How to Interpret TURF Analysis Results
What TURF Output Looks Like
TURF analysis produces three core outputs: the optimal item combination at each portfolio size, reach and frequency metrics for each combination, and an incremental reach curve showing diminishing returns. Understanding how to read each one turns the algorithmic output into portfolio decisions.
Reading the Optimal Combination Table
The main TURF output ranks item combinations by reach:
| Portfolio Size | Items | Reach | Frequency |
|---|---|---|---|
| 1 | Chocolate | 62% | 1.0 |
| 2 | Chocolate, Strawberry | 78% | 1.6 |
| 3 | Chocolate, Strawberry, Mint | 87% | 2.1 |
| 4 | Chocolate, Strawberry, Mint, Mango | 92% | 2.5 |
| 5 | Chocolate, Strawberry, Mint, Mango, Cucumber | 94% | 2.7 |
| 6 | + Vanilla | 95% | 3.1 |
What Reach Means
Reach is the percentage of respondents for whom at least one item in the combination is acceptable. A reach of 92% at portfolio size 4 means 92 out of 100 respondents would find at least one of those four items appealing. The remaining 8% aren't served by any item in the set.
Reach always increases (or stays flat) as you add items. It can never decrease because adding an item can only bring in new people, not repel existing ones.
What Frequency Means
Frequency is the average number of acceptable items per respondent within the combination. At portfolio size 4 with frequency 2.5, the average respondent finds 2-3 of the four items acceptable.
Low frequency (near 1.0) means most people have exactly one option. High frequency (3+) means variety and choice. The right target depends on your business context. For restaurants relying on repeat visits, you want frequency above 2. For a one-time product purchase, frequency of 1+ is sufficient.
Spotting Surprise Items
Look for items that enter the optimal portfolio despite low individual popularity. In the example above, Cucumber might have only 25% individual acceptance, but it enters at position 5 because its fans are almost entirely people who don't like the first four items. These "reach extenders" are TURF's most actionable finding.
Conversely, look for popular items that never enter the optimal portfolio. Vanilla (65% individual acceptance) doesn't appear until position 6 because most Vanilla fans already like Chocolate or Strawberry. Vanilla adds minimal incremental reach despite being individually popular.
Reading the Incremental Reach Curve
Plot portfolio size against reach. The curve rises steeply at first and flattens.
The key metrics:
- Steep section (items 1-3): Each item adds significant reach. These are your must-haves.
- Inflection point (usually items 3-5): Incremental reach starts dropping below 5% per item. This is your natural portfolio size.
- Flat section (items 6+): Each item adds 1-2% reach. Adding these items has marginal audience impact.
The business decision sits at the inflection point. If going from 4 to 5 items adds 2% reach but costs $50K in manufacturing, you need 2% of your market to be worth more than $50K. This is where TURF meets business judgment.
Incremental Reach Table
| Added Item | Incremental Reach | Cumulative Reach |
|---|---|---|
| Chocolate | +62% | 62% |
| Strawberry | +16% | 78% |
| Mint | +9% | 87% |
| Mango | +5% | 92% |
| Cucumber | +2% | 94% |
| Vanilla | +1% | 95% |
The first item always has the highest incremental reach (it starts from zero). Each subsequent item's incremental reach is guaranteed to be equal to or lower than the previous. When incremental reach drops below your threshold of meaningful impact (often 2-3%), that's your stopping point.
Segment-Level TURF
Running TURF separately by segment reveals whether different audiences need different portfolios.
Example: Age Segments
| Portfolio Size 4 | 18-34 Optimal | 35-54 Optimal | 55+ Optimal |
|---|---|---|---|
| Item 1 | Mango | Chocolate | Vanilla |
| Item 2 | Strawberry | Vanilla | Chocolate |
| Item 3 | Mint | Strawberry | Strawberry |
| Item 4 | Cucumber | Mint | Peach |
| Reach | 91% | 89% | 88% |
If you can only offer one portfolio (single shelf, one menu), run TURF on the combined sample. If you can customize by segment (regional menus, targeted digital assortments), segment-level TURF produces higher total reach.
Comparing Segment Portfolios
Look for items that appear in all segments' optimal sets. These are universal items that belong in any portfolio. Items that appear in only one segment's optimal set are candidates for segment-specific offerings.
Comparing to Your Current Portfolio
The most actionable TURF analysis compares the optimized portfolio against your existing one.
Calculate the reach of your current portfolio using the same data. If your current 10-item lineup achieves 82% reach and the TURF-optimal 8-item lineup achieves 88%, you have a clear case: a smaller portfolio serves more people.
Identify specifically which items in your current portfolio are the weakest. These are items whose removal causes the smallest reach drop. If removing Item X drops reach from 82% to 81.5%, that item serves almost no one who isn't already covered by other items.
Frequency vs. Reach Trade-Offs
Sometimes the highest-reach portfolio has low frequency (everyone has exactly one acceptable option but no variety). You can run TURF with a dual objective: maximize reach while maintaining minimum frequency above 2.0.
This trade-off appears most in repeat-purchase categories (restaurants, subscription boxes, streaming services) where customers need variety to stay engaged. In one-time-purchase categories (phones, cars), reach alone is the right objective.
Presenting TURF Results
For Executive Audiences
Lead with two numbers: "We can serve X% of customers with Y items." Follow with the recommendation: "These Y items are..." Show the reach curve to illustrate diminishing returns, and highlight the 1-2 surprise items that TURF recommends that individual popularity wouldn't suggest.
For Product/Operations Teams
Add the incremental reach table, segment breakdowns, and the comparison to the current portfolio. Include the items recommended for removal and the expected reach impact. Flag any business constraints that might override TURF recommendations.
Avoiding Misinterpretation
- Don't equate reach with revenue. A 92% reach portfolio isn't automatically better than an 88% portfolio if the missing items are high-margin.
- Don't present TURF as deterministic. It optimizes for one metric (reach). Margin, brand strategy, and operational feasibility are separate inputs.
- Do present the sensitivity analysis (how results change with different acceptance thresholds).
Frequently Asked Questions
What does it mean when reach plateaus early?
If reach hits 90% at portfolio size 3, your item set has high individual acceptance and moderate overlap. Most combinations perform well. This is common with broad-appeal categories (mainstream food items). It means you have flexibility: many different portfolios achieve similar reach.
How do I know if my TURF results are reliable?
Check two things: sample size (200+ for single-population TURF) and acceptance threshold sensitivity. If the same items appear in the optimal portfolio across strict and moderate thresholds, the results are strong. If the portfolio shifts dramatically with threshold changes, the data is noisy.
Can TURF tell me which items to add to an existing portfolio?
Yes. Lock in your existing items and run TURF at portfolio size = current + 1. The algorithm will identify the single item that adds the most incremental reach to your current lineup.
Related Guides
- TURF Analysis: Complete Guide -- Full methodology overview
- How to Run TURF Analysis -- Step-by-step execution guide
- TURF Analysis Examples -- Case studies with interpretation
- TURF Analysis for Product Development -- Applying TURF to product portfolios
- MaxDiff Interpretation -- Reading item priority scores
- Conjoint Analysis Interpretation -- Comparison with trade-off analysis output
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