SServices

Advanced Research Methods for Complex Business Questions.

Not every research question can be answered with a standard survey. I combine rigorous quantitative methodologies with practical business understanding to uncover preferences, explain customer behavior, and support confident decisions.

01Conjoint Analysis

Understand the Trade-offs That Drive Customer Choice.

Design and execute conjoint studies to understand how customers value product features, service attributes, brands, and prices.

Capabilities

  • Choice-Based Conjoint (CBC)
  • Attribute and level development
  • Experimental design
  • Utility estimation
  • Preference and choice simulations
  • Product and service configuration
  • Market scenario modeling
  • Volumetric and SKU optimization
  • Menu-Based Choice approaches where appropriate

Typical business questions

  • — Which product features really drive customer choice?
  • — What is the optimal combination of features and price?
  • — How would different product configurations perform?
  • — Which trade-offs are customers willing to make?
02Preference Measurement

Identify What Really Matters.

Apply MaxDiff and other advanced preference measurement techniques to produce differentiated rankings and quantify relative importance.

Capabilities

  • Best-Worst Scaling / MaxDiff
  • Experimental design
  • Individual-level preference estimation
  • Relative importance measurement
  • Preference-based segmentation
  • Advanced Kano approaches
  • Paired comparisons
  • Priority mapping

Typical business questions

  • — Which product features should be prioritized?
  • — Which customer needs matter most?
  • — How can we establish meaningful priorities across many alternatives?
  • — Where do different customer segments disagree?
03Pricing Research

Find the Right Price, Not Just an Acceptable One.

Rigorous pricing research that balances conversion, revenue, and perceived value.

Capabilities

  • Gabor-Granger pricing research
  • Price sensitivity measurement
  • Conjoint-based pricing
  • Willingness-to-pay analysis
  • Demand and revenue simulations
  • Price-feature trade-off analysis
  • Price architecture research

Typical business questions

  • — What are customers willing to pay?
  • — How does demand change at different price points?
  • — Which pricing strategy offers the best balance between conversion and revenue?
  • — How much value do customers assign to specific features?
04Customer Segmentation

Discover Meaningful Differences Between Customers.

Identify strategically relevant segments based on needs, attitudes, and preferences.

Capabilities

  • Needs-based segmentation
  • Behavioral and attitudinal segmentation
  • Cluster analysis
  • K-means clustering
  • Segment profiling
  • Discriminant analysis and segment assignment
  • Quantitative persona development
  • Preference-based segments

Typical business questions

  • — Which distinct customer groups exist?
  • — How do their needs, attitudes, and preferences differ?
  • — Which segments offer the greatest strategic opportunities?
  • — How can segments be translated into product and marketing decisions?
05Drivers Analysis

Understand What Really Drives Customer Experience.

Separate frequent issues from genuinely influential ones, and direct improvement resources where they matter.

Capabilities

  • Customer satisfaction driver analysis
  • Regression-based modeling
  • Correlation and multivariate analysis
  • NPS, CSAT, and CES analytics
  • Voice-of-Customer research
  • Quantification of open-ended feedback
  • Prioritization of improvement opportunities
  • Advanced modeling of customer outcomes

Typical business questions

  • — Which experience factors have the greatest impact on satisfaction?
  • — Where should improvement resources be invested?
  • — Which issues are frequent, and which are genuinely influential?
  • — How can unstructured customer feedback be turned into measurable priorities?
06Quantitative UX Research

Make Better Product Decisions With Better Evidence.

Quantitative research for digital products and services — from concept evaluation to benchmarking.

Capabilities

  • Quantitative usability studies
  • UX surveys
  • Concept and prototype evaluation
  • Feature prioritization
  • Product experience measurement
  • User needs research
  • UX benchmarking
  • UEQ / UEQ+ and standardized UX metrics where appropriate
  • Mixed-method research designs
  • Research for digital products and services

Typical business questions

  • — Which product concepts are most promising?
  • — What should be built next?
  • — How do users evaluate the product experience?
  • — Which improvements have the greatest potential?
07AI-Augmented Research

Combining Human Evidence With AI-Powered Analysis.

Explore how artificial intelligence can support advanced research workflows, accelerate analysis, and create new possibilities for predictive insights — while keeping real respondent data and methodological rigor at the center.

Capabilities

  • AI-assisted coding of open-ended survey responses
  • Structured qualitative-to-quantitative analysis
  • AI-supported research workflows
  • Automation of selected research and reporting processes
  • Human-grounded digital twins and synthetic respondent experimentation
  • AI-assisted contextual enrichment of quantitative models
  • Research-based predictive modeling
  • Model validation and predictive performance measurement

Typical business questions

  • — How can real preference data inform probabilistic predictions?
  • — Where can AI accelerate analysis without sacrificing rigor?
  • — How can open-ended feedback be structured at scale?
  • — How do predictive models perform out-of-sample?

AI is not a substitute for real customer evidence.

It is an additional analytical capability that can enhance research efficiency, scalability, and predictive potential. Experimental approaches are presented as exploratory, not as established or universally validated solutions.

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