What is TURF analysis?
TURF (Total Unduplicated Reach and Frequency) is a method for selecting the combination of products or variants that reaches the most unique consumers. It answers the question: which X products should we carry to maximize the share of potential buyers?
TURF analysis originated in media planning but has become a standard tool in assortment optimization. The basic idea is simple: given that consumers have different preferences, which combination of products reaches the most unique people? It is a reach question — not a volume question.
In its basic form, TURF works with binary data: each consumer either accepts or does not accept each product. The algorithm then searches for the combination that maximizes the share of consumers who accept at least one product in the assortment. The standard method is a greedy algorithm that selects the most popular product first, then the one that adds the most new reach, and so on.
TURF is a good starting tool but has clear limitations. It treats all consumers as equally valuable (someone who accepts but rarely buys counts the same as a high-frequency buyer). It ignores cannibalization. And the greedy algorithm does not guarantee the globally optimal answer. Reflect uses TURF as a starting point, not as the final answer.
Key takeaways
- TURF maximizes unduplicated reach, the share that accepts at least one product
- Originated in media planning, now standard in assortment optimization
- Binary data: accepts/does not accept
- Greedy algorithm, fast but not always optimal
- Good starting tool with clear limitations
Example
An ice cream producer used TURF to choose 6 flavors from 20 candidates. The TURF assortment reached 82% of consumers. But a manual adjustment — swapping a niche flavor for one with lower reach but higher frequency — increased estimated volume by 12% despite marginally lower reach.
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