Artificial Intelligence (Data Science) Based Concept Testing

Deploying data science and predictive analytics to identify high market potential concepts (Products, Ad Creatives, Packaging, Messaging, Promotions, Etc.)

A research rigor based testing approach used by Best Buy, Samsung, PepsiCo, Fidelity, P&G, Unilever and other brands.

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AI Concept Testing Webinar (Short Video)

Watch the next generation concept testing framework.

QQS’s concept testing speeds up market acceptance and adoption rates. Each concept is tested for initial reactions, using a mix of traditional quantitative KPIs, along with the Hybrid Qual/Quant technique for insightful diagnostics.

  • A monadic research design is typically used, exposing one participant to one concept, which helps to avoid survey fatigue and bias.
  • In order to rank and compare concept performance, a proprietary quantitative benchmarking system called the Market Readiness Score (MRS) is applied to determine the level of market acceptance.
  • The result: A prioritized list of “Do’s, Don’ts and Risks” that can be confidently acted upon to increase the chance for a quicker market adoption.


    • Are there any unmet needs or market gaps in the category that need to be addressed?
    • Which is the best performing concept and why?
    • What are the concept optimizations and improvement areas to immediately implement?
    • Which words or phrases are resonating or creating negative sentiment?


    • Product or Packaging Concept Testing
    • Description, Design or Visual Testing
    • Market Readiness Concept Testing