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Marketing More with Less
Achieve your goals with econometrics and optimization models.
Posted May 18, 2009
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If you are like more than 25 percent of executives, you have had your marketing budget cut, perhaps dramatically. How do you know where to allocate your remaining budget to achieve or surpass your annual goals?

Historically, marketing budgets have rarely been statistically analyzed for optimum productivity. Instead marketing budgets are usually based on meaningless metrics, such as percentage of last year's revenues or percentage of last year's budget. Once marketing managers receive the budget, they divide it among a wide range of marketing activities from advertising to sponsorship and from Web search to emails.

Oftentimes, the allocation of monies across the various marketing activities is a guesstimate with little statistical or financial data to determine the specific allocation of funds for each activity. Not knowing "which half of their marketing budget is working," marketing managers engage in numerous activities to cover all bases. They buy group insurance so that some items in their cumbersome marketing portfolio will have a positive effect, even if diluted with several deadbeats.

Econometrics identifies effective marketing

Enter econometrics, the art and science of statistical analysis used to determine the levels of factors that best explains a result. Optimization is the process that takes the econometric results, builds financial simulation models, and allocates the budget to achieve a desired result in the most efficient method.

Econometrics identifies activities that drive marketing performance and lift outcomes. The analysis examines both sides of the equation. On one side are the driver inputs that include marketing activities; controllable variables, such as the number of consumer facing employees; economic factors, such as interest rates or gas prices, that might affect outcomes; and competitor spend.

On other side of the equation are the outcomes, which could include the number of new customers, profits, customer equity, or market share, for example. All of the data is analyzed to determine relationships between the inputs and the outcomes over time. The results help marketing executives determine the effectiveness of different marketing activities.

As the cornerstone of econometric analysis, data plays a critical role. Capturing appropriate data, both on the input and outcome sides, is vital to determining marketing accountability. The first step in the data identification process is to ask, "What is the company's goal?" As the outcome, the answer to this question dictates the type of metrics that will be used for the inputs.

Once the goal/outcome is determined, the company focuses on the inputs to answer the question "What impacts the goal?" Goals may be impacted by nonmarketing activities that are controlled by the company such as the number of stores or the number of salespeople. Goals are also impacted by noncontrollable or external variables, such as interest rates and gas prices.

After analyzing the inputs and outcomes, equations explaining the variations in the outcome over time are developed. This equation is then compared to what actually happened historically. How closely the actual compares with the equation, which predicts what happened, is known as the fit. The fit is explained with a mathematical term, adjusted R squared. The higher the adjusted R squared, the better the fit between the actual outcome and the predicted outcome. An adjusted R squared of over 90 percent is considered a good fit.

Optimization determines ideal marketing mix

Underlying the marketing budget optimization is the concept of diminishing return market response curve, which is based on a commonly accepted principle that the next dollar spent will have less impact than the previous dollar, and that no matter how much is invested, not every prospect will be converted to a customer. Using historical data or marketing experimentation, executives can calculate their products' market response curves. From the response curves financial simulators are developed and budget optimization can be determined.

With lots of data resident in most companies, executives have the capability to determine which marketing activities drive performance. Armed with this knowledge, executives can more easily develop budgets, forecast sales, and demonstrate marketing accountability.

Marketing mix determination, which used to be a half million dollar project, can now be completed for a fraction of the cost with outsourced analytics through PhDs in India. No longer are marketing budgets left in the realm of guesswork or percentages of dollar figures or target amounts. Marketing budgets can and should be optimized to achieve the company's goals.

About the Authors

Barbara Lewis and Dan Otto are cofounders of MarQuant Analytics, a provider of marketing analytics services with tools to optimize the marketing budget across numerous scenarios. Their clients include Fortune 200 companies. For more information, visit www.MarQuantAnalytics.com

Please note that the Viewpoints listed in CRM magazine and appearing on destinationCRM.com represent the perspective of the authors, and not necessarily those of the magazine or its editors. If you would like to submit a Viewpoint for consideration on a topic related to customer relationship management, please email viewpoints@destinationCRM.com.

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