Marketing Mix Modeling and ROI Analytics

To better understand how Marketing ROI measurement fits into the entire Corporate Market Strategy paradigm, let's look at a different arrangement of the classic Profit equation used in the traditional 'Breakeven Analysis':

Selling a greater number of units
A higher Unit Selling price
Lower variable Unit cost
Lower overall Fixed costs

Regardless of how a firm reports its expenses, Marketing can be functionally assigned under either Fixed or Variable costs. Typically Mass Media or 'Above the Line' Marketing in general is a Fixed cost because it doesn't vary by the number of units sold. It may be possible to classify some below the line marketing, especially Direct Marketing also as a Fixed cost, while pricing and consumer promotions like Coupon that change depending upon the number of units sold are typically Variable costs. The expectation in Marketing spending is of course that the number of units sold with Marketing spending is more than that without Marketing spending. Although it would be desirable to spend as much on Marketing as possible, this drives up both Variable and Fixed costs thereby lowering profitability, therefore to invest in Marketing efficiently and effectively, it is important to understand how each marketing tactic impacts units sold as accurately as possible. This is where quantitative methods like Marketing-Mix Analytics enter.

Marketing-Mix Modeling leverages econometric techniques like regression models to quantify the contribution of each marketing tactic to total sales. Marketing-mix output can be used to optimize Marketing Spending and Marketing budget can be optimally distributed across marketing tactics by iteratively adding marketing dollars to each tactic that maximizes total ROI. It is important to remember that ROI of a marketing tactic is not constant but changes as investment levels are changed. This is because of the nonlinear relationship between most marketing tactics and sales. Marketing optimization will always distribute the next marketing dollar to that tactic that will yield the highest total ROI. It is also important to remember that tactics like trade promotions that are usually included as a linear impact on sales cannot be included in the optimization, since the linear relationship will result in the ROI for that tactic never decreasing for any level of spending. Also most marketing-mix models in industry and academia use a preset nonlinear form like logarithmic, exponential decay or s-curve. The actual shape of the relationship for different marketing tactics and sales may differ from tactic to tactic and the correct approach is to empirically determine the correct shape by iteratively testing various logical shapes.

Evaluating the effectiveness of marketing activities is an important task in the market strategy for any consumer product. Measuring the effectiveness enables marketers to determine the return on marketing investment, but more importantly, it also enables them to ascertain if one marketing channel is over-saturated, so that resources can be more efficiently deployed in under-saturated channels using optimization techniques.

Marketing Mix Analysis is typically carried out using Linear Regression Modeling. Nonlinear and lagged effects are included using techniques like Adstock transformations. Typical Marketing-Mix output includes a decomposition of total annual sales into contributions from each marketing component, a.k.a Contribution pie-chart.

Marketing contributions can also help mathematically determine the correct level of marketing spend to maximize total profits.

Overall Current Year Marketing ROI=[Incremental Unit Sales Due To Marketing In Current Year*Profit Margin Per Unit]/[Total marketing Spend]

This formula can be applied to each individual Marketing tactic to derive ROI separately for each tactic.

Marketing budgets optimized using marketing-mix models may tend too much towards efficiency because marketing-mix models measure only the short-term effects of marketing. Longer term effects of marketing are reflected in its brand equity. The impact of marketing spend on brand equity is usually not captured by marketing-mix models. One reason is that the longer duration that marketing takes to impact brand perception extends beyond the simultaneous or at best weeks ahead impact of marketing on sales that these models measure. The other reason is that temporary fluctuation in sales due to economic and social conditions do not necessarily mean that marketing has been ineffective in building brand equity. On the contrary, it is very possible that in the short term sales and market-share could deteriorate, but brand equity could actually be higher. This higher equity should in the long run help the brand recover sales and market-share.