Preference-rank Translation
Shop for probability marketing books. Get Preference-rank Translation essential facts below. View Videos, Research or join the Preference-rank Translation discussion. Add Preference-rank Translation to your topic list for future reference or share this resource on social media.
Preference-rank Translation

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

A survey might ask a question using a ranking scale such as :

A marketing researcher will re-specify the numerical values during codification. 1 will become 5, 2 will become 4, 4 will become 2, 5 will become 1, and 3 will remain the same. In this way greater values will correspond with greater preference.

Next, the researcher uses a data reduction technique like factor analysis to obtain aggregate scores. To convert these aggregate rankings into purchase probabilities, each category (in this case, each product) will be weighted with a translation coefficient. These weights are predefined.

A typical weighting scheme is:

The weighting schemes vary depending on the variables being measured.

The following chart illustrates the procedure:

score rank weight probability
product A 6.4 2nd .17 1.1
product B 5.1 4th .02 .1
product C 8.7 1st .75 6.5
product D 4.3 5th 0 0
product E 5.5 3rd .06 .3

Other purchase intention/rating translations include logit analysis and the intent scale translation.

See also

  This article uses material from the Wikipedia page available here. It is released under the Creative Commons Attribution-Share-Alike License 3.0.

Preference-rank_translation was developed using's knowledge management platform. It allows users to manage learning and research. Visit defaultLogic's other partner sites below: : Music Genres | Musicians | Musical Instruments | Music Industry
NCR Works : Retail Banking | Restaurant Industry | Retail Industry | Hospitality Industry