Media departments are no place for guessing. With millions — even tens or hundreds of millions — of dollars at stake, clients want hard data showing that their budgets are being well spent.
And yet for too long, media executives have been forced to rely on indirect information to judge a campaign’s postbuy effectiveness. If sales or awareness goes up, things must be working (even though dozens of non-advertising factors affect such measurements). If all GRP goals are fulfilled, the spend is a success (even though it only proves people saw the ads).
To be sure, all these metrics are important. But to complete the picture, it’s critical to look at what advertising is meant to impact: consumer behavior. And thanks to the world of cross-media analytics tools, reliable measures finally exist that can calculate true payback of media investments.
Cross-media solutions can finally integrate the silos of data that exist in the media world — some of which have been around since the ’70s — to create actionable insight. And unlike the days when the media landscape comprised a few sources of research and a couple of metrics, today’s tools are not dependent on mainframes. Instead, they tap the power of distributed, Web-based processing to generate strategic data unthinkable even a few years ago.
Now, online and offline data are married to create an amazingly accurate picture of what a campaign is accomplishing. Everything from site analytics to competitive media buys, from ad-server stats to CRM, from store-sales info to traditional ratings is integrated with the agency’s media purchase data to create multi-source insight into campaign effectiveness. Data can be stratified by ZIP code, DMA, MSA, city, state, area code or dozens of other preset or custom criteria.
Perhaps best of all, these services provide information automatically and in near real time. The result is a picture of what’s happening that far supersedes canned reports, presented in a drill-down format suitable for analysis by specialists on both the agency and client sides.
Dedicated analytics products now exist that let researchers and planners not only evaluate campaigns post-buy, but also monitor them as they unfold. What’s more, the same information can be used to model alternatives, demo hypothetical buys and make changes midstream.
Because they are a direct measure of consumer interest, Web analytics play a key role in the new cross-analytics paradigm. But it’s not enough to look solely at the client’s Web site activity; additional measures need to be included. As many as 10 to 20 discrete data sources may be needed to generate the insights needed to make effective changes.
While cross-analytics clearly benefit advertisers, they are especially valuable to ad agencies for an additional reason: They give shops a new competitive advantage. After all, while agencies add real value to the marketing process, they’re not data experts. Even the largest multinationals typically don’t have the technology and systems infrastructure to cost-effectively aggregate the many forms and sources of data needed to conclusively evaluate campaign effectiveness. With purpose-built media-specific ETL (Extract/Transform/Load) tools, data can even be integrated from a client’s agencies to measure any metric with exquisite accuracy.
Many examples exist of advertisers who are benefitting from online/offline data integration. In one case, a major healthcare services provider was looking for a way to reduce its cost of obtaining qualified leads through its advertising. Its target was $100 per lead; by obtaining real-time visibility into its campaign performance and making a fact-based, strategic shift from national TV to its best-performing DMAs, the advertiser was able to decrease its cost per lead by 21percent in the first month, from $112 to $89. Moreover, it maintained an average 13 percent decrease in each of the next four months.