Standing Up for Audience Targeting

 

Last week, John Mracek, the CEO of NetSeer, commented that audience targeting is overrated and touted the benefits of contextual targeting. While I can appreciate that early-generation audience targeting lacked scale and performance causing industry-wide frustration, that was three years ago. At that point, audience targeting amounted to contextual-consumption data and the data markets of today were non-existent.

Fast forward to today. Much has changed although many solutions are still incomplete. Successful audience targeting requires an entirely new solution, as well as a fundamental shift in the way we think about audience and data. Opposed to contextual platforms, which have existed for nearly twelve years, true audience targeting is still in its infancy. Right now successful execution requires access to diverse sets of data that haven’t been widely available until recently, so it’s easy to understand why most people still believe that scalable audience targeting beyond context is unachievable.

However, to say that data is the new black is to say that having the opportunity to make informed decisions is in style and will come to pass. Utilizing data effectively helps contribute to better business decisions overall. That’s unlikely to change as time goes by and data becomes more integral to our businesses. While the term “data” is used quite loosely, user data can be used for much more than just targeting.

For example, data should be used for segmentation so that advertisers can determine optimal messaging strategies. Data should also help drive a more efficient RFP process, ensuring the most responsive audiences are clearly communicated rather than stumbled upon by optimization happenstance.

To be sure, when it comes to data it’s important to acknowledge that there is no silver bullet; there is no MVP of data. No single data type or source will work for all brands or meet all campaign objectives. In many cases, context is a valuable data point, but it’s not any more or less valuable than any other data point. In some instances, it will work and in others it makes no difference. Rather, context should be viewed as just another dimension of a user, and effective data strategies are predicated on gaining as close to a complete understanding of that user as possible, via the aggregation of a large and diverse set of anonymous user-level data.

Contrary to Mracek’s opinion, audience targeting is actually quite scalable more often than not. It just takes investment in the right infrastructure, combining data aggregation, media fulfillment, and predictive modeling with the right organizational alignment. The ideal platform must be purpose built to aggregate, organize and normalize billions of data points across a centralized database of unique users, borrowing many design principles from direct mail that deal with high dimensionality. It must be deeply integrated into the ad server to understand why the ad was served to begin with and to close the loop by analyzing outcomes. Scalable supply and demand inputs are also a must — without them, it’s garbage in, garbage out.

Additionally, audience targeting and brand safety are not mutually exclusive and should be thought of as highly complementary to one another. Optimal campaign performance is derived from the ability to align data, inventory and creative; with greater alignment leading to greater performance. Ensuring the protection of brand safety can be supported by a disciplined business development practice, as plenty of unsold inventory is consistently and readily available on large (non-UGC) publishers every day. If audience targeting leads to the misalignment of brand and content, then that falls squarely on the shoulders of the buyers and the structure of the buy, not an inherent flaw in audience targeting as a practice altogether.

There are many misconceptions about audience targeting that are pervasive throughout this industry. While some may be justified, most of what I read last week was not. Audience targeting can stand on its own and when executed properly, it doesn’t cause risk to advertisers looking for brand-safe, quality environments for their campaigns. In order to better understand how to engage in optimal audience targeting, however, we need to think about data differently. The optimal solution provides a greater understanding of the holistic composition of consumers, and context is just one of the many data points that need to be taken into account. As more companies develop the tools to properly address this, hopefully we can put many of these misconceptions to rest.

Michael Katz is CEO of Interclick, an audience-targeting company. Follow him on Twitter @mkatz_ic.

 

 

https://digiday.com/?p=3130

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