Welcome to the Marketing Math section on Marketing Binder. In this section you will find marketing calculators, math formulas, and marketing math explanations. This section is currently being developed and new marketing math formulas and explanations are being added weekly, until we complete the entire section which will be a mega resource for both marketing students and marketing professionals.
The section below provides a brief discussion on marketing math essentials. You will find the marketing math formula and calculators menu to the right side of this page. If you have any comments or would like to provide your feedback, please contact us.
Marketing Math Essentials
Marketing managers are increasingly faced with the accountability for financial implications of their marketing actions. This section of Marketing Binder introduces formulas and calculations in measuring marketing financial performance.
The marketing calculations presented in the Marketing Math Essentials section of this site are important in the sense they are foundational to marketing and that they are simple to calculate. Effective marketers understand that the quality of their qualitative inputs are important for good analyses. When it comes to analyzing marketing situations and issues of validity and reliability, managers should look for data inputs in the order of the four types of inputs below:
- Hard numbers
- Company/Industry averages
- Educated guesses
- Wishful thinking
Four Types of Data Inputs
This section of marketing math outlines, briefly, the above four types of data inputs.
Hard number inputs are are:
- market shares
- size of customer bases
- other reliably measured data
Other types of hard number data can result from a combination of marketing research, econometric modeling, and managerial judgement.
Company/Industry Average inputs are well-established averages typical for a company or industry. As useful as these numbers are, they should be adjusted to fit the current product and situation.
Some general, U.S. industry benchmarks are listed below. Data assumptions that stray from these numbers may be valid, but require stronger justification.
Educated guesses inputs are based on professional experience or common beliefs. They may be based on experience with a specific product or market. An example of an educated guess would be that it takes one to three advertising exposures to tap into a consumer’s conscious awareness. As a side note, educated guesses in marketing math should only be used as a last resort when supplementing hard data.
Wishful thinking inputs have no basis in reality and are often used to make marketing objectives look achievable, regardless of their true merit. These types of inputs should not be used except in sensitivity analyses.
Source and additional reading: Marketing Math Essentials, The Wharton School, University of Pennsylvania