In my first post, I wrote about how advertising optimization allows marketers to increase ROI by shifting allocations between audiences, media types, and creative versions. Usually these three areas are optimized against direct response metrics: the click and the conversion. But the use of automated optimization should not be synonymous with a myopic focus on click and order counts. It is possible to optimize campaigns to do more than generate clicks and online sales. If you can measure the persuasive, memorable, emotional impact of an ad — impact which clickthrough rates and conversion rates alone does not capture — you can optimize campaigns to better build brands.
But first, let me give the click it’s due respect. For one thing it’s immediately measurable. Brand study survey results might not be available for weeks, but the click is measured instantaneously. Second, attribution is clear. The adserver knows which exactly which site delivered the click, so its straightforward to optimize to deliver more clicks. Lastly, there’s no selection bias since every click is captured.
Its difficult to find a branding metric as easy to incorporate into optimization models as a click, but here are some other metrics that agencies can use to optimize branding efforts.
1) Ad Exposure Time — One important difference between ad impressions is ad exposure time. Lotame has published a white paper, “Time Exposure by Banner Size,” that found that 300×250 ads were visible for an average of 13 seconds, compared to an average of 5 seconds for 728×90’s and 2 seconds for 160×600. In addition to creative size, ad exposure time varies greatly by site type. Banners on blogs and social network pages will have much lower exposure time than a companion banner on a video site. VideoEgg recently released their floating Twig ad unit in part to address the challenges that blog publishers face given the low ad exposure time.
All else being equal, an ad that is visible to the user for 20 seconds should have a larger impact on brand health than an ad that is visible for 2 seconds. This type of information should be incorporated into advertisers’ impression bidding strategies.
If a planner is building a branding campaign, they should be able to target sites in their planning process where the ads are visible for a longer period of time. At the very least, they should be able to ensure that if their advertiser’s name and logo only shows up in the 7th second of animation, that each impression is visible for least 7 seconds on average. In a buying platform, planners should be able to enter in time exposure rules by creative. There also needs to be a comparison between value (average ad exposure time) and price (CPM). This is where planners need to rely on the automated optimization power of a buying platform.
2) Time Spent on Landing Pages — Not all clicks are created equal but just as click traffic for DR campaigns can be differentiated by conversion rates, clicks for branding campaigns can be differentiated by time spent on the site. Optimizing audience targeting by clickthrough rate is a risky strategy when studies have shown that a small majority of users generate the majority of the clicks and that display exposure still has a significant impact on those who don’t click. For branding campaigns, time spent on the landing page is a much more meaningful metric for understanding which audience segments are interested in engaging with the brand. By incorporating time spent metric into automated buying platform, an advertiser can pursue a pay-for-engagement buying model on any type of media with any type of creative assets.
3) Visits to Advertiser Homepage — A consumer who doesn’t click on an ad may still visit the advertiser’s homepage to learn more about products. Measuring the number of impressions it takes to generate a visit to the homepage is good measure of ad effectiveness. This metric is especially important for multi-channel retailers where online advertising drives consumers to do further online research but end up buying in-store. The impact of online advertising on these particular consumers is never captured by online click and conversion metrics.
There will never be an algorithm to spit out innovative, memorable integrated marketing programs, but marketers still have the opportunity to use automation, optimization, and data to build brands.
[...] Hills illustrates the complexities of optimization in his blog post, "Optimizing Beyond Click and Conversion." Hills suggests that useful metrics for brand-conscious marketers could include ad exposure time, [...]
Interesting stuff. I think that getting the metrics right will open the door to much more interesting planning & optimization.
We've toyed around with using simple one-question surveys to measure brand awareness (i.e. pre- and post-exposure unaided awareness, aided awareness, etc). Seems like you might be able to use these to measure effectiveness on an automated basis if you made it easy enough.
Any sense as to whether there's a standard “question” that would work for most advertisers?
I think you would have to create a different question for each each advertiser's campaign based on the creative. I can't think of of a question that would work across multiple advertisers and multiple campaigns. But I agree with you that brand awareness would be a good starting point.
One-question surveys must have some role to play, but I haven't figured it out yet. I think it would be difficult to build up a statistically significant sample to use surveys to optimize media or audience on a campaign by campaign basis, since there are so many different media and audience segments.
Although one-question survey data may not be rich enough for dynamic optimization of individual campaigns, I think a company could aggregate a large amount of survey data to build a proprietary model that incorporates the degree of banner blindness that occurs on different sites and different site categories. I think the lowhanging fruit is not measuring the brand lift among different creatives or different audiences, but simply identifying sites where people actually notice the ads.
I think you would have to create a different question for each each advertiser’s campaign based on the creative. I can’t think of of a question that would work across multiple advertisers and multiple campaigns. But I agree with you that brand awareness would be a good starting point.
One-question surveys must have some role to play, but I haven’t figured it out yet. I think it would be difficult to build up a statistically significant sample to use surveys to optimize media or audience on a campaign by campaign basis, since there are so many different media and audience segments.
Although one-question survey data may not be rich enough for dynamic optimization of individual campaigns, I think a company could aggregate a large amount of survey data to build a proprietary model that incorporates the degree of banner blindness that occurs on different sites and different site categories. I think the lowhanging fruit is not measuring the brand lift among different creatives or different audiences, but simply identifying sites where people actually notice the ads.
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Usually these three areas are optimized against direct response metrics: the click and the conversion…..
Так бывает. Давайте обсудим этот вопрос. Здесь или в PM….
Usually these three areas are optimized against direct response metrics: the click and the conversion…..
Весьма полезная мысль…
http://rel” rel=”nofollow”> Менеджер по рекламе. Менеджер по проектам. Usually these three areas are optimized against direct response metrics: the click and the conversion…..
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Ой, не говорите.