The importance of this MIT project is to prove a point, for a given time and location there will always be differences in opinions and unique cultural perspectives based on state changes. When the US began to start trade with Japan, locals considered Westerners as “blue eyed barbarians,” a unique perspective that has evolved and changed over time.  As depicted in the portraits below some artists rendered Commodore Perry from a realistic to demonic perspective. Click here for more.

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“Often referred to as ‘nature’s sports drink,’ milk can be an effective way to help the body refuel, rehydrate and recover after a workout as every serving contains nutrients that promote effective recovery after vigorous exercise,” said Gregory Miller, president of the Dairy Research Institute.

Miller is also executive vice president of the National Dairy Council, which co-sponsored the research with the Milk Processor Education Program.

Nutrients in chocolate milk include carbohydrates to help refuel muscles; protein to stimulate repair and growth; and fluid and electrolytes to help replenish what is lost in sweat and to rehydrate the body, according to Miller.

Methodology

The study involved 32 healthy, untrained participants following a 4½ week aerobic training program consisting of one hour of moderately intense cycling, five days each week.

Immediately and one hour following exercise, the cyclists consumed low-fat chocolate milk, a calorie and fat-matched carbohydrate beverage, or water.

Increased lean muscle and decreased body fat of the men and women was measured to assess the drink’s effect on body composition.

Other recent findings

The study’s findings follow the publication of a larger body of research on chocolate milk in Journal of Strength and Conditioning Research last month.

The research (2) studied ten endurance trained cyclists and triathletes who cycled for 90 minutes at moderate exercise intensity prior to performing ten minutes of high-intensity intervals.

Immediately following exercise and again, two hours following exercise, participants consumed a recovery drink of low-fat chocolate milk, a calorie and fat-matched carbohydrate beverage or a non-caloric flavoured water.

The results showed that chocolate milk improved cycling performance more than the other drinks, cutting at least six minutes on average off the cyclist’s ride time.

According to the author, chocolate milk and the carbohydrate drink were more effective than water in restoring carbohydrate fuel in the muscle. There was no difference between groups in markers of muscle breakdown.

Chocolate milk was also found to increase signals for muscle protein synthesis, which leads to the repair and rebuilding of muscle proteins, more than the other drinks.

1. Presented: American College of Sports Medicine 58th Annual Meeting and 2nd World Congress on Exercise is Medicine, June 2, 2011. Aerobic exercise training adaptations are increased by post-exercise carbohydrate-protein supplementation Authors: Ferguson-Stegall, et al.

2. Source: Journal of Strength and Conditioning Research Vol. 25, Issue 5, Pages 1210-1224, 2011 Post-exercise carbohydrate-protein supplementation improves subsequent exercise performance.

Reading Facial Expressions

Forbes tells of new technology developed at MIT that can read facial expressions over a webcam, which has proven difficult for computers to achieve. The researchers embarked on the task to help people with autism read others’ emotions more easily; now, Forbes reports, it is becoming commercialized to help businesses read their customers.

The MIT Media Lab Affective Computing Group – an MIT spin-out – is creating cloud-based tools that collect and communicate emotion data. It is also building a what is said to be the world’s largest repository of facial expressions. Other developments are more geared directly to businesses’ needs.

Omnicom Digital is experimenting with technology that allows billboards to tell if a passerby is paying attention and then send messages accordingly. The technology “actually recognizes faces. If you raise your eyebrow, it can track that,” says Jonathan Nelson, CEO (via the Wall Street Journal). “We’re exploring the applications, and they are endless.”

The Barbarian Group is planning to introduce this summer such a device. The next step, the Journal says, is a billboard that can interpret what images have intrigued the passerby the most and then more of them. Further down the line, marketers envisioning linking the real-time emotion captured by the technology to the person’s demographic background – a possibility that makes privacy advocates shudder.

Source:  MarketingVox

Psychographics has many fathers (including me), and all of them seem to have a valid reason for claiming to first develop it or be better at it than anyone else. Although there may be some argument about who was first, the truth is that everyone in psychographics (even those who call it lifestyle research or values research) is probably correct in advocating a “right” way to do psychographic research.

Their methodologies are different, but all researchers are trying to go beyond the demographics to quantitatively improve on past research for decision making when demographics are found not to be enough.

As far as I know, I did the first publicly available study of psychographics in 1965, and made up the name at the spur of the moment. I was at a Detroit ad agency with Jack Connors, then publisher of Holiday magazine and later publisher of Travel & Leisure, explaining the research I was about to do. The vice president we were visiting asked, “What do you call what you’re attempting to do?” My spontaneous reply was, “Psychographics!”

(As far as I knew then, psychographics was a word I had suddenly made up. Many years later I found the word had a history. It was used in “Grey Matter,” a newsletter published by Grey Advertising in New York.)

I would define psychographics as: “The use of psychological, sociological, and anthropological factors, such as benefits desired (from the behavior being studied), self-concept, and lifestyle (or serving style) to determine how the market is segmented by the propensity of groups within the market–and their reasons–to make a particular decision about a product, person, ideology, or otherwise hold an attitude or use a medium. Demographics and socioeconomics also are used as a constant check to see if psychographic market segmentation improves on other forms of segmentation, including user/nonuser groupings.”

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LARGE SAMPLES

The importance of being able to use large samples, which is a feature of psychographics, is that the study of a total population could finally be done with samples projectible to millions. Once we used to consider a sample of 100 quite large in a depth interview or focus group. With psychographics, we could finally use probability samples of about 1,200 to build marketing segments of the total population-and get media habits by each segment’s tendency to hold attitudes or behave a certain way–and the reasons for this.

This achievement had great importance because we could now profile media, as well as products, by their psychographic segments. A new development allows us to determine how a medium may influence the psychographic profile of its audience; in effect, doing a psychographic study of a medium and competition without the sizable expenditures normally associated with a major psychographics study.

My experience with what finally came to be known as psychographics goes back to 1948. While working with Dichter, I first thought of the usefulness of a segmentation technique that would cluster people by their tendency to think or act in a certain way.

Though he didn’t use the word psychographics to describe his work, Dan Yankelovich developed useful segments of watch buyers in the middle 1960s and wrote about this in the Harvard Business Review. This has to be considered one of the precursors of psychographics, as were studies in the early ’60s about consumers’ responses to product benefits by Russ Haley and Shirley Young for Grey Advertising.

MEANINGFUL NUMBERS

My original concept was that learning whether the finding that a person earned a particular salary, say $25,000 per year, could be made more meaningful if we knew if that person had been earning $50,000 and was reduced to $25,000; if the individual had just been given a raise to $25,000; or if the person had been making $25,000 per year for a long time.

Depending on which situation applied, an individual’s reaction to products, communications, and even choice of media ought to be different, and this variable could be used for building segments. Everybody I spoke to agreed with the possible value of this concept, but nobody would invest money in it.

As we entered the computer age, it became possible to handle much larger amounts of information about people, and I got “fancier.” Not only did income status concern me, but also the individual’s level of expectation: aspirations about such things as product desires, political and personal goals, etc.

This also aroused a great deal of interest, but resulted in no money. In fact, for many years, the publisher of Time had me make presentations of the idea to him, one year even having me compile make-believe data to show what such a study might reveal and its possible importance to media. This also didn’t sell.

Meanwhile, I did studies throughout Europe for Caltex gasoline (a marketing combination of Socal and Texaco worldwide), and for several divisions of Chesebrough Pond, Alka Seltzer, and IBM. These studies gave me an opportunity to experiment with attitudinal questions that would later be incorporated into psychographics.

Suggestions from two of my then-employees, Louis Cohen and Larry Wolf, turned me in directions that worked ultimately by using variables (questions) with which advertisers, agencies, and media were familiar: what people actually bought, where (and if) they traveled, vacation habits, party and dinner customs, beverage consumption, product benefits sought, lifestyle and serving style and self-concept, media habits, and projective tests that revealed whether respondents were “appreciative” or “thankful” toward others.

MISSING LINK

I built segments with three classes of variables–responses about lifestyle (or serving style), self-concept, and benefits sought. These seemed most to reflect what groups of people had in common. These predicted, quite accurately, who were and were not early new-product buyers. This was one of the dependent variables that earlier attempts to profile people did not have.

The first study was sponsored by Time, using depth interviews. This research led to presentations at the annual World Association of Public Opinion Research (WAPOR) conference in Williamstown, Mass., and the Dublin (Ireland) conference of WAPOR in 1965 and 1966, respectively, and to a presentation to the AMA’s New York Chapter later in 1966. My papers were titled “Beyond the Demographics.”

The long voyage from an idea to a research project took me from 1948 to 1965, with a quantitative investigation sponsored by Holiday magazine, using segmentation questions found useful in the qualitative work.

Interestingly, when I held demographics and socioeconomics constant, great differences in attitude and behavior existed that could not be learned in the usual media studies. Using a two-segment model of consumers (creative and passive to rep-resent, respectively, those who did and did not buy lifestyle-changing new products), I found that there were important differences even in such demographically and socioeconomically similar media audiences as Time and Newsweek. There were more creative consumers (early new-product purchasers) in the Time audience than in the Newsweek audience.

Probably the most important technological advance in the first 20 years that led to the development of psychographics was the computer. Simultaneous use of three different classes of variables to construct segments is accomplished by a clustering program, something that couldn’t be done before high-speed computers. For psychographics, I prefer the Q clustering program, actually an inverse factor analysis, to form segments. My preference for Q is that it shows, much more than other methods, what contributed to segment formation.

The second most important advance is the use of what can best be called “special profile information” to form psychographic groups. One set was developed by Douglas Tigert of the University of Toronto in the 1970s. It involved what he called AIO: attitude (and activities), interests, and opinions.

Read the entire article at http://polaris.umuc.edu