Video Advertising Strategy: Audience Optimization

  |  May 9, 2011   |  Comments

Four areas for a winning video ad campaign strategy. Second in a series.

Video is an increasingly important online advertising channel for both branding and performance. In last month's column, "Video Advertising Strategy Part 1: The Metrics," we discussed how to choose the right combination of metrics for your campaign success. This time, let's look at how we can enhance the branding and performance of a video campaign using the latest real-time audience targeting and optimization tools. Video ads are highly engaging and much more expensive to deliver than traditional display ads; therefore, we need to be much more precise with our audience targeting approach.

Let's look at the following four areas for a winning video ad campaign strategy:

  • Optimization: The required component of optimization is to apply the same predictive learning process available in display to your video campaign. Predictive learning is incredibly powerful when combined with a real-time feedback loop of the user engagement and campaign success metrics. Predictive learning optimizes both the targeting and bid price paid when buying a video ad impression and the technology should come as an integrated part of your media platform (aka demand-side platform or DSP). The effectiveness of the optimization depends on the quality of the platform's algorithms combined with the type of success metrics fed into the system. Plugging in different real-time response metrics, such as ad engagement, advertiser website engagement, or brand survey responses will lead to correspondingly different optimization outcomes. Therefore, using the appropriate tools to monitor and understand the implications of these changes through in-flight analytics and data visualization is a must-have for maximizing video campaign performance.
  • Audience targeting: Custom audience targeting delivers the biggest gains in video campaign optimization. Over the past several months, an increasing amount of video inventory has become available through real-time bidding (RTB) exchanges. This increase in video inventory is a critical evolution for the industry that enables you to target your campaign specifically to consumers who fit the exact profile you're looking for. Whether the audience is defined by traditional retargeting data, offline customer relationship management (CRM) data, or third-party behavioral segments, you can now hone in on the right audience every time.
  • Frequency: Human brains are very sensitive to repetition. We are open to new information only the first few times we are exposed to it. As a result, every ad has an ideal frequency. Under-delivery will fail to build strong brand awareness in the consumer's mind, while over-delivery can turn those extra ad impressions into a negative brand association due to fatigue and annoyance. Managing your video campaign through a real-time media platform will enable you to quickly learn the optimal frequency for a campaign, but also deliver that optimal number through RTB and the enforcement of universal frequency caps.
  • Think cross-media: Cross-media optimization is the new "black" in online advertising. The reason is simple: combining data and intelligence across multiple media channels is a force multiplier. Suppose you already know what keywords work for your SEM program. Perhaps you also learned what ad placements and audience targets work for your display campaign. Then why not launch your video ad campaign with these as the optimal starting point? Better yet, connect the keywords pipeline and synchronize the audience targeting to your video ad campaign using the same audience platform, so that the cross-media execution is automatic and instantaneous.

Based on our research, messaging consumers through multiple channels is significantly more effective than a single channel. Real-time audience targeting allows us to sequence ad messaging based on the ad impressions users already have received from across multiple channels. Combining this with insights gained from analyzing the conversion path of existing customers creates a powerful, multi-channel marketing solution for any type of campaign.

While video alone is not a "lower funnel" performance driver, it can still boost the performance of other mid- and lower-funnel channels, such as display and search. By monitoring performance lift on display and search through tracking tags on a brand's site, we can optimize user targeting on video channels based on this shared data. This means showing more video ads to the types of users who are known to convert more often via search and display after video ad exposure. In RTB language, this means bidding higher for specific users so that your ad message remains top of mind for the consumers who are most likely to be influenced.

To date, marketers have typically separated video from their campaign planning and execution for display, search, and email. But as online video matures, marketers are realizing the benefits that cross-media channel strategies and metrics can deliver for campaign performance. Because online video optimization is still very new, it's important to test, learn, and optimize as much as possible. Video ad metrics, along with video optimization strategies, are continuing to evolve and, consequently, so is the game. For marketers who want to stay one step ahead of the curve, applying optimization tools, real-time audience targeting, and a philosophy of continuous experimentation are the keys to success.

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ABOUT THE AUTHOR

Xuhui Shao

As Chief Technology Officer at Turn, Xuhui Shao focuses on the power of optimization, machine learning, and advanced analytics solutions in driving new business models, products, and services across all industries. Xuhui is responsible for architecting the machine learning and optimization technology to deliver the most effective data-driven digital advertising in the world. He is passionate about the dynamic online advertising community and works closely with industry leaders developing data transparency and consumer privacy protection.

For the last 12 years, Xuhui has practiced research and development in machine learning, statistical theory, and computational intelligence for Fortune 100 companies in various industries from banking, finance, online retailing, healthcare, insurance, marketing, and online advertising. As the lead inventor and co-inventor of three awarded patents in the areas of advanced analytics and optimization, Xuhui is a recognized expert in harnessing data and transforming analytics into actionable insights and optimization strategies.

He earned his bachelor's and master's of science degrees from Tsinghua University, Beijing, and his Ph.D. in electrical engineering from the University of Minnesota.

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