Drop Your Last-Click Crutch

Let's not talk about best practices for using attribution models to measure the effectiveness of your digital marketing campaigns. Type "attribution modeling" into your search bar and you'll have a windfall of insight and guidance on the subject from some of the best marketing brains in the world. And let's not spend our time here debating the merits of various attribution scoring techniques, since research tells us only about half the companies in Europe and North America do any sort of marketing attribution analysis in any case.

No, let's stick to basics and ask a frank question: If you can count your company among those using attribution models for your digital campaigns, are you still defaulting to traditional "last click" measurement?

It's OK to admit it, because it's understandable. Not long ago, we had little choice but to rely on the last click. We had the motive — demonstrate marketing's ability to drive revenue — but we didn't have the means. The data connecting each touchpoint along a customer's path to purchase wasn't available or reliable. Moreover, the tools for analyzing this type of information were neither sophisticated nor affordable. Spending most of your marketing budget to determine whether marketing was working just didn't add up.

Plus, we rarely had the opportunity to analyze. Who had time in the past (or now) for hours of complex modeling? All modern business moves as fast as the latest microprocessors can carry it, which lays heavy pressure on marketers to produce results just as quickly. Digital marketing isn't just about driving revenue; it's about driving revenue ASAP.

So, if the last marketing tactic in a campaign produced a sale, we gave it 100 percent credit, even though a mix of campaigns and as many as five touchpoints preceded that sale. On some level, we also knew we were sacrificing the potential modeling would deliver. We knew we could beat our competitors if we could just see the whole picture. We knew we could produce more revenue if we could focus time and effort on the most successful campaigns. And we knew we could cut costs without sacrificing returns if we could determine the optimal balance of spending between branding and direct response.

For that edge on the competition, that boost in productivity and that increase in return on investment, however, we would have needed to understand the intricate relationships between campaigns — i.e., precisely how one influenced the other. And finding that out was complicated and expensive. Last-click analysis was quick and easy, so it became our crutch for showing digital marketing works.

Well, you can drop that last-click crutch. Retailers today have the motive, means and opportunity to use sophisticated attribution modeling. Your motive should be stronger than ever. A flood of handheld devices and epidemic of mobile applications is giving retailers more ways to reach more customers more often than ever before. At the same time technology is facilitating unparalleled access to consumers and businesses, it's enabling unprecedented means of measuring the impact of your outreach.

In this era of big data, unavailable or unreliable streams of data are swiftly fading in the rearview mirror as users speed through billions of transactions every day. Meanwhile, software tools for capturing and measuring that information are multiplying and improving rapidly. Researchers estimate nine out of every 10 websites has some sort of analytics package attached.

Furthermore, our opportunities to analyze have expanded recently. Major players in the field of web analytics have been making strategic moves to deliver robust attribution modeling capabilities. In the last year Adobe, Google and IBM all unveiled refinements to their analytics engines that sharpen attribution modeling tools.

So, why aren't more retailers using sophisticated attribution modeling? Maybe they've been leaning on the last-click crutch for too long. Maybe they need some therapy to learn to walk this path of analysis on their own. Here are the first three exercises:

1. Find it. If you have a web analytics package, the odds are high that attribution modeling tools are in there somewhere. If you can't find the module, search for help online or just ask your software provider. Turning on modeling capabilities may come with a price tag, but the move also comes with potential rewards — e.g., competitive advantages, elevated productivity and greater ROI.

2. Learn how to use it. Plethora is the proper word to describe the amount of online information available regarding attribution modeling. As noted earlier, within a few quick searches you'll be learning from the best minds in retail marketing. The plentitude may be intimidating at first, but these days digital marketing isn't for the timid. A little unease is understandable; long-term ignorance is not.

3. Build it into your routine. We all have marketing goals; we all have plans for achieving those goals. Include attribution modeling in those plans from the start, midstream or even in retrospect. The data is there. The tools work. You must measure your results in some way. Start using the most powerful method as soon as possible. At today's breakneck pace of business, every delay in analysis could lead to lost sales, drops in productivity and/or dips in ROI.

As experienced retail marketers, you all know driving revenue requires investment in terms of time, budget and mindshare. Sure, walking without that last-click crutch may be uncomfortable at first, but with some discipline and dedication, you'll be running in no time.

Kurt Anagnostopoulos is co-founder of KeywordFirst, a digital marketing firm. Kurt can be reached at Kurt@KeywordFirst.com.