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Sam Cox is chief executive officer at Milabra. Sam is an entrepreneur with multinational startup experience, as well as experience in Venture Capital investing. He previously worked at The Loughlan Group for two and a half years investing in technology and media ventures with internal capital, and providing strategic consulting to seed and venture stage companies. He founded a successful design & software firm in Canada and has consulted for firms in the UK, China, the United States and Canada. He graduated with his MBA from Cass Business School in London, UK with a degree in
strategy and completed his undergraduate degree in Art History, Chinese Language and Economics at Queen's University in Canada.

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Crossing the Content Gap With Visual Data

Written on
Aug 2, 2010 
Author
Sam Cox  |
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Crossing the Content Gap With Visual Data

pitfall_smallADOTAS – As an industry we’ve focus most of our targeting efforts on creating media and audience opportunities through contextual and behavior data. But now there’s a new variable — visual data, which can be added to your contextual and behavioral programs to increase audience engagement.

Visual data is the next key tool to help networks and exchanges get improved return for their customer’s ad dollars. Here are some examples on how visual data can add value:

Visually understand your advertisers creative

Analyzing the visual components of an ad will automatically help you identify opportunities where it will engage your audience and avoid opportunities where it will blend into the ineffective background. What does the ad look like? What images, objects, colors, and contrasts does it contain? Do you have versions? Sizes?

Visually understand the content environment where an ad is being placed

Analyzing the visual content of target pages will automatically ensure the most effective ad placement and prevent the appearance of ads on pages with non-compliant content. What does page look like? What images, objects, colors, and contrasts does it contain? Is there a big photo in the middle? Is the background black, white, blue or green?

Know what your user base likes

Analyzing the visual data of ads and content pages automatically helps networks and exchanges understand what types of ads drive engagement. Do girls really like pink? Do boys really prefer blue? It is important to know what your users like, so you can give them what they want and grab their attention.

Contextual and behavioral data will always be very important pieces of the advertiser value chain but we need more data points to take targeting to the next level. The current data points don’t connect a user to a specific creative, campaign, or call to action, they just find the right places where there is an opportunity to connect. By adding visual data to the mix, we can to do a better job of maximizing those connection opportunities and increase audience engagement.

At this point, display advertising should work. It should work given the amount of contextual data and audience data available on the market today. The truth is, display advertising doesn’t work as well as it should because of an audience attention problem. Most sites are inconsistent and jumbled and we have to find a better way to place our ads in an environment that maximizes their ability to deliver campaign results.





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