Category, consumer, and competitive evidence identified the opportunity.
Independent integrated case study · Product marketing × analytics
Dairy Queen: a premium line-extension decision.
A franchise-aware recommendation for a Dairy-Free Blizzard: translate preference data and category economics into a price, pilot design, and launch decision that can actually be tested.
$1.25Bmarket opportunity
12–15%category CAGR
~44%plant-based willingness-to-pay premium
Context & role
Context: Dairy Queen could address an expanding dairy-free opportunity, but a viable offer needed to work for customers, the brand, and franchisees. My role: Independent product marketer and analyst responsible for market assessment, conjoint analysis, pricing logic, GTM recommendation, and pilot measurement.
The product question
Should Dairy Queen launch a dairy-free Blizzard, and how should it price and validate the offer without treating the cheapest modeled option as the final answer?
One system: preference to pilot
The project integrated analysis with product marketing judgment. Quantitative outputs set the boundaries; customer value, unit economics, and franchise operations determined the recommendation.
Preference analysis tested attributes, trade-offs, and price sensitivity.
Decision views made pricing, target, and test assumptions transparent.
Positioning, premium price, and franchise rollout defined a measurable test.
Analytical readout
Do not optimize for the lowest price.
- Used conjoint analysis, perceptual mapping, and value-curve modeling to evaluate the proposition.
- Applied SQL and Python workflows to organize preference and pricing scenarios.
- Pressure-tested the low-price model output against willingness to pay, oat-milk costs, and franchise economics.
Marketing translation
Premium, but operationally credible
Shaped a premium line-extension story around a clear consumer benefit, then designed a bounded pilot that protects franchisee economics while generating the evidence needed for a scale decision.
Recommendation & outcome
Launch a premium Dairy-Free Blizzard through a six-month pilot across approximately 30 franchises. The decision was not to follow the lowest conjoint price blindly: the evidence supported a premium position once consumer willingness to pay, costs, and franchise constraints were assessed together.
Product decision
Offer a premium line extension.
Keep the product value and price aligned with the differentiated dairy-free occasion.
Validation decision
Prove it in a controlled pilot.
Use a 30-franchise rollout to validate consumer and franchise outcomes before scale.
What I would measure next
Use the pilot to validate 8% attach rate and 30% repeat rate thresholds, alongside incremental ticket value, franchisee margin, operational complexity, customer satisfaction, and repeat purchase by location. A good launch decision needs both demand proof and operational proof.
SQLPythonTableauConjoint analysisPricing strategyMarket assessmentGTM strategyPilot design