In "Evolving Toward Targeted Display Advertising," I took you on a semi-anthropologic journey through the stages of growth toward a fully evolved behavioral display advertiser. The journey began with Homo Webilisite, "Web Site Man" and covered the following stages:
Keyanderthal Displayis had learned how to place his cave paintings (display ads) on others' cave walls (Web sites) to extend the reach of his messages. Let's move to the next stages in the digital evolution.
Adnetworkus Cro-Magnon: Ad Network Man
With his ability to walk upright, Adnetworkus Cro-Magnon had great mobility. He traveled to hundreds or thousands of peoples' caves, negotiating the right to place his messages on their walls. He quickly realized that he could also carry his friends' messages with him, taking a part of the fee they paid to Web publishers. This gave him and his advertisers incredible reach and allowed them to put their messages in front of millions of people. The ad network was born. During this stage, dancing behaviors were first exhibited as well.
Advertisers, however, began wondering exactly where their ads were being displayed. They began to get reports that their ads were appearing alongside unsavory content, potentially doing more damage to their brand than good. The ad networks moved fast, allowing their advertisers to choose which sites their ads appeared on. Some created premium ad networks, weeding out sites that didn't fit their advertisers' ideals.
The advertisers, still holding the ancient DNA of their Keyanderthal Searchilis ancestors, remembered the times of search advertising, when click-through and conversion rates were high. The ad networks had expanded the advertisers' reach but could not equal the returns of search. To battle this, new ad networks emerged, assembling smaller but more targeted niches of related sites, hoping to provide search-like returns.
Display ads' relatively poor performance put downward pressure on the prices publishers could charge. Site owners wanted more control. A mutation, Exchangus Cro-Magnon, emerged. Ad exchanges allowed publishers to work directly with advertisers to sell their inventory, finding better matches, potentially at higher rates. A worldwide Ice Age (the recession) seemed to have thwarted both publishers and advertisers in their search for better returns.
Nonetheless, Adnetworkus Cro-Magnon had tasted the possibility of marketing to millions and was restless to evolve to the next step.
Homo Pixelus: Behavioral Man
With an expanding brain, in the form of ever-cheaper storage and processing systems, Homo Pixelus had the capacity to take in and sort through large amounts of information. He began watching as people visited caves in his network and gave them cookies to eat. He then went to the cave owners, telling them to watch for cookie crumbs on their visitors' clothes. Cave owners would use this as a sign to put out messages specifically targeted at these cookie-dusted prospects.
Behavioral targeting companies monitored the sites the surfers visited, collecting large amounts of data on them. They tagged surfers with browser cookies and used them to monitor potential prospects' movements from site to site, estimating each surfer's interests. This gave Homo Pixelus the ability to target his ads and control the number of times a specific visitor saw his message.
It was with the most innocuous-sounding of instruments, the pixel, that amazing amounts of information could be learned about each visitor. This information was stored in giant databases for ready analysis. A variety of behavioral technology vendors offered numerous ways to mine this data and made it available for targeting.
As behavioral advertising companies and publishers began to share what they knew about each surfer, concerns about abuse of this information arose. There is evidence of the brief emergence of a mutation called Homo Bigbrotheris, but he appears to have been cast out of Homo Pixelus villages and eaten by Governmentasaurs before fully evolving.
Homo Optimizapien: Optimization Man
Both ad networks and behavioral targeting technology companies then developed sophisticated ways to slice their data, including systems that learn from interactions with Web surfers, offering increasingly better returns. Homo Optimizapien has clearly left the Stone Age.
Homo Optimizapien had discovered the ability to dynamically change the messages he displayed based on the wealth of information available in his databases. Dapper can literally scrape the product offers from an advertiser's Web site and stage these out to the ad networks with little interaction from the advertiser. This is great for companies that had many products or frequently changing offers.
Tumri assembles ads from a selection of headings, backgrounds, images, offers, and more. It's the intelligent display equivalent of a multivariate test, making it possible to try hundreds of combinations of behaviorally targeted ads without creating hundreds of ads.
Teracent provides an ability to design intricately dynamic ads that intelligently shift based on the data available about any network visitor. It uses a special tool, appropriately called Darwin, that lets agencies develop ad creative and link it with behavioral data. It has even begun to dynamically alter video creating the equivalent of moving cave paintings.
All these solutions provide the advertiser with feedback on which creative is working and which isn't. In addition, poorly performing ads could be automatically rotated out of circulation.
With the addition of these intelligent dynamic creative technologies, we are now approaching search-like returns on our display advertising efforts with a wider reach. Homo Optimizapien has optimized his message all the way to the right visitor's eyeballs. Have we reached the pinnacle of our evolution?
Future Evolutions: Siddha Socialis, or Social Media Man
Social networks offer a kind of behavioral data not available even to Homo Optimizapien: rich, detailed data maintained and updated by the prospects themselves. When we update our social media profile, share things, "favorite" content, and play games, highly accurate information is collected on our likes and dislikes.
This information can then be used to provide increasingly more relevant messages to us. As marketers and advertisers, we could achieve a kind of enlightenment in which we and our prospects work as one to ensure that only desired messages shine through. Unfortunately, the results of injecting display advertising into social networks have proved disappointing, with click-through rates even further from our search-like aspirations.
Given the quick evolution of targeted display advertising to date, I don't doubt that we will soon find a way to achieve Siddha Socialis status and beyond.
Thanks to Paul Knegten of Dapper, Calvin Lui of Tumri, and Chip Hall of Teracent for their contributions to this column.
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With 15 years of online marketing experience, Brian has designed the digital strategy and marketing infrastructure for a number of businesses, including his own technology consulting company, Conversion Sciences. He built his company to transform the Internet from a giant digital-brochure stand to a place where people find the answers they seek. His clients use online strategies to engage their visitors and grow their businesses. Brian has created a series of Web strategy workshops and authors the Conversion Scientist blog. Brian works from Austin, Texas, a place where life and the Internet are hopelessly intertwined.
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