Make a good product or service great.
Make a great one excellent

Traditional research tells you customers want better quality, more features, and lower prices. That is not a brief. The right study tells you which features win, which ones are wasted spend, and exactly what Canadian customers will pay.
Mockup image
Device frame

"Customers want everything" is not a product strategy.

Knowing what customers say they want is not the same as knowing what they will actually choose -- or what they will actually pay.

Everything is important
Feature icon

Ask customers to rate product features and they rate them all as important. Ask what they are willing to pay and they say less than they actually spend. The result is a ranked list where everything ties for first. That is not a product strategy. That is noise.

Research without tradeoffs
Feature icon

Traditional surveys capture what customers say they prefer right now. They cannot tell you what shifts when the price goes up, how one segment responds when a feature gets cut, or where purchase intent actually breaks down before the launch is committed.

Launches made blind
Feature icon

Pricing decisions, feature investments, and configuration choices all get made on survey data that cannot answer the question that actually matters: if this product launches as designed, what should we expect Canadian customers to choose?

The wrong question
Feature icon

Conventional research asks customers what they want. The more important question is what they will actually choose when forced to pick between real options at real price points. Those are not the same question -- and confusing them is where product launches underperform

Know which features win before building them

A decision model, not a preference ranking. Change this feature, expect this shift. Price it this way, capture this segment.

Nobel Prize-winning decision science models how Canadian customers actually make product decisions -- not what they say they want, but what they choose when forced to pick between realistic options at real price points.

The output is prescriptive. Add this feature and here is how purchase intent moves. Price it here and here is which segment you capture. Bundle it this way and margins improve without losing volume.

A major airline learned the hard way what happens when this question goes unanswered. They reduced seat pitch expecting modest pushback. The reaction was severe. The real question -- how much will passengers tolerate before switching -- was never properly tested before the decision was made. That is an expensive way to do research.

This is not a customer satisfaction report. It is a product decision engine.
Mockup image
Device frame

Nobel Prize-winning science. Better products. Stronger margins

The credentials behind the work -- not academic theory, applied decision science with a track record across product design, pricing strategy, and market research for companies operating in Canada and globally.

  • PROVEN SCIENCE

    • Nobel Prize-winning decision science
    • Forces real purchase tradeoffs, not wish lists
    • Predictive, not just descriptive

  • DEEP EXPERIENCE

    • 30+ years across the US and Canada
    • Touched most major industry verticals
    • Author of Measuring "Customer Satisfaction"

  • REAL RESULTS

    • Applied across product design, pricing, and packaging
    • Identified winning configurations before launch
    • Prescriptive commercial recommendations, not preference rankings

No budget for a full study?
There is still an answer

Syntellia uses AI to generate insights from Canadian consumer profiles in days -- a faster, leaner alternative when the launch timeline or budget does not allow for full fieldwork.

Fresh thinking on hard decisions

No fluff. 

Just useful thinking on the decisions that matter.

  • Contact us

Submission Successful

The form has been successfully submitted.