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Does a Simulated Yogurt-Choice Study Match Human Behavior? The Ares Replication

A simulated conjoint study on functional yogurt reproduced the attribute ordering found in a published human study, with a rank correlation of rs = .7723, p = .009. For a CPG or consumer-research leader deciding whether to trust a simulated study's ranking of choice-driving attributes, that result shows the ordering direction can replicate. It does not show individual-level prediction, calibration, or performance across subgroups.

Two-column comparison. Left, "Confirmed": attribute ordering direction agrees. Right, "Not established": individual prediction, calibration, subgroup performance, cross-category generalization.
A significant rank correlation confirms the two studies agree on attribute ordering, and nothing else.

Why the decision matters

A CPG team weighing a simulated conjoint study against a fielded human study needs to know whether the simulation recovers the same decision ordering, not just a plausible-sounding result. Treating a directional rank correlation as individual-level prediction, calibration, subgroup validity, or a guarantee across products risks a launch decision built on a simulated ranking that generalizes further than the replication supports.

What the replication compared

Ares et al. published a 2009 choice-based conjoint study asking how three factors unrelated to taste or texture shaped whether shoppers picked functional yogurt over regular yogurt. A matched simulated study compared its attribute-ranking output against the same three factors. The rank correlation between the two orderings is the outcome measured.

Evidence

StudyPopulationMethodResult
Ares et al., published in Food Quality and PreferenceHuman respondentsChoice-based conjointAttribute ordering across three non-sensory factors
Matched simulated replicationSimulated studySimulated choice comparison against the same three factorsrs = .7723, p = .009

The rank correlation of rs = .7723 (p = .009) is a directional statement about whether the two orderings agree. It says nothing about how closely individual respondent choices matched, and it does not carry over to a different product category without its own replication.

Three validation options

Three ways exist to check whether a simulated ranking is trustworthy for a given category: trust the simulated study alone, run a fielded human study alone, or compare the two against a matched human study, as in this replication. Only the third produces a testable correlation instead of an assumption.

Recommended decision process

  1. Identify the published or fielded human study that covers the same product category and choice factors.
  2. Run the matched simulated study against the same attributes and alternatives.
  3. Compute the rank correlation between the two attribute orderings, and report the p-value alongside it.
  4. Treat a significant, positive correlation as support for using the simulated ordering as a first-pass read, not as a substitute for category-specific validation.

Where Subconscious fits

The replication leaderboard shows how Subconscious tests studies against real human participants, letting a team move from a simulated experiment to real-human validation without changing the underlying causal question. Teams evaluating packaging, claims, or assortment decisions in CPG can use the same matched-replication approach before extending a simulated ranking to a new product line. The broader research method is documented on the research page.

Limitations and failure conditions

One conjoint replication does not establish individual-level fidelity, calibration, subgroup performance, causal identification, or general validity across products. The rank correlation measures whether the ordering of factors agrees between the two studies; it does not measure preference magnitude, choice share, or any individual respondent's decision. Applying this result to a different product category, attribute set, or subgroup decision needs its own matched replication first.

Sources