TURF optimization

TURF, which stands for "Total Unduplicated Reach and Frequency," is an optimization method that identifies a subset (portfolio) of items that maximize the number of respondents reached.

Originally developed for broader survey research, TURF can also be used in MaxDiff studies. Rather than simply selecting the most preferred items on average, TURF identifies combinations that most effectively motivate, satisfy, or appeal to the largest number of respondents.

For example, when deciding which ice cream flavors to stock in a store, TURF can help maximize customer appeal given limited shelf space. Selecting only the most preferred flavors may overlook niche options that appeal to distinct segments, decreasing overall reach.

Suppose most respondents enjoy vanilla, chocolate, and cookie dough. While offering just these flavors may appear optimal, if many respondents are satisfied with any one of these options, substituting one or even two with a less common flavor like strawberry or mint chocolate chip could expand reach and boost sales.

This approach helps businesses to identify market preferences that improve both reach and profitability.

Different reach methods — Weighted by probability, First choice, and Threshold — often result in varying optimal portfolio outcomes.

For MaxDiff data, we typically recommend the Weighted by probability approach because it effectively utilizes information from potentially sparse data. It is also more stable—minor changes, such as adding a few respondents, are less likely to disrupt the rank order of optimal portfolios compared to the First choice and Threshold methods.

The First choice approach makes less efficient use of detailed preference data and is more sensitive to small data changes, which can significantly change the rank order of outcomes.

The Threshold approach falls between First choice and Weighted by probability in terms of efficiency, but determining the ideal threshold value for MaxDiff data can be challenging.

Since many TURF solutions tend to deliver similar reach levels, this overlap can be viewed as an opportunity. Additional criteria, such as expert judgment, can help determine the most suitable portfolio to address the business problem. For instance, if a grocer observes that a frequently appearing flavor spoils quickly, they might prefer an alternative portfolio with a comparable reach that mitigates this risk.