TURF Analysis

What is TURF Analysis?

The Definition

TURF analysis stands for “Total Unduplicated Reach and Frequency.” It is a research technique that helps organizations gauge the appeal and reach (i.e., willingness to buy) within a market for a combination of products, features, or messages. TURF provides insight into maximizing the number of people you can connect to and address with various lineups.

How is it conducted?

TURF analysis is strictly a methodology to analyze data after collection and can be applied to a variety of survey techniques. The data foundation that allows for a TURF calculation to be applied is a binary indication of whether variables “reach” a respondent.  It most commonly ran on multi-select questions in MaxDiff projects (e.g., “Select all the candy bars you would be interested in purchasing”) where each individual in the respondent set has a preference for the tested attributes.

What business objectives does TURF analysis answer?

There are key business research objectives that TURF can deliver on.  TURF analysis has core questions that it specializes in answering, which include:

• What messaging and marketing campaigns connect best with our market?
• What is the optimal product lineup to reach the largest population?
• What subset of services provide the biggest return on investment, and allow us to best focus our operations?

Calculation and Metrics of TURF Analysis

Calculation Overview

The Qualtrics TURF analysis offering is conducted on MaxDiff projects.  The TURF analysis is conducted by calculating the percentage of respondents that are reached or addressed by all of the different product/feature/message lineups being tested.

Qualtrics has two calculation approaches used within the MaxDiff XM solution:

• Top Choice: This method is calculated by looping through each package combination and deriving the percentage of the sample that is reached. The researcher can define if being “reached” means that the item has to be a respondent’s top overall choice (this is a First choice methodology) or preference or in their top two (this is a Top 2 choices methodology).
• Weighted Probabilities: This method incorporates the principles of the multinomial logit modeling used to derive the MaxDiff utility preferences.  It calculates the probability that a combination of items would be selected as most preferred, weighted by the item’s preference share.

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