Video Advertising Strategy Part 1: The Metrics

  |  April 11, 2011   |  Comments

A look at the different measurement strategies available for video advertising and the pros and cons that are important to understand. Part one in a two-part series.

In 2011, video is evolving from a standalone marketing channel to an integral part of an advertiser's overall online campaign strategy. By harnessing the power of multi-channel targeting, advertisers can more effectively reach custom audiences as compared with taking a single-channel approach. The most successful campaigns target customers across multiple channels by using both display and video advertising to complement each other and drive overall ROI. And now that audiences can be targeted directly via real-time bidding (RTB) on ad exchanges, selecting the right metrics has become job number one when planning a new campaign.

The objective of any ad impression can be to drive either upper funnel (branding) or lower funnel (performance) activity. Because video ads are more engaging and typically are played to a captive audience, video has particularly strong potential for branding objectives. But how should you measure video advertising effectiveness and performance? In part one of this discussion, we're going to look at the different measurement strategies available for video advertising. Each has pros and cons that are important to understand and tailor to your specific needs:

  • Rating point: This is the traditional measure of broadcast video success, but does it work online? Rating point comes in the form of gross rating point (GRP) or target rating point (TRP) that measures the reach and frequency of a video ad. The advantage of being an absolute measure is that you can compare different ad campaigns directly. The problem is that the standard formula makes frequency and reach interchangeable. For online video, there's an optimal frequency for viewing an ad for every user and deviating too far from that optimal frequency - especially going over - can be very wasteful and even detrimental to a campaign. A frequency-capped GRP/TRP is the first step in the right direction. The ideal solution is a frequency-optimized GRP/TRP where deviation from optimal user frequency is discounted or penalized.
  • Brand perception survey: The approach here is to conduct random surveys on how people perceive the brand before and after seeing an ad. For online video it can provide real-time feedback on how well a campaign performs across different sites and demographics. The disadvantages of brand survey are mostly related to data collection. Surveys are interruptive and that's something that consumers - as well as website operators - typically don't like. This creates the devious problem of "selection bias." To put it plainly, only certain people respond to surveys and the answers depend largely on their motive for participating and how the questions are posed. These two factors are not things we want to measure but can easily influence the results. So while perception surveys have tremendous power, they also have to be designed and interpreted carefully.
  • Brand interactions: Brand awareness can also be measured by users' interaction with a brand including their clicks on ads, how long they watch videos, their engagement with rich media, or visits to the brand's website. Brand interaction metrics are real-time, user-level, and high-resolution. Therefore they can be statistically reported and algorithmically optimized to measures like cost per view (CPV). The benefit is that we can actually measure the effectiveness of various design and optimization tactics using user-level A/B tests. Integrating brand interaction metrics into exchange buying and audience-based optimization makes real-time brand optimization a reality.
  • Social monitoring: As social media becomes the primary channel for consumers to express their opinions, scanning these sites with keywords and sentiment analysis can measure the changes and trends of users' brand perception, as well as their attitudes toward competing brands. Social monitoring can measure share of voice among consumers and provide additional insights into one of the most important new media for brands. Overall, social monitoring yields an aggregate picture of the brand.

As we discussed earlier, branding and performance are not necessarily competing objectives. While branding is more powerful with video ads, performance results and campaign ROI should not be ignored. This is true especially when video ads are only one of the media channels in an advertiser's overall cross-media strategy. Here we should measure the impact that video has on the overall conversion volume and campaign eCPA. To accomplish this, two primary methods are available:

  • A/B test: This simple but highly effective approach is the user-based A/B test, where one user group is exposed to video branding campaigns (treatment group) and another user group that is not exposed (control group) are compared on search and display ad responses. The lift of video ads is then computed as the difference of responses (click rate, site visit rate, or conversion rate) between the treatment and control groups.
  • Attribution analysis: This is where things really start to get interesting! Probability-based attribution analyses can reveal the combined influence of user responses by multiple touchpoints across one or more media channels. A touchpoint is defined as any advertiser-driven user interaction, such as ad impressions, clicks, visits, or other activities. This particular approach is also called multi-touch attribution (New Year, New Attribution Model). Attribution reports allow a richer analysis of multiple dimensions and factors. It is a much more complex process, however, and one that needs to be handled with extreme care. When in doubt, always use an A/B test as a post-analysis validation tool.

To understand the true value of video advertising and leverage its full potential, it is important to adopt a holistic view about audience targeting and use the necessary toolset to track, store, and analyze the terabytes of data in a cross-media campaign. Consumers don't make decisions just over a single ad impression, nor are they isolated to a single media type. Understanding how consumers interact with your brand across search, display, video, and other media types offers many powerful insights - and specifically insights that can lead to actionable real-time marketing decisions. So how do you translate this array of actionable insights into a powerful multi-channel marketing strategy? We'll dive into those details in the part two of the video strategy discussion next month!

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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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