If you’re like me, reading last month’s Black Friday and Cyber Monday reports from IBM Digital Analytics Benchmark felt like a true vindication. Digital marketers are constantly under the magnifying glass, expected to deliver report after report demonstrating the ROI of their marketing activities; And now, in black and white, we see the results: a 30.3% year-on-year increase in Cyber Monday online retail sales; soaring rates of mobile shopping; and greater visibility into the changing behavior of savvy shoppers, including multiscreen shopping and bargain hunting across different retailers. Huzzah!
As more and more consumers are turning to digital channels to buy goods and services, the race is on for companies to capture more eyeballs and lure customers into their sites. Recently, the Interactive Advertising Bureau (IAB) and PwC announced that internet advertising revenues had hit a “historic high” of $9.26 billion in the third quarter of 2013, representing an 18% rise over the same period last year:
It is, however, the rare marketing department where marketers can simply point to a graph like this, or those in the Black Friday/Cyber Monday reports, to make the case for a bigger budget. We all know that customers are quickly moving to digital channels, and their online behavior is evolving rapidly. But what does that tell us about the performance of this display ad, that email campaign, or last week’s Facebook promotion? Would those marketers now in the midst of spring planning benefit from knowing what devices and channels their customers are using, in what combinations, and what they’re doing in each?
Of course they would. But up until very recently, this kind of marketing attribution analysis was usually guesswork and intuition at best. Attribution analysis techniques were often inconsistent or unevenly applied across channels, a trend that was only exacerbated by the traditional silos that existed (and often still do) in many marketing departments. Using different systems and vendors (and sometimes some creative data analysis), the marketing groups responsible for each realm–display ad, email, social, mobile, search, etc.–were able to show (surprise!) impressive ROI across the board. Budgeting and campaign decisions were made as much on the basis of hunches and politics as on what the data itself showed.
Perhaps this will suffice for some. But markets iterate, and as the digital marketplace becomes increasingly competitive (another key takeaway from the IAB’s report), it’s becoming clear that consistent, data-driven attribution analysis is the missing link between digital marketing spend and results. The challenge for digital marketers now is how to embed this analysis into all levels of marketing, from the analyst on up to the CMO. This will require a single digital marketing platform which combines not just digital analytics, deep attribution and marketing execution capabilities to act on the insight gleaned, but which also easily integrates into ecommerce, CRM, order management and fulfillment, supply chain and other systems. By avoiding the pitfalls of a piecemeal marketing solution utilizing multiple disparate vendors and systems, marketers can avoid making isolated decisions, IT delays and costs, and inconsistent measurement.
Think of how many online ads $9.3 billion can buy. How does your digital marketing budget compare? How many of those ads do you suppose drove real results? And how many were subject to automated, real-time attribution analysis that could conclusively prove a positive return? My guess is not many. But I would bet that those marketing departments that have learned to iteratively embed attribution analysis into their digital spending are taking home a disproportionate amount of the return from that advertising.