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Answering “Million Dollar” Marketing Questions

By Feather Hickox

Decision modeling, optimization and simulation can be used to answer difficult questions. The answers to these questions can be worth millions. For example, 

With a trade partner that wants to push out a million discounted offers for milk, what percentage of that would be most profitable to use to promote customers?

The larger and more varied the data set being analyzed, the more complex the range of questions that can be answered in a statistically reliable manner. These answers can be extremely valuable. In a 2012 CEO Survey, 100 percent of respondents could identify a piece of information that, if they had it, would allow them to run their businesses better. “Customer intelligence” was the most sought-after category of information, above information on competitors and even sales.

Using Big Marketing techniques, companies can find answers to questions that they believe will give them an edge. For example, FICO is helping one retailer explore trade-offs such as:

 Will 10 percent off be more effective than free shipping, or than simply telling the customers that the desired item is in stock and will be reserved for a short period of time?

Is offering 12 months of interest-free credit necessary, or will six months be nearly as enticing?

We’ve helped an Asia-Pacific client increase usage of an installment loan product attached to a credit card by figuring out:

Which customers are likely to increase the loan utilization if offered a 30 percent temporary discount?

Which customers would be sufficiently incented with just a 20 percent or even 10 percent offer?

The technique is helping our client better understand the subtle relationships between line increase, utilization and delinquency in a market where consumers have traditionally been reluctant to take on debt.

Moreover, Big Marketing analytic techniques can help marketers answer questions that connect operations-level customer decisions with executive-level direction. Instead of limiting themselves to isolated account-level questions like:

 Should I offer this customer a line of credit, and if so, what should the limit be?

... they can answer questions that capture the real-world complexity of these decisions:

In light of our portfolio goals and the customer’s current and future value, risk profile and expected reaction, what is the most profitable offer?

For more information on this topic, check out our Insights paper (registration required).

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