Peer-choice
What do you think others would choose?
Captures what respondents think people like them would choose. This can reveal perceived norms, likely winners, and market assumptions that self-report alone may miss.
The patented RAADZ Method · peer-choice at the core
Private preference and market perception, compared with discipline.
RAADZ is a methodology-led research workspace: peer-choice captures perceived market behavior; own-choice comparison shows private preference on the same tasks. Alignment and divergence between the two sharpen concept, message, brand, pricing, and product decisions. That pairing matters most when self-report alone may be filtered by norms, visibility, or privacy concerns.
Ready to try: 14-day free trial, then RAADZ Starter from $99/month in the app. Team or enterprise: book a walkthrough for rollout, outputs, and governance.
Peer-choice as core method for market perception, own-choice as private-preference comparison lens
Peer-choice
“What would people like you (or your target) choose?”
Shows what respondents think people like them would choose. That helps surface perceived norms, likely winners, and market expectations.
Own-choice · private preference
“What would you choose?”
Captures private preference on the same tasks. Alongside peer-choice, it makes alignment and divergence easier to interpret, without turning into a parallel generic scale battery.
Same tasks · same wave · clearer comparison between personal choice and perceived market choice
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Patented, proprietary methodology
The RAADZ Method centers on peer-choice for market perception, not a generic questionnaire layer. Own-choice comparison sits where it adds interpretive value, not as a second unrelated study.
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Research discipline with stakeholder-ready outputs
Auditable structure, alignment and divergence reporting, and synthesis framed around what the evidence supports so teams can stand behind the readout.
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Built for serious decision support
For insights, brand, innovation, product, and strategy teams who need repeatable programs in a real workspace, not one-off feedback exercises.
Why private preference alone is not always enough
Own-choice and self-report are essential, but they can skew when people want to sound reasonable, avoid judgment, protect privacy, or answer in a way that feels socially acceptable.
What teams often see
- Toplines that look strong in self-report but weaken once norms, shelf, or social proof show up.
- Options that sound safe or respectable in self-report but do not reflect true private preference.
- Visible or sensitive topics where social desirability bias, self-presentation, or fear of judgment shape what people say.
- Teams that need to understand both personal choice and what respondents think other people will do.
None of that means own-choice should be ignored. It remains the baseline for private preference. The risk is one lens only when the decision depends on both private preference and market perception.
RAADZ uses peer-choice to capture perceived market behavior, then pairs own-choice comparison on the same tasks where it helps. The result is a clearer read on alignment, divergence, and where follow-up validation may be needed.
Methodology-led, not self-report-only
Why teams use the RAADZ Method instead of generic self-report-only tools
Self-report-only tooling
- One lens: self-reported private preference only
- Self-report can reflect social desirability bias, fear of judgment, privacy concerns, or the urge to give the 'right' answer
- Harder to explain when stated preference and real-world behavior do not line up
RAADZ decision support
- Peer-choice captures market perception: what respondents think people like them would choose
- Own-choice comparison on the same tasks shows alignment and divergence with private preference
- Same methodology-led structure wave to wave, so differences are tracked consistently over time
The RAADZ Method and the comparison that completes the picture
Peer-choice surfaces market perception. Own-choice comparison captures private preference.
Own-choice
What would you choose?
Captures what respondents choose for themselves. Paired on the same tasks, it shows where personal appeal and perceived market behavior match, or pull apart.
Neither signal should be treated as universal truth on its own. In many real-world decisions, the gap between them reveals what self-report alone may miss and gives teams a stronger basis for interpretation and follow-up.
The flagship read
The gap between personal choice and perceived market choice
RAADZ is built around peer-choice, meaning market perception of what people like them would choose. Where it helps, own-choice adds the private-preference baseline on the same tasks. The workspace makes that comparison disciplined and repeatable, because high-stakes decisions are rarely answered by either signal alone.
Alignment
When peer-choice and own-choice agree, you have a cleaner read: private preference and market perception are pointing in the same direction.
Divergence
When peer-choice and own-choice disagree, you get something worth investigating before you commit budget: hidden assumptions, socially filtered self-report, or ideas that look like market winners without feeling personally motivating, or the opposite pattern.
Commercial use
That gap is often where the most useful insight lives: sharper concept tests, clearer message evaluation, and stakeholder conversations grounded in evidence instead of a single flattened score.
How RAADZ works
From study design in the app to decision-ready readouts
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Design from starters or scratch
Open a methodology-led study starter when it fits your job, or configure a custom program. Either way, peer-choice stays primary, with own-choice comparison on aligned tasks when you need private preference alongside market perception.
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Field in one workspace
Run the study with standard quality controls, stimuli, and respondent flow kept in the product. That keeps things operational in one place instead of a scattered toolchain.
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Read alignment and divergence
Review where peer-choice and own-choice agree, and where they split across concepts, messages, segments, or offers. The views are structured for decision support, not vanity metrics.
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Brief stakeholders
Move to launch, messaging, positioning, pricing, or product calls with stakeholder-ready outputs: what the evidence supports, where it is thin, and what to validate next.
Where teams use RAADZ
Buyer decisions tied to methodology-led study starters
The workspace includes RAADZ-native starters for common jobs (concept and packaging, message and claims, pricing, competitive preference, naming, and more), so programs begin from a disciplined peer-choice structure instead of a blank generic questionnaire.
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Concept, offer & packaging
Study starters for concepts, offers, and packaging: see whether market perception and private preference agree before you scale production or shelf.
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Message, creative & claims
Test messages and claims with peer-choice at the center; own-choice comparison shows when a socially easy pick is not the motivating one, or the reverse.
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Pricing & value framing
Separate individual resistance from beliefs about wider adoption so value narrative and price architecture rest on both private preference and perceived market behavior.
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Competitive brand preference
Structured peer-choice on preference and consideration, with own-choice comparison for where the competitive story is about norms versus personal pull.
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Brand trust & relevance
Snapshot how audiences associate the brand privately versus how they believe others see it. That supports positioning, trackers, and recovery narratives.
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Naming screen
Shortlist names with the same disciplined pairing: which options people believe will win in-market versus which they would choose for themselves.
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Feature prioritization
Before roadmap locks, compare what respondents would prioritize personally with what they believe peers would prioritize. Divergence flags where to dig in.
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Perception-sensitive topics
When visibility or stigma may shape self-report, peer-choice on the same tasks adds structured market-perception signal next to private preference.
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Public opinion & policy stance
For issues work: pair personal stance with expectations about broader sentiment when communications or policy decisions depend on both.
Why this matters commercially
Decision support, not chart volume
Sharper concept and message calls
See when an option is personally motivating, broadly expected to win, or both, before you scale creative or media.
Segment-aware divergence
Break the peer vs own comparison by audience so strategy teams know who the signal is really about.
Defensible synthesis
Reporting that states what the evidence supports, where it is thin, and what to validate next, without overclaiming.
A serious research workspace
Structured views built for stakeholder-ready readouts
Start from methodology-led study starters, field in the workspace, then move to stakeholder-ready views: peer-choice and own-choice comparison, alignment and divergence, and reporting structured for decision support rather than a generic survey export.
Study · Concept wave Q2
Key finding
Market perception favors one concept; private preference leans another. That divergence is worth reviewing before launch.
Representative layout
Own-choice
38%
Concept B
Peer-choice
41%
Concept C
Interpretation support: Summarize the gap, note likely drivers, and suggest follow-up tests without overstating what the data proves.
Credible by design
Why RAADZ feels like a serious research product
Built around the RAADZ Method
Peer-choice for market perception, own-choice comparison for private preference on the same tasks. That keeps alignment and divergence visible, auditable, and tied to the business question.
Grounded, not overclaimed
RAADZ is not positioned as magic. It is most useful when direct answers may be shaped by social desirability, false consensus, privacy concerns, self-presentation, or visible category norms.
Designed for real decisions
The product helps teams move from fieldwork to a practical readout they can use in launch, messaging, brand, pricing, and product decisions.
Good fit checklist
Built for teams who need stronger insight quality, not commodity fielding volume
If you already run serious research but want peer-choice standardized, with own-choice comparison where it sharpens interpretation, RAADZ fits how high-stakes programs actually decide.
- Use when private preference and perceived market behavior could diverge, and that gap would change a decision.
- Use when you need a stakeholder-ready story grounded in a differentiated method, not a single topline.
- Use when you want the same peer-choice structure and comparison wave after wave, not a rebuilt spreadsheet each time.
- Use when assistive tools should speed synthesis, not replace an auditable research design.
Pricing
Methodology access in the workspace, not per-question commodity pricing
Self-serve Starter includes the RAADZ Method, study starters, and reporting built around alignment and divergence. Team and enterprise packages add rollout, governance, and shared libraries at scale. Confirm current entitlements in the app; use Pricing for how org buying typically works.
FAQ
Questions teams ask before committing budget
Is peer-choice the same as asking about ‘other people’ in a separate study?
No. RAADZ pairs peer-choice with own-choice comparison on the same tasks when that lens matters. The value is disciplined alignment and divergence, not a second, loosely related questionnaire.
Does RAADZ replace qualitative research?
It complements depth work. Alignment and divergence between peer-choice and own-choice often show where to probe next, not what respondents would say verbatim in a room.
How should we talk about results with executives?
As structured evidence with proportional caveats: what the design supports, where segments split, and what deserves another test before major spend.
Where does AI show up?
As a secondary assistive layer for drafting and organization. The core value is the RAADZ Method, peer-choice design, own-choice comparison where configured, and reporting framed for decision support.
Put the RAADZ Method to work in your next wave
Start a free trial in the app, or book a walkthrough for team rollout, study design, and governance.