Mavera – Predict audience response with GANs, not LLM sentiment
Mavera is an audience intelligence API. Give it a message, product prototype, or creative asset and it returns a predicted distribution of emotional and behavioral responses across your target stakeholder population. This is the best way to test your assumptions before you spend or push anything live. To show this in practice, we ran all 101 Super Bowl LX ads through Mavera on game night: https://superbowl.mavera.io. We simulated how audiences would emotionally and behaviorally respond by platform and segment. We returned a distribution rather than a single score as part of a full analysis of each ad in under 4 hours. The model is a GAN adapted for language, emotion, and cognition. A generator produces synthetic audience responses and a discriminator validates them against human benchmarks. Scoring follows a feel-think-act framework: emotional activation, cognitive framing, behavioral prediction. We validated scoring against the Harvard/Illinois OASIS benchmark. MAE on emotional response is 0.02-0.15 versus 1.0-2.5+ for GPT and Claude. Every response includes a confidence score and a hallucination risk score. You can also build-in spread of opinion, response stability, and impact of news/market context scores to your outputs. The API is OpenAI-compatible. Change the base URL to app.mavera.io/api/v1, add a persona_id, and you are running against 50+ pre-built personas or you can customize your own. Sub-100ms latency at P99. Free API key and docs at https://docs.mavera.io/introduction.
- API 平台
- 大型語言模型
- 數據分析
✨ AI 摘要
Mavera is an audience intelligence API that uses GANs to predict emotional and behavioral responses to messages, prototypes, or creative assets. It provides a distribution of predicted responses across target populations, validated against human benchmarks.
適合誰
Marketing teams, Product managers, Creative agencies
為何值得關注
Mavera enables pre-launch testing of assumptions by predicting audience responses with higher accuracy than LLM sentiment analysis.
核心功能
- Predicts audience emotional and behavioral responses using GANs.
- Provides a distribution of predicted responses, not a single score.
- Analyzes messages, prototypes, or creative assets.
- Utilizes a feel-think-act framework for scoring.
使用場景
- A marketing manager can use Mavera to test different ad copy variations for an upcoming campaign, receiving predictions on which emotional responses (e.g., excitement, trust) and behavioral outcomes (e.g., click-through, purchase intent) are most likely across key demographic segments before allocating budget.
- A product development team can input early-stage product mockups or feature descriptions into Mavera to gauge potential user reactions and identify any cognitive framing issues or negative emotional activations that might hinder adoption.
- A PR specialist can simulate audience responses to a press release or crisis communication statement using Mavera, understanding the predicted spread of opinions and the potential impact of current market sentiment on public perception.