What is TURF analysis? Total unduplicated reach & frequency

Struggling with campaign effectiveness? TURF analysis reveals your true audience reach and frequency patterns for smarter media planning.

How Turf Analysis Can Transform Your Market Research

Total Unduplicated Reach and Frequency, or TURF analysis, is a method that helps you measure the unique number of people reached by a product or message without counting anyone twice. It uses straightforward statistics to determine both the spread and repetition of audience exposure, making it a reliable tool in market research. This method provides insights into which parts of a product portfolio resonate best with various audience segments and explains why some offerings might perform better than others. By outlining a clear process, TURF analysis also shows how to compare different market research methods and understand their specific strengths. It’s a practical approach designed to connect research data with real-world product decisions.

What is TURF analysis and how does it work?

TURF analysis—Total Unduplicated Reach and Frequency—is the market research technique that answers this critical question.

TURF analysis helps companies determine the optimal combination of products, features, or marketing messages that will reach the maximum number of consumers without redundancy. At its core, TURF analysis measures two key metrics:

• Reach: The percentage of consumers who would select at least one option from a given set

• Frequency: The average number of options each consumer would select from that set

The "unduplicated" aspect is what makes TURF particularly valuable. Traditional methods might simply count all positive responses across products, but this approach counts consumers multiple times if they like several products. TURF eliminates this double-counting by identifying the unique consumers reached by each combination.

Here's how it works in practice: Imagine a snack company testing five potential new flavors. Rather than launching all five (expensive) or guessing which will perform best (risky), TURF analysis would:

1. Collect consumer preference data through surveys

2. Calculate the reach of each possible combination (single flavors, pairs, trios, etc.)

3. Identify the optimal combination that maximizes unique consumer reach with the fewest products

For example, TURF might reveal that while "Spicy BBQ" and "Tangy Ranch" individually score highest, they appeal to the same consumer segment. Adding "Sweet Honey" instead of "Tangy Ranch" might reach more unique consumers despite its lower individual score.

TURF analysis works through iterative calculations, examining how each potential combination performs in reaching unduplicated consumers—making it an invaluable tool for portfolio optimization and efficient resource allocation.

Step-by-step guide to conducting TURF analysis

Ready to run your own TURF analysis? While it may sound statistically complex, breaking it down into manageable steps makes the process straightforward. Here's your practical roadmap:

1. Define your research objectives

Begin by clarifying exactly what you're trying to optimize—product assortment, feature combinations, messaging options, or flavor profiles. Set clear parameters for what success looks like (maximum reach with how many options?).

2. Design your data collection method

Create a survey that asks respondents which options they would choose, purchase, or use. This typically involves:

• Presenting all potential options (products, features, etc.)

• Asking which ones they would select

• Gathering demographic information for segment analysis

3. Collect sufficient data

Ensure your sample size is robust—generally 300+ respondents for reliable TURF analysis. The sample should represent your target market accurately.

4. Run the TURF calculations

Using specialized software (like SPSS, Sawtooth, or dedicated TURF analysis tools):

• Input your preference data

• Set parameters for the analysis (maximum number of items in combinations)

• Run the algorithm to calculate reach for all possible combinations

5. Generate the TURF table

The output will show reach percentages for various combinations, typically arranged from highest to lowest reach.

6. Identify the optimal combination

Look for the "elbow point" where adding more options produces diminishing returns in additional reach. This often appears as a noticeable flattening in the reach curve.

7. Validate with secondary metrics

Cross-check your TURF results against other important factors:

• Production costs

• Cannibalization concerns

• Brand fit

• Operational feasibility

Most market research platforms now offer built-in TURF analysis capabilities, making the technical aspects more accessible than ever. The key is ensuring your data collection is sound and your interpretation aligns with business objectives.

How to interpret TURF analysis results effectively

Are you staring at TURF analysis results wondering what they actually mean for your business? Making sense of TURF output requires understanding both the numbers and their strategic implications.

The typical TURF analysis report presents multiple product combinations with their corresponding reach percentages. Here's how to extract meaningful insights:

Understanding the reach curve

Plot your reach percentages against the number of products in each combination. The resulting curve typically shows:

• Steep initial increases (first 2-3 products)

• A visible "elbow point" where returns start diminishing

• A plateau where additional products contribute minimal additional reach

This elbow point often indicates your optimal product assortment size.

Analyzing frequency metrics

While reach tells you how many unique customers you'll attract, frequency reveals intensity of interest:

• Low frequency with high reach: Broad but shallow appeal

• High frequency with moderate reach: Deep appeal within a specific segment

• High frequency and high reach: Potential market winners

Examining specific combinations

Look beyond just the highest-reaching combination to understand:

• Which products appear most frequently in top-performing combinations

• Products that rarely appear in high-reach combinations (potential cuts)

• Surprising combinations that outperform individual high-scorers

Segment-level insights

Break down your TURF results by consumer segments to discover:

• Different optimal combinations for different demographics

• Opportunities for targeted offerings

• Potential for phased product launches to specific segments

Common interpretation pitfalls to avoid

• Ignoring practical constraints: The mathematically optimal combination might not align with production capabilities or shelf space realities.

• Overlooking cannibalization: Some combinations might maximize reach but create internal competition.

• Missing complementary effects: Some products perform better together than their individual scores suggest.

Remember that TURF analysis is a decision support tool, not a decision-making replacement. The final product assortment should balance mathematical optimization with brand strategy, operational feasibility, and market positioning.

Differences between TURF analysis and other market research methods

How does TURF analysis compare to other research approaches you might already be using? Understanding these distinctions helps you choose the right tool for each research question.

TURF vs. MaxDiff Analysis

Aspect	TURF Analysis	MaxDiff Analysis
Primary purpose	Optimizes product combinations for maximum unique consumer reach	Identifies relative preference or importance of individual items
Output	Reach percentages for various product combinations	Preference scores for individual items
Best for	Portfolio optimization, assortment decisions	Feature prioritization, understanding preference hierarchies
Considers interactions	Yes - accounts for overlap in preferences	No - treats items independently
Sample size needs	Moderate to large (300+)	Can work with smaller samples (200+)

TURF vs. Conjoint Analysis

Aspect	TURF Analysis	Conjoint Analysis
Primary purpose	Maximizes unduplicated reach across product lineup	Determines value of specific product attributes and price sensitivity
Complexity	Relatively straightforward	More complex design and analysis
Output	Optimal product combinations	Part-worth utilities, importance scores, market simulators
Best for	Product assortment decisions	Product design, pricing strategy, market share prediction
Time requirement	Quicker to execute	More time-intensive

TURF vs. Simple Preference Testing

Aspect	TURF Analysis	Simple Preference Testing
Primary purpose	Optimizes product combinations	Identifies most popular individual options
Accounts for consumer overlap	Yes	No
Complexity	Moderate	Low
Output sophistication	High - shows optimal combinations	Basic - shows ranked preferences
Best for	Efficient resource allocation	Quick directional guidance

When to choose TURF analysis

TURF analysis shines when:

• You need to make assortment decisions with limited resources

• You want to maximize consumer reach with the fewest products

• You suspect significant overlap in consumer preferences

• You need to optimize across multiple consumer segments

The key advantage of TURF over simpler methods is its ability to account for the unduplicated aspect of consumer reach—preventing the common error of double-counting consumers who would choose multiple products. This makes it particularly valuable for efficient portfolio management and resource allocation.

Final Thoughts

TURF analysis represents a powerful approach for brands seeking to understand and maximize their market potential. By providing a nuanced view of product reach and consumer preferences, this methodology offers more than just numbers—it delivers strategic insights that can fundamentally reshape product portfolios and marketing strategies.

The true value of TURF analysis lies in its ability to move beyond traditional market research techniques. It's not just about collecting data, but about understanding the complex intersections of consumer choice and product appeal. Whether you're managing a small product line or a diverse brand portfolio, TURF analysis can help you make more informed decisions that resonate with your target audience.

At its core, TURF analysis is about precision—understanding exactly how different products connect with consumers and identifying opportunities for strategic growth. By carefully examining unduplicated reach and frequency, brands can craft more targeted, effective approaches that speak directly to consumer needs.

Our team at Highlight continues to support brands in navigating these complex market research landscapes, helping transform raw data into meaningful, actionable insights that drive real business success.