I believe that anybody can fit a model to a set of data – however random those data may be, there will always be relationships. Some relationships may be valid – some may be spurious and coincidental. Some relationships are probably worth checking out further – some are simply downright irrelevant.
Numbers – and data – can always be arm-twisted, bent, fashioned to meet one’s needs.
Equations and models can always be created with sufficient data points.
But what really matters is interpretation.
Based on my experience and beliefs, I have crafted the following ‘principles’ of accountability and econometrics in marketing.
It is not by all means exhaustive – if it however starts people to think about accountability, modeling, and econometrics in marketing more deeply and perhaps, get engaged in discussions, it would have reached its goal.
Marketing Communications Econometrics ‘Principles’
Draft by PTiongson • Wednesday, September 30, 2009
1. Every investment in marketing has an effect on the company’s sales or revenue.
The goal of econometrics in marketing communications is to quantify these effects and be able to compare-contrast the effects of investments in marketing channels in order to make decisions.
2. Revenues and marketing investments have don’t have a 1to1 relationship.
There is a point where additional investments in marketing will not have any significant effect on revenues or other marketing KPIs; beyond which, any additional investments are considered wasteful.
On the other hand, there is also a minimum threshold that needs to be met in marketing investments in order to ‘break through’, be competitive, and generate returns on marketing investments.
This is the economics behind marketing investments – economics is all about the optimal allocation of finite resources, and marketing econometrics is aimed at understanding the brand’s opportunities to optimally allocate finite resources that are not linearly related.
This is where the concept of S-curved and diminishing-return response rates comes in.
3. Investments in marketing communications have an immediate effect on a brand’s revenue.
Marketing communications spent in time period “t” has a measurable impact within the same time period “t”. Marketing econometrics is aimed at understanding the immediate effects of investments so decision-makers can course-correct accordingly.
4. Investments in marketing communications have a ‘lingering’ effect on a brand’s revenue.
Marketing communications spent in time period “t” has a measurable impact after time period “t” – though such an impact may well be diminished and not so strong as the initial impact.
Marketing econometrics is aimed at quantifying the persistent effect of a campaign on a brand’s revenue through the use of concepts such as decay rates and ad-stock.
5. Marketing accountability – and therefore, econometrics – needs to take into consideration differences in execution and messages.
While econometrics is a quantitative technique and a science aimed at quantifying relationships between two or more variables, it should take into account the messages that are being conveyed by the brand.
This may be achieved by incorporating dummy variables that code different campaigns of the brand, the use of granular (by-version) data, qualitatively reviewing and comparing-contrasting messages and executions, and other similar techniques.
6. Marketing econometrics should result to action points.
Econometrics should result to potential action and/or decision points for the clients. These may include (1) making decisions on how much to spend on specific brands, (2) optimizing revenues and other campaign-effects against constrained, finite budgets, (3) optimizing investment lay-down to optimize revenues and returns, (4) creating different scenarios with varying effects, and (5) deciding the optimal course of action given current knowledge.
7. Decisions about the future carry risks; these should be taken into consideration.
Econometrics is an application of statistics and probability to test hypothesis on the economics of marketing. As such, there are risks involved. The most basic of econometric models –
Yt = β0 + βiXi + εi
suggest that there are ‘errors’ that cannot fully be accounted for. These ‘errors’ – or innovations – are the source of risks that no matter how robust a certain model is, there will always be unaccounted for variation – and there will always be errors and risks.
Risks should therefore be considered in making decisions based on marketing econometrics – and any other technique.
8. Risk management principles need to be integrated into marketing econometrics.
Risk management aims at quantifying and mitigating the impact of random, stochastic variation (and shocks) in the future. Marketing econometrics provides an opportunity for marketing executives to ‘look into possible futures’ – and a basis to mitigate the effects of negative events.
In the practice of marketing econometrics, this entails not just a review of the distribution of “errors”/“residuals” and their corresponding impact on the brands’ business. This also entails the understanding of each variable/factor’s contributions and effects on the company’s revenues, and the risks they pose on the company’s revenues.