Mobile advertising owes a lot to traditional and digital media: best practices for TV, radio and particularly desktop ads helped shape what it is today. But as more media consumption shifts to mobile, and as engagement remains elusive, it's time to take a critical look at these best practices and ask, "Are they working against mobile campaigns?"
1. Ad formats
Let's begin with ad formats, because "leading with ad format" is a common practice in advertising. It's a habit innocently rooted in traditional media, where format was clearly and easily determined by channel. This practice became further entrenched as more digital ad formats entered the marketplace -- and with a higher level of complexity and higher CPMs, ad format become a defining construct for campaigns.
Historically, the format-first approach worked well because one could assume a laptop or desktop user was sitting and, treadmill desks aside, stationary. This increased the likelihood that a consumer would engage with rich creative, so why not shape a campaign around it?
But those assumptions fail in mobile, where users are just as likely to be kicking back at home, in line at the supermarket, or in a crowded bar. Busy, on-the-go consumers who grab their phones to complete a specific task are more likely to find that 360-degree product tour or even a short video disruptive.
That's why mobile advertising needs to be more fluid where ad formats are concerned. Instead of constructing a campaign around a single format, advertisers need to build format-flexible campaigns that ensure that the format that is served is the one that is most likely to engage. Not only is it better for the consumer experience, it's more cost-effective for the advertiser.
The next logical question is how advertisers can determine which ad aligns best with a given mobile experience? The answer is in targeting, which may be in its own best practice rut.
For all its strengths, ad targeting wasn't designed to handle the many nuances of mobile behavior. Standard targeting criteria doesn't make it easy to react to a mobile consumer that might be anywhere in the world, performing any number of tasks during what could be a quick mobile session, a long lean-back experience, or something in between.
Location targeting has been a key innovation here, because knowing if a consumer is AT home or at work gives more context. But bringing more data into the targeting equation isn't enough -- the real advantage comes from using smarter data. With advances in machine learning, data should be processed in a way that identifies patterns in consumer behavior, such as what ad format would best serve a given moment, or how environmental variables (like weather) influence performance. This kind of intelligence can go a long way in eliminating the impressions that drag down performance.
This leads us to another practice worth examining: how campaign success is measured.
There's been enough debate over the years as to whether or not click-through rate is an effective measure of campaign success, so there's no need to revive that here. A more practical question is whether too much emphasis is placed on these metrics when evaluating campaigns.
At a time when advertisers are still struggling to understand mobile, the greatest value of a campaign may not be the rate by which someone clicked on ad ad, but rather the insight it offers on mobile behavior. What can be observed about a specific audience's mobile experience as a result of the campaign performance? What about their ad receptivity? And, most importantly, how can this insight be applied to future campaigns?
A willingness to press deeper and learn more essential to mobile success. Mobile is a channel in flux, and will continue to the be in flux as more variables, such as IoT and virtual and augmented realities, build relevancy. This doesn't mean that best practices can't be established along the way, only that the industry needs to continually check those best practices to ensure they aren't getting in the way of better practices. In a space as dynamic as mobile, the biggest mistake anyone can make is assuming they figured it all out.