In last week’s blog post, I wrote somewhat skeptically about
micro segmentation and big data. I questioned the usefulness of very micro
segmentation, or very big data.
This week’s Numerati article got me thinking further on the topics
of micro segmentation and big data, and not their power to segment individuals
based on demographics or even purchase data, but to segment based on moods.
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| Image source: PBS.org |
The article talks about a data scientist Dave Morgan who
found a data pattern where a large number of romantic movie goers clicked on an
Alamo car ad.
While at first the relationship was puzzling, eventually the
researchers discovered the link had to do with people’s moods—the romantic
movie goers were more likely to respond to the Alamo car ad because it talked
about escapes, which was a better fit for their current mood than car ads which
focused on the car for business use.
The possibility of targeting someone in the moment—not based
on a detailed database of the person’s demographics or even purchase history—but
based on their instantaneous mood, is to me, much more intriguing.
Here is why.
First, it’s simpler
than most micro targeted because it does not require storing large amounts of
data. It didn’t matter if these movie-goers were male or female or from the
country or the city--- what mattered was that the ad’s focus on “escape” fit
their mood for romance and escaping. The ad was able to be very effective,
without all of the hassle of trying to keep an ongoing database or track of
each individual. It was effective by simply recognizing the user’s current
mood.
Second, segmenting on
mood has the potential to be so on-target that it could actually be welcomed by
the customer. To demonstrate its power, I will digress for a minute to talk
a bit about the current forms of advertising
- At one end of the spectrum is the mass TV ad—it will hit some of the intended target but also a lot of people that would not be interested. For example if I watch the golf channel with my dad, I see ads for golf clubs and Viagra, neither of which is appropriate for me.
- Further along the spectrum towards targeting is a service like Pandora. (I am a loyal Pandora user and often like to analyze the ads that they give me to understand how they might be targeting me). While Pandora does a much better job of targeting ads than TV, it is still not perfect. For example, one of the channels I like is Spanish music which serves me commercials in Spanish. For probably 99% of their audience this makes sense; however I happen to be the 1% that likes to listen to Spanish music but can’t understand a word of it. Closer, but still no cigar.
- Even banner ads with their precision targeting sometimes get fooled. For example, after I have been researching Cadillac for this course’s Online Marketing Information assignment I have seen ads for the Cadillac ELR follow me around on nearly every site. The technology is smart, but unfortunately in this case wasted. Sorry, Cadillac.
In contrast to these examples,
what makes the prospect of targeting by mood so exciting is that success will
be nearly guaranteed. If you find ways to identify and reach consumers with
specific moods your chances of connecting with them are nearly 100%, and
potentially even welcome. For example, imagine being able to identify certain
consumers within a 10 mile radius who are projecting a “fun, laid back mood.”
An ice cream store that could reach out to the consumers in that mood to invite
them to come in to try the latest flavors would probably find resounding
success.
Readings
Readings
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Week 5 Readings
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Great very recent article on Big Data and your
Health. Thanks to a
student for providing this link.
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Week 4 Readings
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Article:
"The Economics of Giving it Away," The Wall Street Journal,
Jan. 31, 2009. (Download content.)
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Video: Disrupters: eCommerce Presentations by Charlie Kim of Next Jump, Inc.; Jen
Beckman of 20X200; and Tebecca Thomsen of Alice.com.
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