Modeling and Optimizing Your Marketing Mix
Tuesday, 01 May 2012 14:38
Fifty years ago, optimizing the media mix was relatively easy. The media options for most companies were typically limited to national and local magazines and newspapers, and national television networks and maybe some local radio and large industry trade shows. By the 90s, channel options became a bit more complex; we had cable to add to the mix along with segmented direct mail and a bevy of trade publications and trade shows. Here we are in a new century and the media channels have exploded with the SEO, social networks, online display, virtual events, email, and mobile. All of these marketing vehicles reinforce and amplify the importance of being able to ascertain the effectiveness and efficiency of our marketing channel investments; hence the increased emphasis on marketing mix modeling and optimization.
What is a marketing mix model? Marketing mix modeling uses statistical analysis such as multivariate regressions on sales and marketing time series data to estimate and forecast the impact of various marketing tactics on sales. Regression is the workhorse for mix models. Regression is based on a number of inputs (or independent variables) and how these relate to an outcome (or dependent variable) such as sales or profits or both. Organizations use Marketing Mix Models to quantify the sales impact of various marketing activities and determine effectiveness and ROI for each marketing activity. Most organizations set their models up to evaluate their various channels.
Once you have the statistics to create the model you can use these equations to figure out how to optimize your mix, this is known as Marketing Mix Optimization. You will want your model to account for direct as well as indirect effects and take things outside of your contract (such as the time of year, interest rates, exchange rates, gas prices, elections, competition, etc.) into account. Developing a marketing mix optimization model requires good data and strong analytical skills. You may find it prudent to partner with your finance organization to co-author the model to as a well to generate buy-in from the sales and leadership team.
When does it make sense to use a marketing mix model? Marketing mix models makes sense when you are trying to answers questions such as:
However, the marketing mix model needs to support your overall organizational outcomes, marketing objectives, and metrics and performance targets. Optimizing a mix that will not enable you to achieve your outcomes and objectives may make your more efficient but will not make you more effective. If you are not meeting your performance targets or industry benchmarks, you may want to revisit your execution before you adjust your mix and spend.
You're ready to build a model. What are the steps and what data will you need? These steps will get your started:
You will want to refresh your models quarterly and rebuild them at least once a year. Things such as the your data quality, the breath of internal and external data, the granularity of your data, the accuracy of your historical marketing data, the robustness of your statistical functionality, and the technical architecture to support the model construction all impact the quality of your model. Building a model may be one of the tasks worth outsourcing to the experts if you don't have the analytical skills to develop your model or access to internal resources that can help (such as finance).