Simulacra Synthetic Data Studio is an AI platform for predictive real-time synthetic data generation and causal scenario modeling. Generate realistic data that replicates and enhances your prior consumer behavioral research studies using the data you already have.

Synthetic data generation & causal belief networks give your team the hindsight, insight, and foresight to update past research with new information and expert knowledge integration. With the Synthetic Data Studio, use Conditional Generation to integrate new knowledge, boost or rebalance specific consumer cohorts & demographics, and parameterize desired behavioral attributes into a new synthetic dataset – allowing you to run what-if scenario models, discover causal relationships, and make new, up-to-date, predictions from prior research in real time.

Consumer research, marketing, product development, supply chain, and cross-functional teams at leading CPG companies use Simulacra SDS for AI enabled decision intelligence and causal scenario modeling in a dynamic global market. Synthetic data from generative AI enables accurate and actionable insights from existing research.

Expand & Update Prior Consumer Research with Conditional Generation

Transform the way you work with your data. Conditional Generation is a new, proprietary technique within synthetic data generation for integrating new knowledge into the generated data. Conditional Generation allows you to expand the range and diversity of the synthesized consumer population by setting parameters to target select cohorts and specific behaviors.

The AI learns the causal relationships amongst all variables within your data to predict beyond the scope of your empirical observations – enabling robust statistical inferences for target populations and scenarios outside those included in the original research.

Together, generative AI and Conditional Generation allow you to draw new inferences and insights from updated predictions, without the time and cost of collecting new consumer data.

Boost Low Incidence & Difficult to Survey Cohorts

Never worry about incidence or sample size again. Use Simulacra to generate new datasets with hundreds or thousands of target consumers from low-incidence or difficult-to-survey cohorts, representing your target consumers.

Simulacra SDS learns from all of your data to predict for each specific sub-population contained within. Using newly enabled Generative AI technology, the synthetic data is guaranteed to maintain the natural variance of each consumer segment, without the bias and loss of predictive power inherent in traditional techniques.

You can immediately discover new insights in even the smallest cohorts at a fraction of the cost and time it takes to commission a new consumer survey.

Predict Winning Strategies with “What-If” Scenario Models

Ever wonder “what if?” With Simulacra’s causal scenario modeling you can find out. Test potential future outcomes of any campaign, decision, or product launch in a safe, real-time data sandbox where you can explore winning strategies for your brand.
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For example, model a sales increase to find out exactly what underlying pricing strategies, consumer preferences, and behaviors are required for that scenario to occur - and translate that scenario into an actionable strategy.

Conditional Generation closes the loop between analysis and action, giving you the tools to implement targeted marketing campaigns, product innovations, and customer experiences that resonate with every target segment of your audience.

Supercharge New & Prior Research

With Simulacra SDS, running simulations on your data is fast, accurate, and insightful. Running simulations is a competitive advantage for understanding consumer behavior in CPG. The Synthetic Data Studio offers you the tools to follow up on hunches, understand why certain consumers respond the way they do, and play with your data in a integrated data sandbox that gives you answers to the questions currently left unanswered.

Use on Prior Research to:

Integrate new knowledge and information for up-to-date data incorporating relevant trends, price changes, and consumer preferences
Increase sample sizes of the entire population or under-surveyed cohorts to reach statistical significance
Simulate new, untested, scenarios to rapidly and accurately model new successful strategies
Turn assumptions and ideas into decisions supported by data

Use on New Research to:

Reduce the number of required participants and the need to over-recruit in new surveys
Generate screened data from non-screened or wide-net research of difficult-to-survey consumers or products with low incidence-rates
Gain deep insights into how various factors influence consumers, enabling data-driven strategies for understanding consumer behavior
Uncover causal relationships within complex consumer behavior networks to predict outcomes

Synthetic Data Generation
for Consumer Research

Supercharge New & Prior Research

Use on Prior Research to:

Use on New Research to:

The White Paper

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Synthetic Data Generation for Consumer Research

Supercharge New & Prior Research

Use on Prior Research to:

Use on New Research to:

The White Paper

Your Data is Secure - Containerized Security and Privacy

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Unlock the power of synthetic data: predict successful strategies

Synthetic Data Generation
for Consumer Research

Unlock the power of synthetic data:
predict successful strategies