Ad Evolution: From Bear Claws to RTB

When it comes to tech there seems to be one thing everyone is talking about: Is privacy dead? Perhaps the industry best suited to teach us about privacy is advertising. This is because advertising is in the position of benefiting from the abundance of more personal data. This article is a brief history of advertising from prehistory to the modern day and discusses how it’s always been dependent on personal information.

Advertising in Nature

On a very meta level, advertising is part of who we are. More specifically it is part of genetics and natural selection. Therefore, advertising has always relied on personal information to drive its decisions. There are many traits that animals in the natural kingdom have acquired simply to show their healthiness. During mating season in the Galapagos Islands, male blue footed boobies pick their feet up and down in a dance. The purpose of the dance is for the females to see which feet have the darkest blue color. The darker the blue, the healthier the male, and the females allow the dark footed boobies to mate. The darkness of the foot color is personal information.

Blue footed booby mating dance

Humans 15,000 years ago used personal information when selecting mates as well. The shine in hair. The quality of teeth. The smell of a person. This too is personal information, used to drive a very important decision — will reproduction with this person result in a child with strong genes that will survive to pass on genes? And so on and so forth. Essentially animal decision making comes down to…will this action result in a higher or lower likelihood of healthy genes being passed on?

As humans became able to use tools, they of course used tools to make themselves more attractive to a mate. Some of the first jewelry was fashioned from shells and bear claws. These are signs that whoever is wearing the necklace has access to a food source. Which is a strong indicator that reproduction with said individual is likely to result in a healthy environment where genes are likely to pass on.

Whether or not the person wearing the necklace does indeed have access to food is another matter and more similar to the way we envision modern advertising. An individual could be very poor and weak and stumble upon a lost bear claw necklace. As soon as that individual dons the necklace, their appearance is changed. They are instantly more genetically attractive.

This can be similar to what people in Scottsdale refer to as “$30,000 Millionaires”. Young men who earn $30k a year, but lease or rent symbols of earning more — BMW, Rolex, etc. They buy these products because they know that their target (single…hopefully…females) will respond positively to. The brands that have spent budget so that you associate their products with wealth, and in part the person wearing the product.

From Who Wants to be a Millionaire — Answer at bottom of post

The Invention of Modern Advertising

Thomas Barratt (1841–1914) is accredited as the “father of [modern] advertising” because of the creative campaigns he ran for Pears, his father in-law’s soap company. Before Thomas, soap was just soap. It was a commodity. Thomas Barratt was the first person to make creative ads with artwork and copy based on a target audience he wanted to go after (high culture). In the ad below from 1885, you see the use of a testimonial from a famous London actress who has been using Pears soap for two years. Being a famous actress is a big deal (a lot of suitors aware of and interested in those genes). By using Pears soap, consumers are able to allow themselves to feel that they have those same attractive qualities as the actress.

Pears Soap Ad — 1885

The next evolution of advertising came about with Nielsen ratings in the age of television. Households bought televisions and consumed shows via the AIRWAVES! Remember in old movies there were antennae on top of televisions. In such a connected world it is easy to forget that before cable, there was TV via airwaves. Therefore people consumed TV shows broadcast via airwaves, but no one paid for the television content. This was paid for by the advertisers. It is an important note that, since the beginning of television there’s been a generally accepted principle that if the content is free then we will watch ads. The ads pay for the content.

However advertisers and content producers needed to understand what content was valuable. They needed personal information about viewing behavior. Remember that this was before the days of privacy concerns. A 1940’s, 50’s, 60’s, 70’s television set couldn’t report back which content was being consumed. Broadcasting was a one way street.

This is a different challenge than other industries had. If you made chairs or any physical product, you could measure consumption and demographic data. If you yelled from a rooftop with a loudspeaker, how would you measure who was listening? How would you know if people found it useful? How would you know if they came back again to listen? You didn’t.

Old School TV — circa 1950s

Measuring Advertising Effectiveness

The Nielsen company became the leader in addressing the challenge of gathering market feedback to programming. Nielsen selected thousands of television viewers based on geographic and demographic information. They would then provide these viewers a diary to record viewing habits. Some users allowed a “Set Meter” to be installed in their home. This device would record the data of the television — on and off, which stations, for how long. The device would send the data via phone line to Nielsen. Nielsen took that personal data and provided it to the TV production and advertising companies who used it to decide what kind of content to create.

While this statement is a vast over simplification, the area of television content and advertising was vastly unchanged since the 1947 advent of the Nielsen system through the 2000’s. This was a 50 year period of viewers consuming content without divulging personal information, unless you volunteered to be part of a survey. This was also a 50 year period of perhaps 15–20 television stations in total to choose from. After all it was difficult and costly to get research about niche markets, so shows were made to please large demographic groups.

The Rise of Digital Advertising

The rise of digital media changed the previous equation. Gone are the days when an unknown Nielsen viewer represented your viewing preferences. Now publishers and advertisers know exactly about your preferences. They know your age, sex, income, education, career, etc. They know which shows you start watching, stop watching, and continue to watch. They are also able to tie in cookies that show your browsing history from other websites.

This has caused a major change in the way content publishers and advertisers interact. Before the shift to digital, a content producer would tell an ad agency, “This show is targeting 30–50 year old men and women who are watching after putting their kids to bed.” Ad agencies would then say which ads were seeking to be seen by that demographic. A bidding and negotiation process would ensue. The ad that won would play on that show for a predetermined amount of time.

Online bidding today takes 200 milliseconds

Today this is changed. The ad bidding process is much faster and much more personal. Online ad bidding happens all the time and in milliseconds. When you go to a website of a major content publisher (CNN, NY Times, Oprah, The Onion, College Humor, etc) you will see ads. When your computer begins to load the website, in less time than the blink of an eye, the website tells advertisers what your demographic and behavior make up is and the content of the website. Ad networks will then place bids to have their ad placed in front of you. A winner is chosen. This all takes place in under 200 milliseconds. It takes 300 milliseconds to blink your eye. The result of advertisers knowing your personal web surfing habits is a more personalized browsing experience.

In order to process all this information machine learning and artificial intelligence are being applied to process these large data sets. This will be the subject of the next post.

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