purchase probability

It takes survey data on consumers' preferences and converts it into actual purchase probabilities.

The resultant functional relationship defines purchase probability.

Kotler proposes a causal chain, connecting atmosphere and purchase probability:

Next, the researcher uses a predefined functional relationship to convert the stated intentions into estimates of actual purchase probabilities.

To convert these aggregate rankings into purchase probabilities, each category (in this case, each product) will be weighted with a translation coefficient.

This occurs in an automated fashion on massive marketplaces such as Amazon.com and their classification and prediction of product associations and purchase probability.

Preference-rank translation is a mathematical technique used by marketers to convert stated preferences into purchase probabilities, that is, into an estimate of actual buying behaviour.

It is the "conscious designing of space to create certain effects in buyers" or more precise, "the effort to design buying environments to produce specific emotional effects in the buyer that enhance purchase probability".