Back in 2005 I had a digital marketing agency and we were buying display ads, email sends and paid search for FedEx Kinko’s. I still remember the anxiety I felt when we presented results from our media buys. Paid search of course looked great, with a very low Cost Per Action. Email produced decent results but clearly took a back seat to search. The media step-child we call Display accounted for a majority of the spend, and appeared to be a complete waste of money with a CPA that was 10x that of search. Naturally my client asked the question: “why on earth are we spending money on display when search is so much more efficient?”
My answer was that: 1) we were buying all the search that was available, and 2) we believed the investment in display was creating awareness that ultimately drove more searches. We cited the increase in clicks and leads from search that correlated with the growth in display advertising, but lacked hard data to support our thesis. Fortunately my client agreed, but also challenged me to do a better job of justifying the media plan. We did what we could at that time and found that 20% of those who converted from a paid search had previously clicked on a display ad. But that was the extent to which we could attribute credit for awareness created by Display ads.
Now, 7 years later, we’ve evolved significantly as an industry. We can now view comprehensive conversion paths and use machine learning and statistical analysis to allocate credit to each impression, click and interaction that influences an online conversion. We can show the true ROI from online advertising, show the role and ROI for each channel, publisher and placement, calculate optimal frequency and quantify wasted spend efficiently and cost-effectively. Capability-wise, we’ve come a long way since the days of last-click reporting and since 2010, the industry has been ripe for massive adoption (learn why: Five Forces Driving Attribution).
But despite these circumstances, most advertisers still measure and optimize the same way we did back in 2005. They realize there’s a better way to do it, but for a variety of reasons (read more: “Ph.D Targeting, 1st Grade Metrics”) they stay rooted in outdated metrics that preclude them from optimizing spend and maximizing ROI.
In Geoffrey Moore’s classic high-tech marketing book “Crossing the Chasm” he defined five groups of adopters: innovators, early adopters, early majority, late majority and laggards. According to Moore, an industry “crosses the chasm” when the early majority adopts new technology, which sparks rapid growth and value creation in that sector. Adoption by the early majority constitutes the evolution from “fad” to “norm”. When it comes to measurement of online advertising, these days are still ahead of us.
While some advertisers (innovators and early adopters) have raised the bar in media measurement and optimization, the early majority is still in the consideration stage. For years they’ve been hearing about Attribution from innovators, and are now seeing case studies and thought leading research from early adopters. Resembling the tortoise more than the hare, the early majority are reading POVs, evaluating solutions and building the business case to invest in Attribution and advanced analytics. For the past 2 years I’ve wondered “will this be the year we cross the chasm?” Despite high hopes for 2011, the big event has not yet happened. A handful of brands and agencies dipped their toe in the water, but only a small percentage of advertisers have taken the plunge.
Earlier this year I again wondered if 2012 would be the year we cross the chasm. Given that the year is 2/3 over, and most new initiatives take place in Q1 or Q2, I have my doubts. But there is a lot more activity and focus on Attribution than in prior years, helped in part by Big Data fever that has everyone atwitter. As noted in my prior post, mass adoption will happen when Advertisers start demanding better metrics, deeper insights and demonstrable improvement in ROI from their agencies. It’s happening today in small numbers, but at an increasing rate. It “feels” like we are close to the Tipping Point and I am hoping 13 (as in 2013) will be our lucky number.
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