Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Next Gen Research is and What it isn’t? – Biometric Research
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Next Gen Research is and What it isn’t? – Biometric Research
Uncategorized

Next Gen Research is and What it isn’t? – Biometric Research

TomAnderson
TomAnderson
7 Min Read
SHARE

As part of the series of posts on what Next Gen Market Research is and what it isn’t and what place it has in consumer research I thought I would start out by taking a look at what place biometric technology should have in consumer research. Specifically things like MRI’s, Lie detectors, eye tracking & pupil dilation equipment…

Today I’m talking to my associate Ryan Brown who has a background in anthropology as well as psychology (See Bio at bottom).

TOM: Ryan, there’s a lot of talk lately about biometric/neurological research. How useful is this, are we going too far? Is it too intrusive? Should we really strap people down and put sensors on their foreheads etc…?

RYAN: I am actually quite a big fan of biometric research, but with the following caveat – the biological indicators under consideration should be closely studied with respect to how accurately they predict behavior. For example, we can spend painstaking hours coding videos of facial expressions or use electrodes to obtain measurements of the activation of facial muscles generally associated with positive or negative effect. This can certainly get us a very accurate read of expressed emotion, but how closely is …


As part of the series of posts on what Next Gen Market Research is and what it isn’t and what place it has in consumer research I thought I would start out by taking a look at what place biometric technology should
have in consumer research. Specifically things like MRI’s, Lie detectors, eye tracking & pupil dilation equipment…

More Read

What Should I Say About Social Search?
“TIME AND TIDE WAIT FOR NO MAN”
Can Cloud IP Address Be Damaged Goods?
3 Reasons Today’s Marketing Datasets Are a Whole New World
DQ-Tip: “…Go talk with the people using the data”

Today I’m talking to my associate Ryan Brown who has a background in anthropology as well as psychology (See Bio at bottom).

TOM: Ryan, there’s a lot of talk lately about biometric/neurological research. How useful is this, are we going too far? Is it too intrusive? Should we really strap people down and put sensors on their foreheads etc…?

RYAN: I am actually quite a big fan of biometric research, but with the following caveat – the biological indicators under consideration should be closely studied with respect to how accurately they predict behavior. For example, we can spend painstaking hours coding videos of facial expressions or use electrodes to obtain measurements of the activation of facial muscles generally associated with positive or negative effect. This can certainly get us a very accurate read of expressed emotion, but how closely is expressed emotion actually associated with, say, the propensity to purchase a certain product?
That is a much more complex matter, and one that is often not as well laid out in biometric or physiological research.

The key with biometric experimental paradigms, in my opinion, is to create studies that accurately portray the real-world situations in which the researcher is interested; for example, driving accurately under stressful conditions, shooting a target but not innocent bystanders, choosing one brand over another, etc. If such an experimental paradigm is developed, then individual differences in physiological responses can be quite informative. For example, recent research has indicated that Navy Seals have different patterns of brain activation in response to threatening faces than regular armed service personnel.
Such data is useful, as it might help with testing procedures to pre-screen personnel who could be particularly effective in certain types of combat situations.

In the end, the researcher needs to stay focused on the behavior or outcome they are trying to predict or alter. It is all too easy to get caught up in the excitement of being able to peer “under the skin,”
and observe the multiple (endless, really) physiological systems that are involved in cognition, emotion, and behavior. The key question to ask is, “will these biological indicators give me additional predictive leverage or information about the outcomes in which I am interested?” Often, biological indicators are useful for detecting individual differences (as in the Navy Seal example above). Unless one is interested in subgroup effects on purchasing, marketing researchers might not always be interested in such individual differences and the intricacies of their biological roots; the bottom line is instead whether a certain marketing strategy increases purchasing behavior in the market on average.

Often, we simply don’t have the data to know how well biometric indicators are linked with actual behavioral propensities. However, these data are slowly accumulating. Biometric research has a lot to add, but it is still in its infancy. Like any research tool, it should be used with caution, and continual attention to “real world”
behaviors.


Dr. Ryan A. Brown – Senior Consultant Anthropology & Psychology
Ryan is an anthropologist with training in human biology and
public health. His primary research focus is on the evolutionary,
biological, and cultural roots of risk-taking behavior.

Brown spent three years studying the lives of Cherokee and White young
adults in the Appalachian Mountains of western North Carolina, and has
published several articles on this topic. Turning his research more
broadly to population health during a postdoctoral fellowship with the
Robert Wood Johnson Foundation, Brown also conducted research on
physiological and emotional responses to social threat.

He is also an expert in youth research having worked with Anderson Analytics’ GenX2Z to study trends and behaviors of White, Hispanic, and Asian youth in the US.

[Post to Twitter] Tweet This Post 

Link to original postTom H. C. Anderson – Anderson Analytics

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

0622cae5 f7d7 4f74 84b5 eabd1a823dca
How Data-Driven Grocery Recommendations Help Shoppers Eat Better With Less Effort
Big Data Exclusive
business recovering from data loss
How Data-Driven Businesses Protect MySQL Databases from Shutdown
Big Data Exclusive
ai driven task management
Reducing “Work About Work” with AI Task Managers
Artificial Intelligence Exclusive
data center uptime
Why Rodent-Resistant Conduits Are Critical for Data Center Uptime
Big Data Data Management Exclusive Risk Management

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Some thoughts on perfect application development

4 Min Read

4 Reasons Why Big Data Analytics Projects Fail, or Do They?

12 Min Read

Complementing IBM BPM with ILOG

8 Min Read

Analyst: clouds are ‘fat dumb happy pipes’

1 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?