Conjoint Bundle Trade-off Survey Template
Test feature, brand, service, and price combinations to identify preferred packages.
12
questions
~8
minutes
312
demo uses
Create a draft from the backend template key, then edit questions, logic, targeting, and reporting in your workspace.
Best for
B2B buyers, admins, and budget owners comparing package architecture.
Decision output
Identify the package bundle most likely to maximize conversion, expansion, and pricing confidence.
Method
Choice-based conjoint with price, support, security, and integration attributes.
Decision blueprint
Which realistic package trade-offs should guide the next tier design?
Adapt this plan to your audience before creating a draft. Review the study design and readiness requirements before launch.
Prepare before drafting
- Use feasible attribute levels and flag prohibited or implausible combinations.
- Agree the competitive context, price unit, and scenarios before fielding.
- Use this template when the real decision is package architecture rather than a simple price point.
- Pair with segmentation cuts by company size and current stack complexity.
Question approach
Present repeated choices between balanced product bundles. Pilot comprehension, task burden, and the meaning of the no-choice option before launch.
Sample and comparison plan
Have a methodologist size the base against attributes, levels, task count, planned segments, and the intended estimator. If design coverage or segment bases are inadequate, simplify the design before recruitment.
Analysis sequence
- Check design coverage, response quality, and qualified bases.
- Review utilities and attribute importance with estimator assumptions.
- Compare feasible scenarios and sensitivity to price and competitor assumptions.
Decision handoff
A package recommendation with trade-offs, scenario assumptions, segment bases, and unresolved design risks.
Limits and risks
- Preference simulation is not a sales forecast.
- Utilities depend on the tested levels and choice context; unsupported extrapolation is unsafe.
Example availability: beta. Illustrative synthetic evidence; live certification remains outstanding.
Preference simulation is not a sales forecast.
Evidence gap: Local authenticated synthetic decision views are captured. Production deployment, customer outcomes, claim substantiation, and method-specific live certification remain unverified.
Suggested Expert Roles
Conjoint methodologist
Conjoint, pricing, segmentation
Browse matching experts
Pricing specialist
WTP, packaging, revenue strategy
Browse matching experts
Brand insights lead
Concept, claims, creative testing
Browse matching experts
Review the sample and comparison plan above.Pair this template with expert review when the study affects pricing, investment, launch, or regulated workflow decisions.
Build an expert invite panel from this templatePreview Sections
Qualification
Confirm category relevance and purchase responsibility.
Choice tasks
Balanced package alternatives with price and service trade-offs.
Why they chose
Preference rationale and switch triggers.
Question Preview
1. Choose the package you would be most likely to buy.
2. What was the main reason for your choice?
3. Which feature would make you switch packages?
Conjoint Output Preview
Choose the package architecture that maximizes expansion without slowing sales velocity.
5
attributes
9
tasks/respondent
224
seeded respondents
57%
holdout hit rate
Monthly price
27.8%
importance estimate
Integrations
24.1%
importance estimate
Security
22.8%
importance estimate
Template FAQ
Who is the Conjoint Bundle Trade-off template for?
It is designed for b2b buyers, admins, and budget owners comparing package architecture. and teams that need Identify the package bundle most likely to maximize conversion, expansion, and pricing confidence..
How many questions are included?
Conjoint Bundle Trade-off includes 12 questions across 3 sections and takes about 8 minutes to complete.
Can I customize this template?
Yes. Use the create-draft flow to copy the template into the builder, then adjust wording, targeting, logic, branding, and analytics settings before launch.