We believe that anything can be measured, and that all things should be. We conduct research both in-person and remotely, depending on study objectives.

We skew towards the quantitative side of the research spectrum to provide as objective, meaningful, and data-based insights as possible, regardless of the methods we are using. We take painstaking care to ensure that your objectives and key results (OKRs) are understood and achieved, and that our final product provides direct benefit and return-on-investment.

Here's a glimpse inside our toolbox:

Quantitative, Empirical, and Experimental Methods

  • Surveys (online and mobile)
  • Between-groups testing
  • Repeated measures and within-group testing
  • Single-subject and small-n experimental designs
  • Product benchmarking and evaluation (single product testing)
  • Product comparison (A/B testing)
  • Direct observation and response / behavior coding
  • Preference assessments
  • Conjoint analysis
  • Behavioral-economic and consumer-choice modeling
  • Social-media analytics
  • Sentiment analysis of open-ended text and verbal responses
  • Voice of Customer (VoC)
  • Psychographic consumer segmentation
  • Gamification, motivation, and user break-point testing
  • Card-sorting and click-through testing
  • Performance assessment and knowledge, skill, and ability (KSA) testing
  • Learning-curve and skill-acquisition measurement
  • Psychometrics and psychological testing
  • Scale development and validation
  • Predictive analyses

Qualitative and Subjective Methods

  • Interviews
  • Discussion panels and focus groups
  • Expert opinion
  • Heuristic analysis
  • Product feature / component comparison
  • Ethnography
  • Consumer profiling
  • Consumer-intercept surveys
  • Consumer journaling
  • Consumer-journey mapping and path-to-purchase analysis
  • Consumer-reaction and impression assessment
  • Case study analysis
  • Needs and opportunity assessment
  • Product use and cognitive task analysis
  • Association and memory mapping

All data are processed using appropriate, complementary, and cutting-edge statistical analyses including:

  • Tabulation and descriptive / summary statistics
  • Inferential statistics and hypothesis testing for significant differences
  • Effect-size estimation
  • Categorization and factor analysis
  • Predictive analysis and trend identification (e.g., regression, machine learning)
  • Data visualization and infographics
  • Development of BI dashboards and real-time data trackers