Technology that derives
personality traits from Twitter updates is being tested to help target
promotions and personalize customer service.
By Tom Simonite
WHY
IT MATTERS
Both businesses and customers
have a significant interest in the technologies used to target and track
personal behavior.
Trying to derive a person’s
wants and needs—conscious or otherwise—from online browsing and buying habits
has become crucial to companies of all kinds.
Now IBM is taking the idea a
step further. It is testing technology that guesses at people’s core
psychological traits by analyzing what they post on Twitter, with the goal of
offering personalized customer service or better-targeted promotional messages.
“We need to go below
behavioral analysis like Amazon does,” says Michelle Zhou, leader of
the User Systems and Experience Research Group at IBM’s Almaden Research Center
in California, which developed the software. “We want to use social media to
derive information about an individual—what is the overall affect of this
person? How resilient is this person emotionally? People with different
personalities want something different.”
Zhou’s software develops a
personality profile based on a person’s most recent few hundred or thousand
Twitter updates. That profile scores the “big five” traits commonly used in psychological research:
extroversion, agreeableness, conscientiousness, neuroticism, and openness to
experience. It also scores the person on measures of “values” (for example,
hedonism and conservatism) and “needs” (for example, curiosity and social
harmony).
Zhou says she is working with
several IBM customers to test how the technology might help their businesses.
She declines to identify the companies but says they might use the system, for
example, to tune marketing messages sent by e-mail or social media, or to
select the promotional content displayed when a customer logs in to his or her
account.
A crucial part of the pilot
program will test whether messages targeted with the technology’s help perform
better than others. “Our hypothesis is that the conversion rates will be quite
high,” says Zhou. At least, she expects them to be higher than is typical:
e-mail marketing
messages ordinarily have a
response rate of just 0.34 percent, she says, and phone marketing calls achieve
about 13 percent.
Zhou says that having a rough
idea of a person’s personality could also help in call centers or other
customer service settings, such as when an airline must break the news that a
flight has been cancelled or delayed.
“Studies show people that are
extroverted want a reward and recognition, like 10,000 [frequent flyer]
points,” she says. “Conscientious people want efficiency, to know their new
flight right away.” In a call center scenario, a customer’s personality profile
might advise a customer service agent whether to efficiently provide “just the
facts” or to try to be more engaging and supportive, says Zhou.
Many businesses already make
use of software that analyzes social-media activity. However, it is aimed
either at helping corporate representatives interact with customers or at
summarizing the overall volume and tone of a discussion (see “A Social-Media
Decoder”), not at profiling
individuals.
Personal profile: According to IBM’s analytic software, this
author’s Twitter account reveals him to be more neurotic than extroverted.
IBM’s software was developed
by recruiting people to answer psychological questionnaires and comparing the
results with their Twitter activity. Machine learning software then looked at
how different patterns of word use matched with psychological traits. Those
correlations were used to derive models that can create a profile from a
person’s tweets alone.
In a study where 300 people
had their Twitter profiles processed by the software and also took psychometric
surveys, the results were “highly correlated” more than 80 percent of the time,
says Zhou. However, she notes that when people use Twitter in a specialized
way—for example, journalists discussing their beat—their tweet-derived profiles
may not be so representative.
Still, Zhou argues that since
the methods companies currently use to target and understand their customers
are relatively imprecise, IBM’s software doesn’t have to capture a person’s
personality completely to be useful. She also says it should be possible to
adapt the software to use other sources of data, such as call center
transcripts or online customer service chats.
Software like Zhou’s that
relies on language use should be able to usefully capture something of a
person’s personality, says Andrew Schwartz, a researcher at the University of Pennsylvania, who
recently published a major study of how personality traits show up in Facebook
activity (See “How Your Facebook
Profile Reveals More About Your Personality Than You Know”). He says previous research has shown that measured
personality traits can predict future actions, such as the number of sick days
or doctor’s visits a person will report.
“It seems reasonable that
personality would be useful for presenting ads that resonate better with the
recipient,” says Schwartz. “The ad-targeting application has been talked about
for a few years now, but I think language-based measures of personality are
just now becoming reliable enough to see it happen.”
http://www.ibm.com/smarterplanet/us/en/ibmwatson/
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