What is TURF analysis?

Originally used by media schedulers to maximize the success of ad and media campaigns across channels, TURF analysis has long since been integrated into the marketing research toolbox. TURF stands for Total Unduplicated Reach and Frequency and is built of two essential components – reach and frequency.

TURF analysis is used as a decision-making tool, most often used when looking to optimize product candidates or size offerings. In a 1993 Quirk’s article, “Data Use: TURF analysis,” Ed Cohen, former president of Survey Perspectives, outlines two main objectives of TURF analysis:

  • “To identify the mix that will attract the largest number of consumers with the fewest number of entries or varieties.
  • “To calculate the incremental value to the full line of adding each additional possible product or variant.”

How is TURF analysis used? 

A popular analogy for explaining the basic usefulness of TURF analysis is the ice cream test. In this example, you imagine yourself the owner of an ice cream shop – and you have a dilemma. You have 16 different flavors of ice cream available to you, but only space in the cooler for eight. How do you choose which mix of flavors will be the most successful? Using TURF analysis, of course.

From a survey of your ice cream consumers, you devise “frequency,” or the total number of consumers who will purchase each flavor of ice cream. Then, you assemble six different arrangements of four different flavors each. Which combination are consumers most likely to favor? This is where “reach” comes in, the number of people who would choose at least one flavor from a mix.

Taking the extra step to learn reach is critical – in a mix consisting of rocky road, chocolate, vanilla and strawberry, each flavor may have a very high frequency, being individually popular. But as part of a mix, rocky road, chocolate and vanilla might appeal to the same corner of your consumers, meaning a lower reach than a more diversified mix.

TURF analysis in action

As an ice cream shop owner with a new grasp of TURF analysis, how might you put this methodology to good use? In a 2005 Quirk’s article titled, “Data Use: Unearthing TURF,” Michael Lieberman, founder and president of Multivariate Solutions, breaks down the most popular uses of TURF, including maximizing reach while minimizing costs, calculating added value of additional possible products, appealing to the most consumers with the least variety and making financial decisions.

1. Maximizing reach while minimizing costs

To continue with the ice cream analogy, as the owner of this ice cream parlor you’ll want your decision to inform the largest profit at the smallest cost. Understanding the reach of a product mix will enable you to create a lineup that reaches more consumers without having to add more flavors.

2. Calculating added value of additional possible products

Perhaps you have six standard flavors that are your best-sellers. You have no intention of removing these flavors, but you’d like to add a new cooler of flavors to the mix. Given the flavors already present, which new flavors would add the most value? TURF analysis can identify the incremental value of each added product.

3. Appealing to the most consumers

As an ice cream parlor, you want to bring the most joy to the most people. This means identifying which flavors will appeal to the most consumers. As in the current example, if the lineup includes rocky road, chocolate, vanilla and strawberry, the first three flavors may be very popular individually, but they don’t speak to the ice cream lovers who want a little more variety. TURF analysis allows for a diverse mix that will appeal to a broader set of consumers.

4. Making financial decisions

TURF analysis can be particularly helpful when it comes to optimizing a budget. If you have a budget of $600 to introduce new products to the line, TURF can help identify the maximum reach possible for $600. Conversely, if you’ve decided that your goal is a reach of 80%, meaning 80% of consumers would choose at least one product from your lineup, TURF analysis can assist in identifying the budget required to accomplish this.

Things to consider when using TURF analysis

In the idealized scenario of the ice cream parlor, TURF analysis can be examined under a clean, scientific lens – but real-life scenarios are rarely so uncomplicated. In a 2018 Quirk’s article, “Optimizing product assortments takes more than consumer data,” Stephen Needel, managing partner at Advanced Simulations LLC, uncovers some of the difficulties of employing TURF analysis when the vendor doesn’t have complete control over the environment.

For example, the owner of an ice cream parlor can dictate which flavors to purchase and how they’re arranged, but this monopolistic choice environment falls apart in a retail setting, where, as Needel points out, “whatever assortment they select for themselves is subject to a retailer’s whims and to competitive effects.” Even if a rocky road- vanilla-chocolate mix is ideal from a vendor’s point of view, a grocery store may choose to reject one of these flavors if they are already well-stocked by another brand.

Additionally, the demographic of one grocery store may be different from another store, meaning that the popular ranking of flavors for different stores may vary wildly from the optimal mix chosen for a representative sample.

Finally, Needel argues, TURF analysis can suffer from weaknesses on both the input and the output sides. On the input side, questions measuring purchase likelihood offer a limited psychometric viewpoint. On the output side, TURF analysis can sometimes require choices made between mixes with incremental differences, which can lead to skewed decision-making later in the analysis.