Multivariate Testing: Do We Need A Chief Measurement Officer?

Test-tubes-BIt seems simple. Marketing campaigns designed to work on a brand's Web site don't always produce positive returns on investments in search, social and mobile. Reasons vary depending on the message. If it comes close, the campaigns can produce so much data that it muddies the message. Do companies need a CMO (chief measurement officer)?

Linking the Web site message to the Facebook Fan page might seem natural to provide continuity across platforms, but Paul Dunay, global VP of Marketing for Maxymiser, said it's anything but easy. So Maxymiser engineers built a tool dubbed MaxSOCIAL that allows marketers to test, personalize and optimize content and promotions on Facebook. The tool will integrate data, along with Facebook user insights, into existing Web site optimization programs to help marketers understand what content and messages resonate with site and Fan page visitors.

Dunay said one line of JavaScript code allows the tool to map information visitors' share on Facebook onto existing online customer profiles. As a result, brands can create an integrated, seamless experience as consumers move between Facebook and the brand's Web site. "This universal campaign you're pushing everywhere might do well on the Web site, but it doesn't hold water on the social," he said.

When you've got that figured out, the next challenge will become determining what to do with all that data. Marketers need to separate existing customers from new visitors, and understand the return on investment (ROI) in marketing to each. Most digital advertisers invest far too much capturing demand and not nearly enough creating it or measuring it, according to a recent study from TruEffect SVP Martin Smith. In his white paper "Big Measurement," he points to the need for another C-title, chief measurement officer (CMO), to tackle big data challenges.

Smith explains that accurate measurement is just as important as collecting lots of data, and defines eight principles that help move toward a measurement model that delivers an effective ROI on big data investments. These principles include: Accuracy, Getting the Data Hierarchy Right, Align Your KPIs with Your Measurement, Action/Communication, Integration, Stewardship, Systems Right-Sizing, and Human Capital Alignment.

The most simplistic principle often times becomes the foundation. "It is one thing to know something, but quite another to do something with what you know," according to the whitepaper. It's important to remember that lots of data and measurement create opportunities to make learning actionable, and do it in real-time, but unless marketers know what to do with it, the knowledge becomes worthless.

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