Pricing & packaging survey templates

Builds a demand curve by asking purchase likelihood at 4-5 ascending price points for the same product or service. Ideal for pricing teams who already run Van Westendorp but need a sequential-elasticity read. The AI follow-up probes the exact price where intent drops, surfacing the value story behind the number instead of just the drop-off itself.

Measures how a recent menu price increase is shaping visit frequency, item choices, and perceived value at your restaurant, plus how guests feel about service charges, kitchen fees, and other surcharges. Built for restaurant operators and multi-unit brands; the AI follow-up uncovers the real story behind a guest's value rating or changed visit habits, not just an averaged score.

Tests demand for a coffee subscription against current buying habits, cadence preferences, and price acceptance (via Van Westendorp), with an AI follow-up that probes the real reasons behind each respondent's likelihood to subscribe. Built for coffee brands and DTC teams validating a subscription launch or repricing an existing one.

Measures how shelf appeal, unboxing experience, materials, and clarity of a product's packaging shape purchase decisions. Built for brand, packaging, and product teams testing a design or concept, with an AI follow-up interview that reconstructs the exact moment packaging almost won or lost the sale.

Measures how clients perceive a broker's fees or commission — the point where a price feels like a bargain, fair, expensive, or a dealbreaker — and which fee structures and service trade-offs matter most to them. Built for real estate, financial, insurance, or mortgage brokerages, with an AI follow-up that uncovers the real reasoning behind each price threshold.

Tests how a product package performs on the shelf — standout appeal, first-noticed elements, message clarity, and purchase intent — with a best-worst trade-off for design priorities and an AI follow-up that reconstructs the split-second decision to buy or pass.

Maps how a target market perceives a product or service's price using the four classic price-sensitivity questions, then layers in purchase intent, feature value trade-offs, and a budget allocation exercise. An AI follow-up interview digs into the reasoning behind each respondent's expensive/cheap thresholds so pricing teams get the numbers and the 'why' behind them.

Measures which features customers want bundled together, how much value each feature category adds, and what they'd pay if features were sold à la carte — built for product and pricing teams designing tiered packaging. An AI follow-up unpacks the reasoning behind a respondent's top-ranked bundle instead of stopping at the ranking itself.

Tests whether prospects can correctly interpret your plan names, pick the tier that actually fits them, and understand what changes when they upgrade. Built for pricing and product teams evaluating a new plan lineup before launch, with an AI follow-up that digs into exactly which name or feature line caused hesitation or a wrong guess.

Measures how deal-driven your customers really are: what triggers a discount-motivated purchase, whether frequent promotions erode brand perception, and how willing shoppers are to pay full price. An AI follow-up reconstructs the last purchase decision they made under a discount to separate genuine price sensitivity from habit.

Measures how customers react to an upcoming or recent price increase — their acceptance thresholds, likelihood to churn, need to re-justify the value, and preferences for how the change is communicated. An AI follow-up digs into the specific reasoning behind each customer's churn risk score, surfacing what would actually change their mind versus what they say in the closed-ended scales.

A choice-based conjoint that shows respondents realistic product profiles built from attributes and levels — plan tier, price, support, contract terms — and measures which combinations win. AI follow-ups capture the reasoning behind choices that a choice matrix alone can't explain.

Measures consumer price sensitivity using Van Westendorp methodology, feature prioritization, and billing preferences for fintech subscription plans. Designed for product and pricing teams evaluating consumer willingness to pay across global markets.

Measures prospect perceptions of pricing page clarity, perceived value fairness, and decision readiness to identify friction points and conversion barriers on SaaS pricing and packaging pages.

Measures price fairness perceptions, value-for-money judgments, and maximum willingness to pay among recent price-exposed prospects and customers. Ideal for pricing optimization, launch pricing validation, and competitive positioning research.

Measures acceptable price ranges, perceived value, and purchase intent for consumer products using the Van Westendorp Price Sensitivity Meter. Designed for product managers and pricing researchers evaluating new or existing product pricing strategies.

Measures willingness-to-pay thresholds for an everyday consumer product using the Van Westendorp Price Sensitivity Meter with Newton-Miller-Smith purchase intent extensions. Ideal for pricing teams seeking acceptable price ranges and optimal price points.

Measures how users perceive paywall messaging, timing, and pricing fairness. Use with digital content consumers to identify UX friction points and inform subscription conversion strategy.

Measures how online shoppers perceive, interpret, and respond to prices displayed in foreign currencies, evaluating display format clarity, perceived fairness, trust, and behavioral impact to guide global ecommerce pricing UX.

Measures consumer attitudes toward dynamic and surge pricing across rideshare, delivery, travel, and retail, identifying key fairness drivers, transparency preferences, and acceptable price thresholds to inform pricing strategy.