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Volume-based TURF

Volume-based TURF weights not just who is reached but how much each person is expected to buy. It gives assortment recommendations that maximize actual sales instead of number of consumers reached.

In standard TURF, every reached consumer contributes equally. That is democratic but commercially naive. A person who accepts a product but rarely buys it contributes minimally to sales. A loyal heavy buyer with strong preference contributes many times over. Volume-based TURF weights each consumer by an expected purchase value.

The weights can come from self-reported purchase frequency, actual transaction data, or a modeled purchase probability based on preference intensity. Reflect often combines acceptance data with a conversion model — not just "do you accept?" but "how likely are you to actually buy, and how often?".

The result is assortments that look different compared to reach maximization. Niche products with passionate followers can win slots over broad products with lukewarm acceptance. It requires more data but produces significantly better commercial outcomes.

Key takeaways

  • Volume weighting gives commercially more relevant assortments
  • Purchase frequency and conversion are factored in per consumer
  • Niche products with loyal buyers can beat broad products
  • Requires acceptance + frequency measurement + conversion model
  • Significantly better commercial outcomes than reach-TURF

Example

A dairy company compared reach-TURF and volume-TURF for its yogurt line. Reach-TURF recommended 6 flavors with 84% reach. Volume-TURF swapped 2 flavors: one with a narrow but loyal audience (protein) and one with high frequency (natural). Volume increased 7% over 6 months.

Related articles

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?

Limits of traditional TURF

Traditional TURF has three fundamental limitations: it maximizes reach instead of volume, the greedy algorithm can miss better combinations, and it ignores cannibalization between products.

From reach to volume

Reach tells you how many you reach. Volume tells you how much you sell. Assortment optimization should aim for volume, and that requires factoring in purchase frequency, conversion and cannibalization.

Advanced TURF: hybrid optimization

Advanced TURF combines exhaustive search, swap optimization and reverse pruning to find better solutions than the greedy algorithm. It is computationally intensive but delivers provably better assortments.

Competitive landscape and assortment optimization

Assortments do not exist in a vacuum. Competitors' assortments determine where the opportunities are. Optimal assortment optimization factors in what competitors offer and where unoccupied positions exist.

How simulation improves assortment decisions

Simulation lets you test assortment changes before implementing them. By modeling how consumers redistribute their choices when changes occur, you can predict the effect of adding, removing or replacing products.

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