Marketers commonly measure the performance of each of their marketing activities as if they work independently of one another-so called swim-lane measurement. (See the exhibit “Get Out of Your Swim Lanes.”) As one CFO of a Fortune 200 company told me, “When I add up the ROIs from each of our silos, the company appears twice as big as it actually is.” Get Out of Your Swim Lanes This still-common practice, what we call swim-lane measurement, explains why marketers often misattribute specific outcomes to their marketing activities and why finance tends to doubt the value of marketing. Making matters worse, different teams, agencies, and media buyers operate in silos and use different methods of measurement as they compete for the same resources.
But that approach is backward-looking: It largely treats advertising touch points-in-store and online display ads, TV, radio, direct mail, and so on-as if each works in isolation. They mistakenly think they have a handle on how their advertising actually affects behavior and drives revenue. Marketers started tracking a consumer’s most recent action online-say, a click on a banner ad-and attributing a purchase behavior to it.Ĭombined with a handful of time-honored measurement techniques-consumer surveys, focus groups, media-mix models, and last-click attribution-such outmoded methods have lulled many marketers into complacency. With the ability to monitor every mouse click, measuring the cause-and-effect relationship between advertising and purchasing became somewhat easier. For about 20 years, everyone gorged on this low-hanging fruit, until the advent of digital marketing in the late 1990s.
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Media-mix modeling, introduced in the early 1980s, helped marketers link scanner data with advertising and decide how to allocate marketing resources. Until recently, the picture was fuzzy at best. That sort of insight represents the holy grail in marketing-knowing precisely how all the moving parts of a campaign collectively drive sales and what happens when you adjust them. Armed with those rich findings and the latest predictive analytics, the company reallocated its ad dollars, realizing a 9% lift in sales without spending a penny more on advertising. And search ads, at 4% of the company’s total advertising budget, generated 25% of sales.
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The analyses revealed, for example, that TV ate up 85% of the budget in one new-product campaign, whereas YouTube ads-a 6% slice of the budget-were nearly twice as effective at prompting online searches that led to purchases. To tease apart how its ads work in concert across media and sales channels, our client recently adopted new, sophisticated data-analytics techniques. For instance, a TV spot can prompt a Google search that leads to a click-through on a display ad that, ultimately, ends in a sale. The company hadn’t grasped the notion that ads increasingly interact. As most businesses still do, it measured how its TV, print, radio, and online ads each functioned independently to drive sales. One of our clients, a consumer electronics giant, had long gauged its advertising impact one medium at a time. New York Times building lobby sentences and phrases that have appeared in the Moveable Type, 2008, Vacuum-fluorescent display screens, each 8″ x 5″, Any company can begin that journey businesses that don’t will be overtaken by those that do.Īrtwork: The Office of Creative Research (Mark Hansen & Ben Rubin), Nichols argues that implementing analytics 2.0 means building the required infrastructure and entwining it in organizational culture, strategy development, and operations. Allocation: redistributing resources across marketing activities in real time.Optimization: using predictive-analytics tools to run scenarios for business planning.Attribution: quantifying the contribution of each element of advertising.The results: 10% to 30% improvements in marketing performance.įirms of various sizes can make the shift to analytics 2.0 by engaging in three broad activities: MarketShare CEO Wes Nichols explains how many big companies are now deploying analytics 2.0, a set of capabilities that can chew through terabytes of data and hundreds of variables in real time to accurately reveal how advertising touch points interact dynamically. But to treat advertising touch points as if each works in isolation is to misrepresent the way today’s complex combination of marketing efforts influences purchasing outcomes. They correlate sales data with a few dozen discrete variables, and they rely on consumer surveys, focus groups, media-mix models, and online last-click attribution. Most marketers think they know how their advertising affects consumer behavior and drives revenue.
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