New technologies have made consumers both better informed and harder to engage. While traditional “one-to-many” mass marketing tools like TV and newspapers remain important, businesses now feel that their reach and influence have declined significantly. This leaves companies with a different and more difficult problem. In a world saturated with media platforms and marketing messages, where attention spans are short and consumers increasingly cynical, what’s the best way to engage consumers and create preference?
Once upon a time life was simple. Choices within the marketing mix were relatively few in number and analysing the past performance and planning the future spend and mix was comparatively easy.
But today the choices facing the marketing executive are numerous and complex. For example, advertising is no longer just a decision between the four major media platforms but now has to take into account the rise of the internet and the explosion of more choice and variety within the old traditional broadcast media platforms.
Now the challenge is managing a mix within the marketing mix – which element of the media mix delivers the best ROI? More importantly, what is the impact of the various elements of the media mix working together?
The old analytics – pencil, graph paper (and then the spreadsheet) don’t provide the right kind of analytics to answer these questions. The reason is that we find it difficult to determine relationships between cause and effect for more than two dimensions.
Just look at the chart above. It shows the variation between just two elements of the marketing mix – price and distribution – and their possible effect on sales. You have admit it is impossible to determine the relationship between these two factors and sales. And it is likely that other factors, not shown in the chart, have had greater impact on sales performance.
How can one tell?
The only safe way of determining the real drivers of sales, and the contribution of each one to sales performance is to undertake Econometric Modelling and determine Baseline Sales – what will be the outcome from maintaining the same marketing mix? Then the results of the modelling, which calculate the relationship between each part of the marketing mix and sales response, can predict how Baseline Sales will change in response to different marketing mix scenarios.
There are four main reasons why this type of data modelling will give you the answers you are looking for:
1. Because the model “thinks” in more than two dimensions
2. Because it identifies relationships that are ‘causal’ rather than just ‘coincidental’
3. Because it can derive the sales effect of each activity, singly and in combination
4. Because it can evaluate and model the impact of changes to the marketing mix and other assumptions on future sales and share performance
Econometric Modelling is at the heart of P&G’s Business Sufficiency program which enables them to look at the outcomes of alternative marketing strategies before they take the decision on which one to pursue.
Now, what’s your excuse for not doing the same?