If you are in the business of buying or selling media and work through networks or automated buying of any kind, you may know the "white list." It's a common practice in digital media buying, where advertisers are able to pick an exclusive list of publishers on which to run, making such selections before a campaign has even started.
At first blush, this seems an easy tactic or right of sorts. After all, why wouldn't you want to choose the company you keep? It feels like a measure of brand protection.
Why Use White Lists?
However, brand reputation management aside, there are valid business reasons to adopt the white list approach. If you know the typical audience associated with a particular publication or app and this profile is in line with the type of consumer you believe matches your offer or message, determining your placement by selecting only publishers with presumably aligned audiences makes sense, right? It feels like a measure in controlling your consumer destiny.
Another reason to predetermine or limit where your digital ads run might be a strict focus on product and/or content relevance. For example, if you sell baby products, it seems prudent to only place your ad with mom and/or child oriented publishers, so your ads will be nestled in a predisposed context, where the audience reading the content or hanging out in the community is inclined to what you offer. I could continue to outline similar business philosophies for advertising via exclusive or white list placement, but in every case, including those above, when one takes this approach, there is also a business risk. A performance handicap is inherited before the campaign even begins.
The White List Handicap
In each one of these cases, or any time you restrict opportunity before you actually know what will or won't work (or what will work best), you hinder your ability to achieve your greatest success and optimize it. That doesn't mean a white list approach doesn't or can't work; it means that if that is the approach you take, then you will actually never know for sure what will work best. In the age of testing and learning, you don't know what you don't try.
If there are shortcomings to this approach, why do so many marketers continue it? And what is the better approach? As with all acquired "best practices," marketers continue this one because they've seen it work in the past. Besides being a proven (if limited) strategy, this tactic of executing on predetermined exclusionary targeting criteria was born in an era when it really was the best approach. Think about broadcast media buying: how was an advertiser to decide when to air a commercial? Knowing the make-up of the audience watching a particular show was, in its time, a brilliant way to buy and place one's media.
As this same "know and align the audience" approach moved into other channels, we continued to witness success. If we wanted to send an offer in the mail, we quickly learned that buying lists of names, constructed based on people's magazine subscriptions, resulted in a much higher response or engagement rate than mailing everyone. This seems obvious now, but back then, it was a revelation; an acquired best practice. Yet, even then, as we bought and marketed to that select list of prospects, we knew we were missing folks. We knew there were consumers likely interested in our product or offering who did not subscribe to our select publications. We had a sneaking suspicion there was a better way.
So, as we moved into the digital desktop world, and the number of publishers increased by multiples in relationship to the number of shows, programming blocks and print publications, so did the spread and variation of type and quality of placement. While the technology emerged to allow for more complex placement decisions and a faster feedback loop, an associated sense of needing to better control ones exposure also increased.
Is White Listing Just a Legacy Tactic in Mobile?
Now, as we move yet again into the uncharted waters, and the exploding new world of mobile, we've brought along our once-strategic wisdom (now more a "safety net" approach to media buying/placement than a proven tactic) and we have ported along this outdated practice of white listing.
White lists are often touted as brand protection, but the reality is brand protection is more than adequately addressed with a black list approach. This is what I'm advocating now: select who not to run with instead.
If you run around with thugs, folks will think you're a thug. Still, running around with the BMOC (big man on campus), who looks good but may not have the right substance, may or may not make folks like you more. The BMOC is always overrated, writing checks based on looks that his (or her) personality simply cannot cash.
The Black List as a Discovery Tool
Once you've employed a black list--a list of places you do not wish to run--and understand the reasons for those choices, you can and should open yourself up to anywhere and everywhere else you might find your best consumers and prospects. You're doing this now without presuming you know better, before you do know better. You're allowing yourself discovery and open to new opportunities that might play out well in testing.
The beauty is, in the mobile media world, with the right technology and strategy in place, you can learn and know--in real time--where to find your consumers. You can learn when they want to hear from you, and what will pique their interest most. This is most likely to change from day to day and rapidly evolve, as we all adopt a more mobile lifestyle.
Today's placement strategy won't and shouldn't stay fixed in time to serve as tomorrow's strategy.
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Writing on mobile and mobile insights, Shannon E. Denison brings a blended background of time spent providing data analytics services to Fortune 500 companies, and on the client side as a frequent user of data analytics systems. Her background combines consumer psychology, statistics, and marketing - including graduate research in advertising effectiveness, along with 20 years of experience leveraging research and data to evaluate consumer behavior and solve business challenges.
She now serves as VP Product and Insights for Voltari, a provider of data-driven solutions for smart marketing and advertising. For more than a decade, Voltari has empowered brands and agencies to maximize their advertising dollars through smart mobile marketing and advertising solutions. Voltari's real-time, machine-learning optimization delivers content and messaging to people who are most interested in it, when they are most likely to interact, through an integrated and scalable, managed service platform. Voltari's patent pending mobile ad recommendation engine enables clients' campaigns to gain performance efficiencies that improve over time. The company is dedicated to providing the most advanced audience targeting and optimization products to its marketers and agencies - and continually delivering insights. The Insights group Denison oversees focuses on the distillation and dissemination of campaign performance and consumer insights. She writes from this vantage point.
March 19, 2014