Subconscious AI

Subconscious AI Features

• Synthetic Respondents: Generate realistic consumer profiles using data from 800 million real respondents.
• User Journey Simulation: Quickly simulate full user journeys and identify key transition drivers.
• Causal Modeling: Execute causal surveys and experiments to predict market impacts.
• Data Augmentation: Enhance datasets with synthetic consumers for richer market insights.
• Human Validation: Integrate human validation into the research process for high accuracy.
• Scalable Insights: Utilize AI to conduct research at a big-data scale efficiently.
• Cost-Efficient: Achieve high accuracy (99%) at a fraction of traditional research costs (10%).

Subconscious AI Pricing

Use Cases

• Product Management: Assess the value of product features and recognize consumer preferences.
• Marketing: Group audiences based on needs rather than demographics and create impactful messages.
• Policy Making: Model policy outcomes and evaluate the effects of different policy actions.
• Healthcare: Enhance patient care and operational efficiency in healthcare environments.
• Sales: Distinguish between crucial and non-crucial product features to boost sales.
• Content Creation: Customize content to suit audience preferences for increased engagement rates.

Pros:

• ✅ High accuracy and reliability in data insights.
• ✅ Ethical and efficient research methodologies.
• ✅ Fast and scalable simulation capabilities.
• ✅ Flexible pricing to suit different business sizes.

Cons:

• ❌ May require a learning curve for users new to synthetic respondents.
• ❌ Dependent on the quality of input data for optimal results.
• ❌ Advanced features might be cost-prohibitive for very small businesses.