Marketing Management: A Decision Theory Approach
- Posted: 25th June 2018
- Written by:
Tanmoy Barua, Systems Integration Consultant
What is Decision Theory?
Decision theory is body of methods and related analytical techniques that help a decision maker choose among a set of choices under possible consequences. Decision theory practices can help marketers to make even better decisions based on all different probable outcomes which can aid in achieving even higher revenues in their programs.
A decision maker could be one person or a firm that must choose among several “strategies”. Let’s denote these strategies as A1, A2….An. A1 here could be “marketing a product using email as the delivery marketing channel”. A2 could be “do not market the product”. The set of acts in the analysis should include all relevant and reasonable possibilities in a given situation.
Making a choice is difficult because consequence of an act depends on certain conditions and these conditions could have risk or uncertainty associated with them. A simple example – I am looking to market product X but I don’t know if marketing the product will be successful because of the existence of other similar products within the firm. Decision under certainty means that each choice leads to one and only one consequence. In decision under uncertainty, each alternative will have several possible consequences. In our example, the decision of marketing product X could mean decrease in sales of product Y or less popularity of product X because of product Y. Let’s call these conditions “states” and similar to strategies all relevant states of nature should be included in the analysis of a decision.
Assuming a given act and all the states are determined, it is possible to determine the “payoff” to the decision maker. “Payoff” is usually the value of an act under a state. These payoffs should be estimated on a net basis, which means the costs of carrying out the decision should be deducted from the estimate revenue.
Probability of State
Since the outcome of a decision can be affected by uncertainties, a key element of the analysis is to assign probabilities of the occurrence of various states which can be determined through analysis of quantitative evidence. For example, sales data could reveal that demand of a product is 20% per week in the month of July and August, 25% per week in the month of November and December. These relative frequencies could be used directly in the analysis.
Expected payoff of A2 here is 0 and the expected payoff of A1 here can be computed as follows:
$1,000,000 (0.4) – $400,000 (0.6) = $400,000 – $240,000 = $160,000
In this problem, the decision should be to market the product X which is equivalent of saying that chances of success are good enough in the case to justify the risk.
This is a simple example of how analytical techniques can be used to make the best decision for your company and brand. Adobe Campaign has built in functionalities that can help us determine some of the variables of the Decision Theory process. For example: success rate of a campaign can be used to determine the probability of state. We can use Adobe Campaign’s reporting feature to predict market trends and estimate expected revenue of a product.
At Celerity IS, we can guide you to make the best marketing decision with our experience in cutting-edge software and expertise. If you have any questions on our consulting approaches do not hesitate to reach out to us.