Automated Marketing Intelligence

Some of the most successful and innovative companies embed analytical wisdom in real time marketing applications instead of relying onto back-end analysis. The last edition of Business 2.0 writes about a new company called Revcube (www.revcube.com), that optimizes banner ads, emails, or text ads based on analyzing in real time over 5,000 attributes to deliver the most relevant Online Marketing experience to consumers. “ “If you analyze data once a month or even every week, you miss something”, says Revcube Bill Schaefer. “We analyze data every 30 second”…Because Revcube automates a process that typically involves a multitude of focus groups and mountains of spreadsheets, its system is seen as the future of Web marketing,” writes Susanne Hamner in Business 2.0.

Does this movement symbolize a dramatic change of where analysts will spend most of their value in the not so distant future? The answer is probably yes. A human being has little chance to compete with machine learning and highly automated algorithms of finding the best success and consumer response correlations of a given marketing challenge. I expect these highly sophisticated automated intelligence generating processes gaining more ground in at least these three important marketing channels:

• Search Optimization Marketing: There is little use for human interference of finding the best search terms for a particular audience.
• Direct Response Marketing like outbound email, Banner Ads: The key human value might be in designing the most efficient test matrix, everything else can be designed and driven by intelligent applications
• TV Media Placement Decisions: Most placement decisions are still done by human beings, this will dramatically change due to the increasing complexity and increasing targeting capabilities of TV channels.
  One common thread amongst all these more marketing areas (that will rely more on automated intelligence) is the increasing importance of auction based platforms that support these marketing channels.

Human analysts are getting much more under pressure to provide higher level strategic value instead of doing the basic number crunching that was (and often still is) the center piece of Database Marketing and even Data Mining. Both disciplines need a serious redefinition and refocus.

Analytics Mainstream?

It seems that not only Geeks became the richest individuals over the last years but that analytics is so much mainstream nowadays that one might wonder what is left for us to do? Fortunately reading the recently published and already pretty popular book “Competing on Analytics” by Thomas Davenport, one can only realize how much analytics is still in its infancy stage in the corporate world. As Davenport describes only a small fraction of Fortune 2000 firms have reached a mature and successful analytical driven organization that creates superior value for its employees, customers, and shareholders.

Why is there still such a hesitance and conservatism by most organizations to apply even the most basic analytical best practices? Let me try multiple answers:

• The sheer number of non-analytical people versus data driven employees creates an unbalanced situation where analytics will always play a minor role. Most organizations have less than 1% of their work force in data driven functions but over 50% in generic business processes that are mundane in nature. This will change only very slowly.
• Analytical corporate individuals are still rather shy in fighting for the top position in large corporations. Unfortunately most of them are comfortable in their mid-level management positions or individual contributor roles instead of possessing the guts to “own” and lead the corporation.
• Corporate Myths have an amazing staying power. It’s more difficult to understand the internal corporate myths of any given organizations. Only the analytical dissection of these myths enables the proliferation of more data and analytical driven attitudes and processes. And this is more work than most of us ever imagined.
• Wrongly applied analytics are not just a detriment to positive results but a real set back for organizations in their quest to be more data driven. These wrong applications can reside in the belief that analytics are an automatically generated silver bullet instead of a significant guiding input for decisions, or analytics are used to stifle the creative process of innovation instead of inspiring new ideas by using fact based inputs. And there are many more ways of misapplying analytics and create a circle of backlash stories.

Only the positive and successful examples of “converted” companies into analytically focused organizations will bring additional pressure for anyone who remains on the sideline. It’s a slow moving conversion one company at a time. And it will take longer than most of us expect. But fortunately there is no way backwards.