Results you can trust.

We combine state-of-the-art AI with research expertise to deliver world-class insights quickly, confidentially, and cost-effectively.

Schedule a call

85%

Similarity

100+

Validation Tests

30+

Academic Studies

Crowdwave simulated personas are rigorously benchmarked against actual human preferences and responses.

We go a step further by ensuring that results reflect human-like patterns.

Overlap in sentiment between Crowdwave personas and human respondents

Multiple Models = Refined Responses

Crowdwave’s proprietary model pools and filters the knowledge of multiple AIs, including OpenAI, Anthropic, and Meta, a technique that’s proven to deliver greater accuracy.

“Ensemble learning is a machine learning technique that aggregates two or more learners (e.g., neural networks)... to produce more accurate predictions than a single model alone.”

‘What is ensemble learning?,’ IBM (3/18/24)

Enhanced with External Data

To enhance accuracy for specific message tests, Crowdwave integrates a series of up-to-date, verifiable external data, including trusted sources such as the US Census Bureau and the Pew Research Center.

“Retrieval-augmented generation (RAG) is a technique for enhancing the accuracy and reliability of generative AI models with facts fetched from external sources.”

‘What is Retrieval-Augmented Generation, AKA RAG?,’ Nvidia (11/18/24)

A powerful complement to human research

AI Research excels at:

Speed and ability to iterate & learn quickly
Overcoming selection bias & low response rates
Ensuring confidentiality
Being able to ask highly sensitive or edgy questions
Talking to niche audiences, anytime
Insights when human research isn’t feasible (survey fatigue, cost, time)
Ability to probe on responses

Human Research is great at:

Forming an empathic connection with people
Tapping into all of the nuances and expressions of language
Seeing people in their real-world environments (ethnography)
General population surveys
Validating quantitative research

The Power of Personas

Unlike AI tools that generate responses without human context, Crowdwave creates virtual personas who answer survey questions based on their unique “personality.”

Each Crowdwave respondent reflects a holistic profile with: Demographics | Personality Traits | Attitudes

“The LLMs [large language models] can help determine the profile of individuals to interview, generate synthetic respondents, interview them, and even moderate a depth interview.”

‘AI-Assisted Marketing Research,’ Arora et al. (2024)

Crowdwave persona example with audience traits

Supported by Academic Research

A wealth of academic research from Oxford, Wharton, MIT, Stanford, Columbia and Cornell supports the use of advanced models like Crowdwave to generate human-like profiles and understand human attitudes.

In ‘Generative Agent Simulations of 1,000 People’ (11/15/24), Cornell University notes that advanced models can be 85% as accurate as human participants.

University of Oxford noted issue stance support can be increased by 12% with the help of AI in ‘Evaluating the persuasive influence of political microtargeting with large language models’ (6/7/24).