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AUDIENCE SIMULATION

Simile

Behavioral simulation: Human-behavior simulations designed to explore reactions to changing products, prices and policies.

PRODUCT PROFILE

About this product

Simile describes a behavioral-simulation system intended to estimate how a population may respond to a defined situation. The supplier frames the system around both observed behavior and research about motives, then attaches a question-level confidence estimate to its simulated output.

Product details

Information from the company's product materials.

Primary category
Audience simulation

Simile models a population's distribution of possible actions under a specified scenario, population and action set.

Simile: Building the What-If Machine · Simile: Building confidence in Simile

Offering
Behavioral simulation

The provider describes simulations for questions about products, prices, policies, messages and other changed conditions.

Simile: Building the What-If Machine

Research posture
Scenario-specific estimates

The published workflow returns a distribution over possible actions and surfaces a modelled confidence estimate for each question.

Simile: Building confidence in Simile

Access
Supplier engagement

The public product material reviewed does not state a self-service plan or price for this simulation workflow.

Simile: Building the What-If Machine

Research methods and outputs

Methods described by the company.

  • Defined population, situation and action space

    Simile describes accepting a natural-language prompt specifying the population, situation and valid actions, then returning an estimated distribution over the actions.

    Simile: Building confidence in Simile

  • Behavioral and attitudinal data together

    The supplier says its models train on observed signals such as transactions and usage data alongside surveys, interviews and experiments that provide information about motives and changing behavior.

    Simile: Building the What-If Machine · Simile: Building confidence in Simile

  • Question-level confidence output

    Simile describes a separate confidence model that estimates likely simulation error, then presents a confidence classification alongside the predicted result.

    Simile: Building confidence in Simile

Data and study setup

Data and settings the company says teams can choose.

  • Observed actions and research context

    Simile says its training combines observed behavior, including transactions and app activity, with survey, interview and experimental signals that describe attitudes, context and changes in behavior.

    Simile: Building the What-If Machine · Simile: Building confidence in Simile

  • Real-world comparison for evaluation

    The supplier describes evaluating a simulation by running the same experiment with real people or observed outcomes and measuring the distance between predicted and observed response distributions.

    Simile: Building confidence in Simile

Reported results

Results reported by the company, with details about how they were tested.

Provider-reported confidence-model evaluation

Simile reports evaluating a question-level confidence model on roughly 8,600 held-out questions with five-fold cross-validation. It describes Total Variation Distance as the error measure for simulated versus observed distributions, and reports metrics for several confidence-model approaches.

This is a provider-published technical evaluation of its confidence signal, not a universal estimate of simulation accuracy. Simile explicitly says a model may be accurate on average while being inaccurate for an individual case.

Simile: Building confidence in Simile

Study limits

  • A confidence label is not a guarantee

    Simile says its confidence score estimates possible error for one question. Its example says the actual error cannot be known until there is a real result to compare with.

    Simile: Building confidence in Simile

  • Counterfactual questions remain difficult

    The supplier notes that questions about new prices, products, policies or other conditions concern outcomes that may not have happened before. Its published framework treats the mechanism behind behavior and the scope of available evidence as material to interpretation.

    Simile: Building the What-If Machine

Sources

  1. Simile: Building the What-If Machine · Provider methodology overview · 2 September 2026
  2. Simile: Building confidence in Simile · Provider-reported evaluation · 25 August 2026

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