Methodologies

Quantitative Methods

Choice modeling or conjoint analysis

  • Maximum Difference Scaling (Max-Diff)
  • Adaptive Choice-Based Conjoint (ACBC)
  • Discrete choice modeling (CBC)
  • Full profile conjoint (CVA)
  • Simulations based on Hierarchical Bayes/HB Modeling (individual utilities from sparse data)
  • User-friendly Excel-based simulators
  • Innovative work to model the effect of brand exogenously to the conjoint design, in order to reduce the confounding of brand effects with other attributes

Segmentation

  • Latent Class Analysis (LCA)
  • Segment profiling
  • Decision tree-based methods (e.g.,┬áCHAID) to identify actions most likely to increase share by segment
  • User-friendly Excel-based segment scoring tools

Predictive modeling

  • Regression analysis (linear and logistic)
  • Multiple discriminant analysis (MDA)
  • Path analysis
  • Structural Equation Modeling (SEM)

Perceptual mapping

  • Factor analysis to identify constructs underlying brand attributes
  • Perceptual mapping of brands among those who prefer a brand and those who do not
  • Correspondence analysis

Tracking methodologies

  • Track metrics over time to watch trends in data
  • Identify statistically significant differences in order to make rigorous statements about what has changed
  • Use effect sizing when statistical significance is not appropriate

Target Audience

We have relationships with vetted global quantitative partners when local language quantitative data collection is desired, and have conducted numerous studies with the following audiences:

  • Enterprise IT decision-makers and implementers (all levels from CTO to the help desk)
  • Business leaders and decision-makers (Enterprise through small business entrepreneurs)
  • Business analysts, data scientists, and information workers (i.e., users of technology)
  • Developers and architects
  • Consumers (including technologically advanced households)
Qualitative Methods

We have relationships with vetted global qualitative partners when local language qualitative data collection is desired, and have conducted numerous studies with the following audiences:

  • Enterprise IT decision-makers and implementers (all levels from CTO to the help desk)
  • Business leaders and decision-makers (Enterprise through small business entrepreneurs)
  • Business analysts, data scientists, and information workers (i.e., users of technology)
  • Developers and architects
  • Consumers (including technologically advanced households)

Global group-based research (specialized in English speaking groups globally)

  • Focus groups
  • Mini groups
  • Triads
  • Diads
  • Online discussion boards and focus groups

In-Depth interviews

  • Face-to-Face
  • Online
  • Telephone