Unless you’re a professional poker player, chances are that people can tell a lot about your mood just by looking at your face. After all, every furrowed brow or slight frown speaks volumes as the human face’s 43 separate muscles constantly communicate with the world around it. Recently, researchers have developed technology that can analyze all those muscles in detail, potentially unlocking the mystery of the many emotional cues hidden within our faces.
This information is especially interesting to a number of marketing companies that want to use facial analysis to learn more about their customers. Affectiva, for instance, has amassed more than 1,400 clients over a six-year span thanks to its ability to generate hard data by studying faces. In a typical test, a person will sit in front of a computer and watch a commercial or handle a particular product. The small camera on the computer records their interaction while Affectiva measures the subject’s face against its database of more than 2.5 million mugs. In fact, the company uses 7 billion “emotional data points” to track the subtle similarities in people’s expressions.
There are also many distinct differences among our faces, especially when factors like age and gender are taken into account. “Women tend to smile more than men,” said Affectiva’s chief science officer Rana el Kaliouby, “and they smile longer too. Older people tend to be more expressive than younger people.” Once these parameters are all set, company researchers track their subject for signs of amusement, excitement, boredom, displeasure, or any other emotions that show their level of interest. Although Affectiva is not yet profitable, its method of data collection has already brought about a number of competitors. In order to stay ahead of this growing pack, Affectiva plans to branch out beyond market research into fields like political analysis and education. The company also dabbles in a few non-profit pursuits, using facial recognition technology to study autism and other cognitive conditions.
- Why would marketers be interested in using facial analysis research?
- What difficulty will marketers experience in interpreting facial analysis?