Facial Recognition Mall Advertising


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How It Works


Using facial-recognition software in mall advertisements is a new and innovative feature that increases the effectiveness of out-of-home advertising. Generally, the advertisement itself is on an LCD screen (also known as a Smart Screen) with a camera system containing software to analyze demographic information about the viewers of the ad. There are different systems available for the needs of different clients. For example, there is a dome shaped camera created by the company TruMedia that simply counts the number of individuals in the area of the ad to measure potential exposure. Trumedia also offers high resolution, wide-angle cameras that can gather information such as the age and gender of individuals who looked at the ad, and how long the ad held their attention. This type of technology also has the potential to alter the ads shown on the Smart Screen based on the age, gender, and potentially race. (Farrar, 2009).
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Benefits


There are many benefits that come with using facial-recognition software in advertising. Most importantly, with this technology, advertisers can finally receive feedback from out-of-home advertising. “Until today, out-of-home media based advertising was suffering because it was an unmeasured media, and as an unmeasured media, it was undervalued by the advertiser," said Rabenou, CEO of TruMedia. (as cited in Farrar, 2009). With this type of technology, it is possible to measure much more accurately the return on investment for mall ads. The software provides raw data and then analyzes it to provide all kinds of useful information to advertisers. For example, TruMedia’s facial-recognition software can help in determining prime locations for maximum audience exposure, analyze consumer demographics based on the time of day or day of the week, as well as gauge customer reaction to display change. This type of information helps the advertiser effectively reach the audience it intends to reach. (TruMedia, 2006).

In addition to optimizing advertising efforts, facial-recognition software is useful in evaluating the effectiveness and reaction to Smart Screen type advertisements. Factors such as dwell time (the amount of time spent lingering near an ad), number of Actual Impressions (The number of people who look at the display), and length of impression (time spent looking at the actual ad) are useful to advertisers because they let them know how well their ad is working, and whether it is eye-catching enough. (TruMedia, 2006).

This can provide unbiased data to the creative team about how well their campaign, slogan, or imagery resonates with consumers. Finally, facial recognition software provides data about WHO is looking at the ad. Age can be broadly determined by teenager, adult, or senior citizen, and gender can be effectively determined 80- 90% of the time. (Ramde, 2009). This can be helpful in evaluating how well the ad reaches a specific audience, as well as identifying secondary markets that may have been overlooked.

The most important thing about the demographic data collected by this type of software is that it is unbiased. Since it is being done by computers instead of people, time measurements are inherently more accurate, and no one is overlooked as a result of human error. Also, since facial-recognition software does not require consumer cooperation, the data is more accurate than something like a survey, which is self-reported and therefore prone to inaccuracies and bias. (Barnes, 2008).

Limitations


Although there are many benefits in using facial-recognition software in mall ads, there are also some limitations to this type of media. The technology is still relatively new, so it has not reached its full potential to measure demographic data. Age groups are still relatively broad, and the software cannot yet identify race or ethnicity, which would be useful to marketers. Ramde (2009) stated, “There’s moderate demand for ads based on ethnic information, but the companies acknowledge that determining ethnicity is more challenging than figuring out gender and age range.” Also, facial-recognition software only identifies consumers by outward appearance, which is not very in-depth, and in many cases, unreliable. The old saying, “You can’t judge a book by its cover” applies in this situation.


Cost


Since face-scanning software itself is such a new concept, it was difficult to assess cost. However, IMC New York, a company that specializes in interactive out-of-home media offers a “Pay-Per-Impression Business Method,” according to its website. (Studio IMC, 2007). Adspace is a company that broadcasts advertisements on LCD screens in different settings across the country such as airports, malls, and sports arenas. Even without face scanning software, a 15-second video ad can cost up to $765,000 monthly. (Ramde, 2009). With the high cost of the video ads themselves, “advertisers expect rigorous information about who sees the spots — information that face tracking can now provide,” stated Ramde. (2009). Clients are essentially receiving feedback from the ad itself, information that can and will save them money in the long run by allowing them to allocate their funds in an optimal way.


Effectiveness


Mall advertisements in and of themselves are a very effective, yet often overlooked medium with a relatively low CPM. Products like TiVo and On-Demand make it easier for consumers to skip television commercials entirely. After internet, out-of-home media is the fastest growing segment of media spending. Michael Hudes, director of global digital media at Clear Channel Outdoor stated, “The beauty of out-of-home...is it provides lots of reach, but with digital you can make it more targeted.'' (Hamp 2007). The main problem traditionally associated with mall or out-of-home media is a lack of reliable metrics, however face recognition technology is gradually changing that. Malls in particular have a large female and teen audience. Also, since people are already shopping at the mall, they are more receptive to messages persuading them to buy something. (Groover, 2005).

Privacy Issues


Face-scanning mall seem like a great opportunity for marketers, however there are certainly issues of privacy for the American public. Most people think of science fiction like Big Brother, and the movie Minority Report which is unsettling to say the least. (Patel-Predd, 2009). Critics of the software claim it’s an invasion of privacy. Harley Geiger of the Center for Democracy and Technology is quoted in the article, “Signs of the Times: Smart ads that watch you watching them,” as stating that this type of technology is, “the beginning of surveillance for profit.” (Farrar, 2009). Another scary thought is the fact that the software used by TruMedia was originally developed for the purpose of government surveillance. TruMedia insists that it only records data, not personal information. Even so, the idea that you are essentially being watched is not something the public is comfortable with. (Farrar, 2009).


Audience


The use of facial recognition mall advertising is especially effective when targeting women and teenagers, who tend to spend more time at the mall than other demographic segments. (Groover, 2005). However, the ability to change the screen based on demographic qualities picked up by the software allows advertisers to tailor the message based on who is looking at it. Studies have shown that advertisements in malls are very effective, especially with teens. This is because people at malls are already in purchasing mode so they are very receptive to advertisements, especially when they contain information about sales and stores that are actually in that mall. Also people repeatedly visit the mall, so that ups the frequency for this media.



References




Barnes, R. (Ed.). (2008). Achieving Viable Metrics. Marseille, FR: Cleverdis Publications.
Farrar, L. (2009, March 11). Sign of the times: Smart ads that watch you watching them. CNN. Retrieved from http://www.cnn.com/2009/TECH/03/11/db.smartsigns/
Groover, J. (2005, January). Mall as media. Shopping Centers Today. Retrieved from http://www.icsc.org/srch/sct/sct0105/index.php#at
Hamp, A. (2007, January 29). What are online giants doing in out-of-home?. Advertising age, 30
Patel-Predd, P. (2009, January). Loser: The ads have eyes. IEEE Spectrum. Retrieved from http://spectrum.ieee.org/consumer-electronics/gadgets/winners-losers-vi
Ramde, D. (2009, January 30). When you watch these ads, the ads check you out. USA Today. Retrieved from http://www.usatoday.com/tech/news/surveillance/2009-01-30-ad-privacy_N.htm
Studio IMC. (2007). IMCfaceplate tracks views. Retrieved from http://www.imcfaceplate.com/
TruMedia Technologies. (2006). TruMedia- Audience measurement systems. Retrieved from http://www.tru-media.com/default.asp