Ask Rally is an AI-powered virtual focus group platform that helps you understand how different personas would respond to your product, content, or messaging. We calibrate each AI persona on interviews with a real person until you can't tell them apart, giving you instant feedback on every decision right when you need it.

Ask Rally's AI personas are calibrated on real user interviews until they can trick a superhuman LLM judge in a modified Turing test. Our GenPop™ panel represents the general population with personas trained to match real human responses. While they're not a complete replacement for all research methods, they provide realistic, directional insights that help validate ideas quickly and reduce the risk of costly mistakes.

Ask Rally's polling feature lets you test multiple variations of your content with different audience segments. You can create polls with custom options and get quantitative feedback on which versions resonate best with each persona group.

Yes! You can create detailed custom personas based on demographics, interests, behaviors, and other characteristics. For the most accurate results, we recommend using our GenPop™ panel, which has been calibrated on real interviews to ensure realistic responses that mirror actual human behavior.

Traditional focus groups are still essential, but you can't run a focus group for everything. Ask Rally provides instant feedback when you need a second opinion, helping you reduce the risk of missing opportunities or suffering avoidable failures. It's best used for early validation and rapid iteration, complementing deeper research methods for critical decisions.

Yes, Ask Rally supports multilingual capabilities, allowing you to ask questions in various languages. LLM providers like OpenAI have global customers and work extensively to regionalize their models. They train models using data from diverse cultures, enabling AI to role-play authentically in different languages and cultural contexts. For example, AI can role-play as an English pirate with phrases like "Arrr... look what the tide dragged in..." or as Don Benito with "Buenas tardes, señores. ¿Les puedo ofrecer la muerte?"

While ChatGPT is designed to be a helpful assistant, it isn't optimized for role-playing multiple customers simultaneously to generate realistic feedback. Major providers aim to remove bias, which can flatten disagreements and overestimate consensus. Rally views bias as a feature and helps you use AI to understand human behavior more realistically. We calibrate our personas on real interviews until they can trick a superhuman LLM judge, ensuring responses that reflect genuine human diversity. We support multiple models and offer features to design, extend, and run virtual focus groups efficiently.

Ask Rally uses a rigorous calibration process where we train each AI persona on interviews with real people until the persona can trick a superhuman LLM judge in a modified Turing test. Our GenPop™ panel has been specifically calibrated to match real-world responses, ensuring that the feedback you receive reflects genuine human perspectives. We continuously refine our approach based on comparisons with real-world research results.

We've invested heavily in calibration techniques that create authentic response diversity. Our GenPop™ panel is trained on real interviews until each persona can pass a modified Turing test against a superhuman LLM judge. Rally uses different base models, persona-specific prompting, and calibration strategies to produce responses that genuinely reflect human diversity. When personas are properly calibrated on real data, they produce natural, varied responses that mirror actual human behavior.

All research methods, including traditional ones, deal with bias. We address this through our calibration process, training personas on real interviews until they accurately reflect actual human responses. Our GenPop™ panel has been specifically calibrated to represent diverse demographics authentically. We're transparent about limitations and recommend using virtual focus groups alongside other methods for the most complete picture.

Scientific literature shows demographics are highly predictive at the crowd level, making them our primary focus for calibration. Our GenPop™ panel is built on demographic personas trained against real interviews. While we find jobs-to-be-done frameworks valuable for one-on-one interviews and continue testing their impact on persona realism, demographics remain most reliable for large-scale insights. We can support jobs-to-be-done approaches as custom projects for clients who prefer that methodology, or you can design your virtual focus group prompts for it.

Our personas are calibrated on interviews with real people who have those lived experiences. Through this training process, the AI learns to reflect authentic perspectives based on actual human narratives. While they don't have personal experiences, our calibrated personas can simulate perspectives that have been validated against real responses. For research requiring deep lived experience, we recommend supplementing virtual focus group responses with traditional methods.

Our calibration process specifically addresses this by training personas on real interviews that capture emotional, contradictory, and impulsive responses. Our GenPop™ panel has been calibrated until personas can trick a superhuman LLM judge, which means they've learned to reflect the messiness of human thinking, including emotional contexts, cognitive biases, and irrational decision patterns. While we continue to refine this, our calibrated personas demonstrate significantly more realistic human behavior than uncalibrated AI.

Discrepancies between virtual focus group and real-world results provide valuable learning opportunities. We encourage clients to share these instances with us, as they help us improve our calibration process. Our GenPop™ panel has been specifically trained to minimize these discrepancies through rigorous testing against real interviews. Remember that virtual focus groups are best used for directional insights and early validation to reduce risk, not as a complete replacement for all real-world testing. The greatest value often comes from combining both approaches.

Ask Rally's interface is designed so that each AI gets the prompt individually, along with lengthy instructions for how to play the role of the persona they have been assigned. Our personas are already calibrated on real interviews to behave authentically, so giving additional instructions can actually throw off the results and isn't recommended. Our support team is also available to help optimize your prompting techniques for best results.

Ask Rally approaches this with careful ethical consideration. Our GenPop™ panel is built on interviews conducted with informed consent, where participants understand their responses will be used to train AI personas. We don't recommend creating exact replicas of specific individuals without consent, unless the information is publicly available. When using the persona cloning feature, we recommend obtaining permission and using it responsibly. Our system extracts patterns but can also capture personal details, so should be used with caution. We're committed to developing ethical guidelines as this technology evolves.

Virtual focus groups can absolutely surface unexpected insights! Our calibrated personas, trained on real interviews, can identify patterns and contradictions that might be missed. When properly designed, multi-perspective AI panels reveal surprising perspectives that reflect genuine human diversity. While the boldest insights often come from combining virtual and traditional methods, we have numerous case studies where clients discovered valuable insights using Rally alone, reducing the risk of missing opportunities.

Uncalibrated AI models do tend toward agreeableness, but our GenPop™ panel has been specifically trained to overcome this. We calibrate personas on real interviews that include disagreement, criticism, and skepticism until they can trick a superhuman LLM judge. Our multi-agent approach naturally surfaces differences of opinion, and our personas are designed with varying personality traits including skepticism, pragmatism, and contrarianism based on real human data. This creates a balanced and realistic range of responses.

Our calibration process specifically addresses this by training personas on real interviews until they can pass a modified Turing test. Our GenPop™ panel demonstrates depth and variability that reflects actual human unpredictability. We maximize response diversity through varied persona designs based on real data, randomized parameters, and multi-model approaches. For research requiring extreme depth or unpredictability, we recommend using Ask Rally for initial insights to reduce risk, and following up with targeted human research for critical decisions.

All research methods, including traditional ones, can be influenced by labeling and presentation order. We mitigate this through randomization techniques, balanced question design, and using multiple prompt variants. Our calibration process helps ensure personas respond more like real humans would, including being influenced by presentation in realistic ways. We also provide guidance on constructing unbiased questions and interpreting results appropriately through our support team.

Uncalibrated LLMs can reflect training data biases, but our GenPop™ panel has been calibrated on interviews with real people across the ideological spectrum and educational backgrounds. Our calibration process ensures personas authentically represent diverse political views, education levels, and cultural contexts based on real human responses. This creates a more balanced representation of perspectives than a single LLM would provide.

Our calibration process trains personas on real interviews, which naturally constrains their knowledge to what real people in those demographics would know. Our GenPop™ panel includes knowledge constraints based on demographics, education, profession, and interests, validated through our modified Turing test. While not perfect, our calibrated approach significantly reduces instances of implausible knowledge. We continue refining these constraints based on user feedback and encourage researchers to interpret responses with appropriate context.

Economic behavior modeling is challenging for all research methods. Our GenPop™ panel has been calibrated on real interviews that include pricing discussions, helping ensure more realistic economic responses. Our approach includes specific techniques to improve economic plausibility, including anchoring to real-world pricing data and incorporating consumer psychology principles validated through our calibration process. For critical pricing decisions, we recommend using Ask Rally for directional insights to reduce risk, and validating with traditional methods that have established track records for pricing optimization.

Ask Rally can't directly simulate sensory experiences, but our calibrated personas can model how real people respond to descriptions of sensory experiences based on training from actual interviews. For products heavily dependent on sensory appeal, Ask Rally works best for concept testing, messaging optimization, and understanding the decision criteria people might use, rather than predicting specific sensory preferences. This helps reduce the risk of missing key insights early in development.

This is a valid concern that applies to all forms of market research, not just virtual focus groups. Our GenPop™ panel is calibrated on real interviews, which means it reflects both the strengths and limitations of interview-based research. We address the gap between stated and revealed preferences by testing our models and prompts based on behavioral data where available, not just survey responses. Our system can incorporate real-world behavioral patterns and purchase data to ground responses in actual behavior. For maximum accuracy, we recommend using Ask Rally for instant feedback to reduce risk, and validating key findings with behavioral testing methods like A/B tests or sales data analysis.