Data and measurement seem to dominate every discussion about marketing these days. And cross-channel attribution, or the science of assigning proportionate credit to every marketing touchpoint, has been the holy grail of those conversations. But in an information economy beset with free content and infinite choices, is attribution really enough?
According to AdRoll, 58% of marketers rely on attribution for making decisions about budget allocations. But dig a little deeper, and you may find few who are playing with a full deck: Last year a Forrester-commissioned analysis found that only one in nine marketers used advanced attribution methods, and among those using attribution, 28% were using single-click methods – the most basic of approaches, which naturally offer limited insights.
Advanced attribution requires advanced tools. Even with them, obstacles abound: convincing stakeholders to adopt new channels or abandon comfortable ones, incorporating findings into cumbersome media plans, making analytical efforts scale.
Then here comes the final downer: The channels that make advertising scale are proving less reliable, with factors ranging from fraudulent bot traffic, which accounts for about 36% of clicks, to the growing phenomenon of ad blocking, which roughly 16% online users in the U.S. admitted doing in Q2 this year. The ad blocking integration that Apple enabled in its recent iOS 9 release will make that number grow even more, and this at a time when advertisers are dumping record sums of money into mobile, the very platform that is most endangered.
According to an eMarketer report, U.S. advertisers devoted 43.0% of programmatic spending to mobile impressions in 2014. This year, they project that share to reach 60.5%, and by 2019 mobile will account for 76.3% of the total programmatic ad spend.
Attribution has forced us to think beyond the click, and consider things like the role impressions play in driving conversions. But trends in technology and content preference are winning over the advertising race to disrupt people's experiences.
This is why attribution data is best put to use in understanding the information that audiences want, and how best to engage them with it. What the modern digital landscape seems to now require to be successful is a content marketing mindset.
After all, engagement that is meaningful to your brand (or client’s brand) is happening everywhere. You have to be OK with the fact that you can only track a small fraction of that engagement, even if you manage multiple marketing channels like paid search, social ads, and display.
Beyond the clicks and impressions that make up your attribution analysis are the countless blogs, forums, articles, newsletters, and more that fall outside a brand’s actively targeted media plan.
Take the example of Houzz, the online platform for home design enthusiasts. Given the aspirational quality of its content, Houzz likely draws a significant audience that is in the market to buy a new home. If Houzz were to send a mass e-blast about “New Home Construction Ideas” that featured a photo crediting a national homebuilder brand, it might prompt a swath of Houzz’s email list to visit that brand’s website.
Like anyone, these visitors would probably find the brand’s website by searching for it in Google, or by entering the website URL directly. But to the marketers who manage that brand's media, these visitors only register as an unexplainable rise in direct visits and branded search. No one would be wiser to the fact that content that works for Houzz also works for brand X.
This is why it behooves the marketers of brand X homebuilder to constantly explore and test in new content categories and channels. This is especially the case in real estate marketing, which can have a long and protracted sales cycle, subject to delays, interruptions, and influences from other content sources.
With winter on its way, we’ve begun revisiting last year’s data to see how to put this practice to work for our own real estate clients. One source for analysis is the data we gathered from weather bidding, the feature in Google AdWords that allows you to automate when your search ads appear based on weather conditions. Our experiments with this tool taught us that home buyers and apartment shoppers are less active on Google when it’s snowing, which is why our keyword bids are set to freeze (pun intended) when such conditions arise.
But just because home or apartment seekers are not action-oriented on snow days, it doesn’t mean they’re not dreaming – clicking around the internet, researching, consuming media. What better way to test this notion than to e-blast snowed-in audiences with aspirational content that invites them to picture themselves with that new spacious kitchen, walk-in closets, or the “wo/man cave” they always wanted?
And if this proves successful, you not only have an effort that scales – proven digital content for future snow days – but you’ve peeled away just one layer of the content marketing onion. Would a February influencer campaign using blogs, Instagram, and other publications precipitate a greater uptick in leads than your existing display campaigns?
You wouldn’t know until you tried. But then, you shouldn’t try unless you can measure.