One of our clients, a consumer electronics giant, had long gauged its advertising impact one medium at a time. As most businesses still do, it measured how its TV, print, radio, and online ads each functioned independently to drive sales. The company hadn’t grasped the notion that ads increasingly interact. 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. To tease apart how its ads work in concert across media and sales channels, our client recently adopted new, sophisticated data-analytics techniques. 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. And search ads, at 4% of the company’s total advertising budget, generated 25% of sales. 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.
Advertising Analytics 2.0
Reprint: R1303C
Most marketers think they know how their advertising affects consumer behavior and drives revenue. 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. 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.
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. The results: 10% to 30% improvements in marketing performance.
Firms of various sizes can make the shift to analytics 2.0 by engaging in three broad activities:
- Attribution: quantifying the contribution of each element of advertising
- Optimization: using predictive-analytics tools to run scenarios for business planning
- Allocation: redistributing resources across marketing activities in real time
Nichols argues that implementing analytics 2.0 means building the required infrastructure and entwining it in organizational culture, strategy development, and operations. Any company can begin that journey; businesses that don’t will be overtaken by those that do.
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