infer vs Branded: Which is better?

Game-changing AI powered data analytics in an easy to deploy and use platform. Traditionally, there have been huge barriers to deploying AI within an organisation, here at infer we believe that AI should be for the many and not just the few. We are driven by a purpose to make AI accessible to all! So, we built infer to enable more organisations to benefit from the power of machine learning enabled data analysis. How did we do this? Well through an AI deployment model of Explore, Predict, Act and Measure and a product that does not require advanced coding skill, we believe that any organisation can now leverage AI to gain deep and predictive insights into their most important metrics. This technology is truly game changing and we’re passionate about empowering more organisations to benefit from it.

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Branded

Branded Research, now part of Dynata, specializes in providing high-quality consumer insights through a vast audience network of over 2 million participants. The platform utilizes advanced AI technology to ensure data integrity and quality, enabling clients to conduct targeted research across diverse consumer segments. With automated API access, Branded Research facilitates real-time connections to niche audiences, enhancing the effectiveness of both qualitative and quantitative research methodologies.

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Key features

inferNo data

Branded

AI-Driven Quality Assurance: Utilizes artificial intelligence to verify participant responses, ensuring data integrity with over 95% accuracy in identifying poor actors.
Intelligent Audience Sampling: Offers access to a diverse audience of over 2 million members, allowing for precise targeting across 100+ consumer segments and industries.
Automated API Access: Provides programmatic API solutions for real-time connection to custom audiences, capturing emotions, motivations, and values for comprehensive insights.
Multi-Method Research Capabilities: Supports a wide range of qualitative and quantitative research methods, including webcam studies, emotional AI, and surveys.
Commitment to User Experience: Focuses on creating a comfortable environment for participants, enhancing the quality of insights through open and authentic responses.

Useful for

infer

infer vs Branded: Which is better?

Key features

inferNo data

Branded

AI-Driven Quality Assurance: Utilizes artificial intelligence to verify participant responses, ensuring data integrity with over 95% accuracy in identifying poor actors.
Intelligent Audience Sampling: Offers access to a diverse audience of over 2 million members, allowing for precise targeting across 100+ consumer segments and industries.
Automated API Access: Provides programmatic API solutions for real-time connection to custom audiences, capturing emotions, motivations, and values for comprehensive insights.
Multi-Method Research Capabilities: Supports a wide range of qualitative and quantitative research methods, including webcam studies, emotional AI, and surveys.
Commitment to User Experience: Focuses on creating a comfortable environment for participants, enhancing the quality of insights through open and authentic responses.

Useful for

infer

Branded

Provides access to a diverse audience of over 2 million members, enabling targeted research across various consumer segments and industries.
Utilizes AI to ensure high-quality insights by verifying participant responses and removing poor actors with over 95% accuracy.
Offers automated API access for real-time connections to custom audiences, facilitating efficient data collection and analysis.
Supports a wide range of qualitative and quantitative research methodologies, enhancing the depth and quality of insights gathered.
Prioritizes user experience, leading to more authentic responses and higher engagement from participants in research studies.

Use cases

inferNo data

Branded

Conducting qualitative and quantitative research using various methodologies, including webcam studies and emotional AI.
Accessing niche target audiences through advanced algorithms for efficient participant recruitment across diverse segments.
Utilizing AI to ensure data quality by vetting participant responses and removing poor actors with high accuracy.
Offering automated API access for real-time connections to custom audiences, capturing emotions and motivations for comprehensive insights.
Supporting product development and concept testing by providing insights into consumer needs, motivations, and purchase drivers.