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Overcoming the Challenges of DCO

By Austin Freeman

August 15, 2017 at 10:26 AM

In part 1 of this blog series, we discussed the ease of using Dynamic Creative Optimization (DCO) to create personalized marketing. For example, showing an ad for rain boots on a stormy day in Boston while simultaneously showing sunglasses to a consumer in Los Angeles. This second post examines the recent evolution of DCO, including some of the challenges involved with traditional DCO vendors, and how RevJet allows marketers to overcome them.

Historically, Dynamic Creative Optimization (DCO) has been thought of as when the creative team creates a single template for an ad and sets up a rule that says, “show everyone in my retargeting pool the product they looked at while on my website.” Or when they ask for “hundreds of ads built using different combinations of these 20 backgrounds, headlines, and calls to action.”

While you can serve many elements (e.g. text, images, offers) within an ad, you’re still working within the framework of a single ad template or concept. DCO answers the question: “How can I get the right product in front of the right person?” but doesn’t consider the best ad concept, or best way to present the product. Unless you are experimenting to determine what are the optimal ads for your users, you won’t know which presentation and layout is best.

Creative Superpowers graph.jpgWorking on RevJet’s Ad Creative Operating System is different. RevJet’s proprietary creative experimentation methodology identifies the statistically significant best-performing ads based on actual performance data. Instead of guessing which ad creatives are likely to succeed, RevJet lets your audience decide and lets you reap the benefits.

Some DCO vendors take dozens of headlines, backgrounds, and buttons, and use them to dynamically produce programmatic creative which is run in hundreds of side-by-side competitions. While this may sound like a valuable approach, it actually wastes huge volumes of valuable ad impressions on failing concepts before they can achieve the statistical relevance to be paused. With that many ads, each vying for a limited number of eyes, it takes an eternity to get enough impressions to definitively find the best ad.

A similar potential pitfall of DCO is the temptation to over-personalize an ad. With so much demographic information available, it is tempting to try to make the perfectly personalized creative for each individual customer. In this case, it is possible to create such hyper-personalization that each segment doesn’t receive enough traffic to ever actually see the ads.

RevJet helps users avoid these pitfalls. On the platform, ad creatives are automatically enrolled in perfectly designed experiments that can be optimized against any metric. This could be anywhere from online purchases to completed video views, making it easy to optimize both direct response and branding campaigns. RevJet is the only platform that drives continuous performance improvement by removing underperforming creatives as soon as they are identified.

dco_5.jpgDCO is most effective when you have large segmented audiences that you want to use for personalization. It is important to keep in mind that you need to plan advertising campaigns well in advance in order to incorporate all of your data segments. Depending on the system, this could take up a lot of time and resources.

RevJet breaks ads up into smart elements, allowing it to recognize and differentiate between headlines, graphics, backgrounds, and logos. This stands out from other systems because the RevJet Operating System goes beyond simply recognizing a label. It actually understands the different elements in an ad without relying on your naming conventions, enabling smarter trafficking and testing by selecting placements intelligently.

This feature means that once you’ve created the initial ad in a campaign, you can pull the elements into the RevJet Operating System, allowing personalization immediately and as often as necessary. You can reorient and resize images, personalize text, visualize the ad, and much more. The ability to make these edits within the operating system means that what used to take customers 3-5 days now takes a few hours.

By identifying the elements in each ad, you can compare performance of individual elements and element types across all experimentation. With access to these insights, you can drill down into each creative’s individual elements to precisely understand what is driving performance. This allows you to develop a data-based playbook from your experiments in order to run extraordinarily effective campaigns moving forward.

Download the white paper, Radically Simple Personalization - Dynamic Creative Optimization (DCO) to learn more about how Dynamic Creative Optimization will benefit your business.