Lotame

The online advertising industry at large is sprinting towards maximizing efficiency. Overall, the working theory is that smart aggregation and assembly of various technology providers will create a unique solution for display advertising, and one that combines audience targeting, procurement, arbitrage and media trade. However, if, as Randall Rothenberg, CEO of IAB, states: “technology succeeds in driving the cost of reaching the perfect audience down to zero” in his latest post titled “Is Marketing a Strategic Resource or a Procured Commodity?” then the industry might be fumbling towards false ecstasy, with “the same low costs, the same perfect efficiency, for doing the same exact thing.”

Allow me to explain. With all of the aggregation and consolidation of publishers, networks, and exchanges, in many instances, an overlap occurs with publisher inventory. Think about a typical web publisher in today’s ecosystem. Think about how many ad networks that publisher works with. Now think about how many ad exchanges those ad networks work with. Then think about how many Demand Side Platforms those ad exchanges work with. The result? The tail wags the dog: when you bid on an impression, in all likely hood, you are bidding on yourself, for the same piece of inventory. This overlap and inconsistency in many cases results in decreased efficiency.

Here at Lotame we call this concept “Macrotization” wherein you try and optimize results at the macro level but have built algorithms and processes that can’t ultimately be supported by the disparate supporting systems and components. Many of the components in these new advertising platforms don’t necessarily complement each other, even though it may seem as if they do, and complementary buzzwords often connect ephemeral dots that don’t belong. In time, the foundation for macrotization will settle, but for now, tremors still abound.

The truth is, there are few companies out there that successfully manage all pieces of the “macrotization” process. Those that can will deliver true efficiencies for their clients because they can seamlessly connect and control all pieces in the value chain—from audience identification through media delivery and resulting insights—in a completely transparent manner.

The world will never be the same. Our society used to build machines and parts, in factories and in assembly lines. Today, our society builds computer programs and data bases, on laptops and in many cases, from anywhere around the world. People and businesses are becoming more efficient. They are working smarter, not harder, because they are beginning to leverage the most valuable employee of all: Data.

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Take for example the airline industry. Consider all those times you got bumped off of a flight, rescheduled, canceled, or offered money to take a different flight. We’ve all been there and it always happens for a reason. This reason is that airlines try to prevent the loss of business and in doing so, they look at dozens of consumer driven behaviors such as how long you travel for, how many weekend flights you take, how many return flights you take, how many flights you take during the week, if you are a frequent flier, and the list goes on. All of these individual data points are used to inform a business decision. The decision is objective. The decision is data driven.

But what happens when we can make decisions using even more data points? Much more data points? Literally, hundreds of thousands if not millions of data points, and did I mention, in real time?

Welcome to the Data Renaissance. Thanks to increasingly efficient and scalable technologies like solid state drives, mobile devices, and cloud computing, the possibilities of data analysis are endless. I mean, just think about how much time we either spend online or connected to a mobile device. This has tremendous implications from travel, health and fitness, to finance, education, and media and the best part is, we haven’t even scratched the surface.

Like I said before, the implications here are huge. Many companies recognize the need to have these comprehensive data sets while having ways of analyzing that data. The digital media and online advertising industry in particular are both in a unique place since their very foundations are dependent upon these high growth technologies; digital devices and the Internet. In this space, companies are racing to a holy grail of advertising where they can leverage millions of individual consumer behaviors to inform brand engagement opportunities and purchasing decisions. Unlike the airline industry, online advertisers can leverage millions of data points instead of those “dozen,” and if done correctly, the consumer experience will be better than it’s ever been before. Everything will matter. Everything will be relevant. We will all become more enlightened and informed to things that interest the most because these new technologies are launching us into the very early, but still uncharted, data renaissance.

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In his blog post over at GigaOm entitled “One Size Doesn’t Fit All When It Comes To Online Recommendations,” Darren Vengroff writes about 4 different product recommendations approaches, all deeply rooted in the smart use of data. This is very similar to some of the processes that can be employed when it comes to making decisions about which advertisement to show, and whom to show it to, with the aid of a data driven ad targeting platform:

• Segmentation, which divides users into groups based on characteristics like age, gender, and geographic location;
• Collaboration, which starts with an individual and attempts to locate others like them;
• Personalization, which relies on a user’s prior actions to determine what they are likely to do next; and
• Similarity, which starts with products, rather than users, and models relationships between them to drive recommendations.

In our business at Lotame, we have found that ad campaigns don’t have to be reliant on a single approach, and at times it may be best to combine different approaches simultaneously. Additionally, we have found that other approaches to use data that revolve around some of the unique social data that Lotame collects.

Darren is chief scientist at richrelevance. Previously, Darren was CTO and co-founder of Pelago, principal engineer at Amazon.com, and a vice president at Goldman Sachs. The entire article, with deeper definitions of each of the four approaches, can be found here.

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• One Size Doesn’t Fit All When It Comes To Online Recommendations (gigaom.com)

A recent study on users with Travel interests within our publisher partners showed that 61% of travel-interested users were female, and over one third (37.3%) were between the ages of 25 and 35. Additionally, 3 out of 4 travel users have interests in arts & culture-related content, such as art, crafts, dance, literature, and theater.

Additional Findings can be found by viewing the full report on Frequent Travelers. (Download the PDF here for free) We sampled approximately 67,000 individuals in our Co-Op who fit the description “Travel Enthusiasts,” users who reported interests in travel or demonstrated interests by sharing, posting or discussing travel related content.

An archive of additional reports can be found here.