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Predictive Modeling for Advertising Campaigns
The New Metrics Frontier


Source: MarketingSherpa Newsletter, June 06, 2004


Predictive modeling, the science of analyzing past campaign results in order to forecast and proactively improve future results, has long been the holy grail of direct marketing.

Analytics experts make, on average, the highest salaries in the marketing field. And the companies that employ them are able to get better response rates, and much higher profits.

The question is, can predictive modeling be applied in any sophisticated way to advertising campaigns? We reviewed a new analysis methodology that claim to help advertisers figure out exactly how to tweak future campaigns for a better response, and enhance long-term reader engagement.

Taguchi Method-based Tactics

The Taguchi Method was invented to help industrial researchers (such as automakers) who wanted to conduct tests with multiple elements, in a short-time frame, with small test cells.

Dr. Jim Kowalick (a respected product engineering consultant with a marketing background) decided to try applying this to advertising campaigns for folks who wanted to test a broad range of variables without creating a separate test cell for every single one of them.

Instead of classic tests where you measure one varying factor per test cell against your "control", you could measure hundreds or even thousands of varying factors -- and the way they interact with each other -- per test cell.

The returning data would tell you what factors go toward making campaign creative that wins.

If it works, this tactic could be a godsend for marketers, or those who need to launch completely new creative instead of just tweaks to what's already working.

Malloy Insurance Agency, an insurance firm based in Northern California, whose regular campaigns to a house list of 7,500 weren't working very well, tested Dr. Kowalick's services in May 2003.

Over a two-week period, Malloy split his list into 12 test cells of 625 each, and sent out each a very different email creative -- ranging from short HTML to long-copy text-only -- hoping to measure the success and interaction of more than 2,000 different specific creative factors.

Dr Kowalick tells us he was able to determine the winner and the specific elements within that creative that made it win with a "95-98% confidence level."

Then Malloy relied on his list of winning elements to craft new email letters to clients and prospects fortnightly from then on.

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