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This illustration shows how a comprehensive data analysis program can deliver benefits as related to customer acquisition and retention.

This slide is a tidy catalog of what questions marketing should be asking about their customers.

This graph illustrates how marketers can optimize their marketing dollars by achieving a ‘lift’ from data analytics, allowing them to reduce their marketing dollars while increasing their response rate.

This primer on branding uses different brand concepts (although not necessarily the ones that are formally taught at business school) and provides their definitions.

This analysis framework provides a series of cross points to discuss brand messages across (the cutely named ) seven ‘Cs’: Customers, company, competitors, cost, control, convenience, confidence. The sum of the cross points is a definitive word f Filetype: Powerpoint
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This is a list of brand implementation activities set next to a comprehensive brand environment graphic.

This slide shows how data clustering (essentially complex, multi-field data similarities) bubble up and can be used to create customer profiles. This is an over-simplification to be sure, but handy for teaching non-analytics professionals about c Filetype: Powerpoint
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This is a neat comparison between segments and clusters, which are often confused/misused by marketers who don’t understand them.

This is a top-level process flow diagram that shows how to conduct market data analysis by ‘training’ a data model.

This slide illustrates how a trained data model can guide two fundamental marketing decisions: determining what the right tactics are (such as creating a specific offer) and identifying the right customers to market to (i.e., picking the right lis Filetype: Powerpoint
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This illustration explains that data analysis, although very analytical by marketing standards, is very much like counting cards. This is the central story of why data mining returns propensity vs. definitive answers.

This slide illustrates how data analysis can find patterns among customers who may have similar buying patterns. By finding customers who meet the buying pattern criteria, but haven’t yet bought all of the items, we can build a targeted list... Filetype: Powerpoint
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This slide illustrates how data analysis can find patterns among customers who may have similar buying patterns.

This slide makes a case for data analytics for customer-driven organizations. It asks the question “Why data analytics now?” and answers the question using external drivers, internal drivers, and new enablers.

This graphic shows the layers of a company that is ready for marketing-focused data analytics.