TURF Analysis, which stands for "Total Unduplicated Reach and Frequency," is a statistical analysis methodology used by researchers and businesses to estimate market and/or media potential. TURF is commonly used in product line research.

In This Article

• Reach & Frequency
• Designing a Ratings-Based TURF Study
• Example of a Ratings-Based TURF
• Building a TURF-Compatible Question
• Creating a Virtual Question for Analysis
• TURF Analysis Options
• Using the Built-in TURF Simulator
• TURF Simulator Tab
• All Combinations Tab
• Requesting a Custom TURF Simulator

Reach & Frequency

The primary objective of a TURF analysis is to identify the set, or combination, of items that appeal to the widest audience. TURF assumes that the item line-up should be developed to provide at least one item for as many consumers as possible, commonly referred to as maximizing consumer reach.

The results of a TURF provide you with two metrics:

1. Reach

   Percent of the audience that is "reached" by at least one product in the set or line. What constitutes reach must be defined by the researcher for the analysis to be conducted. Most often, this is a Top Box or Top 2 Box rating on a 5-point purchase intent scale (e.g., definitely would buy, definitely or probably would buy). Also referred to as Unduplicated Reach.

   Maximizing Reach is the most common objective in a TURF analysis, making this the key output.

2. Frequency

   The average number of items in the set that reach a given respondent. Frequency should not be interpreted as purchase frequency or volumetric purchase interest. In contrast to Reach, which removes duplication among consumers for a set of products, Frequency measures any overlap that may exist. Increases in frequency indicate an increase in the average number of viable "back up" options consumers may have at the shelf should their preferred product be unavailable.

   Although it is a standard output of TURF, Frequency as a metric is typically considered tertiary behind Reach and raw item scores (e.g., Top Box, Top 2 Box).

The most common set-up employed for a TURF study is a ratings-based design. Often in product line research, this takes the form of a 5-point purchase intent question asked and answered for every product by every respondent. This article focuses specifically on ratings-based TURF.

Designing a Ratings-Based TURF Study

For a successful TURF result, it is critical that every item to be included in the TURF analysis be evaluated by every respondent. The analysis needs to know whether or not each item, independent from other items, "reaches" each respondent.

Input:

• Since all respondents need to evaluate all products for a successful TURF analysis, keep the number of products to test reasonable enough for respondents to evaluate in one survey.
• If only asking purchase intent for each product, we recommend including no more than 30 products maximum. If measuring multiple metrics per product, or including a large question set outside of ratings for a TURF analysis, reduce the number of items.
• Other scales can be used, such as an appeal-oriented scale, but keep in mind the design used will be the basis of interpretation for the analysis. If your goal is to report a line-up with the highest reach of consumers where reach implies purchases, then a purchase-oriented scale should be used.
• As with any concept test, be sure to randomize the order of items being evaluated to reduce order bias.

Output:

• With a ratings-based design, reach is typically defined as a Top Box or Top 2 Box response, possibly more depending on the number of scale points (e.g., Top 3 Box on a 10-point scale). Using a stricter definition of reach is more conservative and will result in lower overall reach and frequency values, and vice versa for more lax reach definitions.
• While Top 2 Box (purchase intent) is a popular metric to report in any concept test, using Top Box as reach criteria for TURF analysis has many benefits. Unlike conjoint and other advanced methodologies, TURF does not simulate choice or predict interest in an item in the context of other options. Using Top Box as reach ensures the inclusion of only the most appealing products, and is likely to have purchase intent that translates to real-world purchase. Top Box also provides a lower starting point to grow incremental reach as products are added to a lineup.

Example of a Ratings-Based TURF

Now that you're familiar with the methodology of a ratings-based TURF, let's walk through building one in the aytm platform.

We recommend programming with a Smart Loop, a feature that lets you set up your concept test using automation. Smart Loop streamlines the programming of your survey and sets you up for success when analyzing your results: it powers the one-click presets you'll use to build the Virtual Question that TURF actually runs on.

In this example, we have 20 new product concepts and will ask respondents about their purchase intent along a 5-point scale. To follow along, open a new draft survey or visit the Editor page of an existing survey.

Building a TURF-Compatible Question

TURF runs on question types that capture a rating for every item from every respondent. The supported types are Sliders, Progressive Matrix (radio-button style), Checkboxes, and Star/Smiley rating.

For a question to appear in the TURF export, it also has to meet a size threshold:

• Rating-style questions (Sliders, Progressive Matrix, Star/Smiley) need at least two items being rated and at least three scale points. [CONFIRM: preferred UI wording for "batches" and "answer variants"?]
• Checkbox questions need at least two answer options.

If a question doesn't meet these thresholds, it won't show up in the question list on the Export tab.

1. Add a TURF-compatible question type to your survey, hover over the question, and click Convert Into a Smart Loop.
2. Input all the product concepts in the Smart Loop table. You can add text, images, or videos in the columns. The first row holds the named variables that will be used in the automated aytm logic.
3. When you've programmed all your variables, create your question set. The variable names from the Smart Loop table customize each run. In this example, one variable, [name], pipes in each concept's product name, and [image:x] adds the corresponding concept image. The :x notation expands the image to full size.
4. Preview your survey. The Smart Loop will create a separate run of the question set for each item, concept, or product.
5. Continue building your survey. Watch out for the length of your survey—keep in mind the number of questions already reserved by the Smart Loop.

💡 Tip: In a TURF, every respondent must evaluate every concept—so be sure the Smart Loop is set to Show All runs/respondent.

Creating a Virtual Question for Analysis

A Smart Loop unfolds into a separate run for each concept, which means the platform sees one small question per concept rather than one question covering all 20. Individually, none of those runs is large enough to qualify for TURF, so none of them will appear in the TURF Analyses list.

To analyze the loop, stack the runs back together into a single Virtual Question (VQ). This is what the Smart Loop one-click presets are for, and it's the question you'll run TURF on.

1. Open your survey's results page and click Analysis in the left sidebar.
2. Click Virtual Question. A Virtual Question editor opens in the main area.
3. Click the question dropdown—it defaults to showing your survey's questions grouped by Smart Loop run (e.g., Q25, Q28, Q31 under Group 1). Select the group that corresponds to your purchase intent question across all concepts.
4. Each concept from the Smart Loop appears as an answer row (A1, A2, A3…). Review them to confirm the mapping looks correct.
5. Click Generate visualization. The Virtual Question is saved and will now appear in the question list on the Export tab.

⚠️ Note: Skip this step and your purchase intent question won't be selectable in the TURF export. If your question list looks empty or only shows unrelated questions, the Virtual Question is almost always what's missing.

TURF Analysis Options

You can choose between two options for analyzing TURF:

1. Export our built-in TURF simulator from the aytm platform.
2. Work with Research Services to obtain a custom TURF simulator. If you're testing more than 15 concepts [CONFIRM: 15-concept threshold—needs Research Services sign-off] or need to analyze multiple subgroups of the data, you'll need a custom simulator.

Using the Built-in TURF Simulator

1. Navigate to the Export tab in the left menu to download your data.
2. Choose the TURF Analyses option.
3. Select your question—for a Smart Loop concept test, this is the Virtual Question you created above.
4. Select your reach definition. Rating-style questions display a set of reach options; pick one before downloading. Checkbox questions skip this step, since selecting an option is itself the definition of reach.
5. Click Download file.

Choosing a Reach Definition

On a 5-point purchase intent scale, the panel generates four reach options. aytm builds them from both ends of the scale, because scale direction varies from question to question—so you'll see a Top 1 Box and a Top 2 Box option anchored at each end.

Pick the pair that matches your positive end. If A1 is "definitely would buy," choose the A1 options; if A5 is, choose the A5 options. Selecting from the wrong end will report the least appealing concepts as your highest-reach line-up.

TURF Simulator Tab

Once you have the pre-formatted spreadsheet open, you'll see two tabs of contents: TURF Simulator and All Combinations.

The TURF Simulator tab provides an interface for exploring combinations of items, one set at a time, and returns four outputs:

Both Frequency columns answer the same question—how many items in this set reach a given person—and differ only in who's counted in the base.

This tab also provides a column to input a cost for each item, along with Total Available, Used, and Remaining Budget inputs to represent the effort associated with a set of items against the pool of resources available.

⚠️ Note: These values are simple calculations of the total cost of the set of items at face value. They aren't tied back to reach or to a percentage in an attempt to understand revenue returns if a set of items were to be introduced to the market.

All Combinations Tab

The All Combinations tab holds all possible set combinations for the items being tested, with each combination's output metrics and the underlying data that powers the simulator tab. Its columns are:

• CombID—the identifier for each combination.
• Reach
• Frequency Among Reached
• Frequency Among Total
• Number of Combinations

It's important to note that the All Combinations tab may not truly hold all of the possible combinations. As the number of items being tested grows, the number of possible combinations grows exponentially. For that reason, the possible set sizes that can be simulated are cut off when more than 19 items are being tested.

Requesting a Custom TURF Simulator

If you're unfamiliar with TURF or need custom analysis beyond what our built-in export supports, our Research Services team offers custom quotes for TURF simulators and expert analysis.

Key features of a custom simulator include:

• No limits on set sizes based on the number of items tested.
• Support for data filters to explore multiple subgroups within one file.
• Support for multiple reach definitions via a dropdown (e.g., Top Box and Top 2 Box), so you can switch between them without re-exporting.
• A preview of the "next best" addition to an existing simulated set, by Reach and Frequency.
• A template for building a chart of Reach incrementality, often called an elbow or whale's tail.

To speak with our team about your next TURF project, open a support ticket or start a live chat.

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