Argo Insights

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Argo Insights

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    • Home
    • Who we are
    • What we do
      • About Our Services
      • Data Management
      • Data Visualization
      • Data Modeling
      • Predictive Analytics
      • Machine Learning
      • Noise Auditing
      • Market Research
    • Make it Real
    • Contact
  • Home
  • Who we are
  • What we do
    • About Our Services
    • Data Management
    • Data Visualization
    • Data Modeling
    • Predictive Analytics
    • Machine Learning
    • Noise Auditing
    • Market Research
  • Make it Real
  • Contact

Market Research

ReMiQS - Retrospective Mining from Quant Surveys

Possibly without even realizing it, your recently fielded Quantitative Marker Research tool inadvertently generated even more insights into consumer deliberations, judgements, and choices. ReMiQS is a validated procedure for mining new insights from past data. Relying on a time-tested and vetted set of computations, we can help you get even more from your survey than you realized.

Quant the Qual

Qualitative Market Research provides nuance and richness from hearing unstructured, online reasoning. But, even your Qual data can be Quant-ed, maintaining the strengths of Qual research while still fostering the confidence offered by quantitative analysis. By combining psychometri validity, ethnographic coding, and computational linguistics, our method helps you literally turn your qualitative data into quantitative data and uncover patterns human would undoubtedly miss. And the best part? It can be done both prospectively and retrospectively on interview data you've already collected.

Multi-modal and Longitudinal

See our page on Noise Audit offering. The key to prospective research that is both rich and rigorous is to field a study that measures multiple-facets of the consumer deliberation and choice dynamic, through multiple approaches, and across multiple points in time. Our signature approach cracks open the "Black Box" that houses all the "why" between available market options and observed consumer choices.

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