge video-gamers. They get big, fat signing bonuses, and their housing is free. They don’t need cars. So they buy big TVs.'”

Morgan followed up because he was curious and felt the need for this counterintuitive association to have an explanation. But he needn’t have. Why ask why? The whole point is that data mining takes us to a realm beyond obviousness and common sense. The data speak for themselves.

This message was hammered home in research the same year for Budget Rent A Car’s weekend-rental promotion. “Shopping for a rental car” was the No. 4 correlation. No. 1 was “recently read an online obituary.” Try to connect the dots if you wish; meantime, go read some online obits and see what ads show up on the page.

“We no longer have to rely on old cultural prophecies as to who is the right consumer for the right message,” Morgan says. “It no longer has to be microsample-based [à la Nielsen or Simmons]. We now have [total-population] data, and that changes everything. With [those] data, you can know essentially everything. You can find out all the things that are nonintuitive or counterintuitive that are excellent predictors. …

There’s a lot of power in that.”