Build menus customers
actually want.
A research platform purpose-built for hospitality. Validate new concepts, optimise the menu mix, and price every item for value — using the methodology global brands rely on.
Built with real research methodology. Tested on real menu data.
Most menu decisions are made with the wrong data.
Sales data tells you what they bought.
It doesn't tell you what they wanted, what they wished was on the menu, or what they nearly ordered. Hospitality marketing teams make decisions worth millions on incomplete data.
Agency research is slow and expensive.
A typical concept test from BASES or Quantilope takes six to eight weeks and costs £15,000–£30,000. Marketing teams need to move faster than that — especially for seasonal menus and limited-time offers.
Generic survey tools miss the methodology.
SurveyMonkey can collect responses. It can't run TURF analysis, Van Westendorp pricing, or BASES five-pillar concept testing. The methodology is the whole point.
Methodology that holds up. Decisions you can defend.
Pare brings together the research methodologies enterprise teams rely on — sequential monadic concept testing, TURF analysis, Van Westendorp pricing — into a single platform built specifically for hospitality menu decisions. The methodology is industry standard. The application is purpose-built.
Concept Testing
BASES five-pillar
Test new ideas on purchase intent, appeal, uniqueness, brand fit, and believability. Sequential monadic methodology with randomised order.
TURF Analysis
Reach optimisation
Find the smallest menu combination that reaches the most customers. Greedy plus exhaustive solvers verify optimality.
Price Sensitivity
Van Westendorp PSM
Discover what customers will actually pay. Identify overpriced and underpriced items with verdicts board-ready.
Ingredient Diagnostics
Highlighter testing
See which words in the description drive appeal and which hold it back. Diagnostic depth most platforms don't offer.
Concept-to-Menu Flow
Connected workflow
Validated concepts promote directly into menu testing. One platform, one decision pipeline, defensible at every stage.
Every question a menu director asks. Answered.
Concept Screener
Before a single chef hour is committed.
Will customers actually buy this?
Purchase Intent T2B benchmarked against 50% — the floor every concept must clear to be commercially viable.
Is it strong enough to launch on its own, or does it need marketing support?
Concept Strength Index across six attributes signals launch heroes vs concepts needing a campaign.
Is this a real differentiator, or a "me-too"?
The Uniqueness × Intent matrix surfaces breakthroughs, niche plays, and incremental safe bets — each with different go-to-market needs.
Does this feel like our brand?
Brand Fit risk panel automatically flags appealing concepts that don't feel on-brand — catch positioning errors before launch.
Will customers understand it?
Comprehension verbatims plus clarity indicator. If respondents can't describe it back, the description has failed.
What specifically is driving love or loathe?
Ingredient Reactions heatmap shows sentiment per word — actionable copy revisions in one screen.
Would it cannibalise existing menu items?
Cannibalisation signal tells you whether this adds revenue or shuffles it — critical for P&L modelling.
Menu Optimiser
Once a menu is live, or when it's being refreshed.
Which items should stay, go, or get repositioned?
TURF analysis identifies the smallest menu that reaches the most customers — drop the redundancies, keep what counts.
Which items pull hardest, not just sell most?
Intent strength distinguishes core items from "default" choices — the items ordered when nothing else appeals.
What should each item cost?
Van Westendorp price sensitivity identifies overpriced and underpriced items with verdicts you can take to a board meeting.
Does the menu work for every segment?
Reach breakdowns by diet, dining party, and visit frequency confirm the optimal menu works across audiences — or surfaces who's being underserved.
Where's the menu reach plateau?
The reach curve shows where adding more items stops adding more customers. Cut everything beyond the elbow.
Which items appear together in real customer orders?
Co-occurrence analysis from intent and TURF responses identifies natural menu pairings and category structure.
From data to decision in under a week.
Pare turns weeks of agency time into days of clarity. Here's what a real cycle looks like.
- 01 · Monday
Set up
Concepts or menu items added to a study. Pre-populated defaults mean a marketing manager can launch in 10 minutes.
- 02 · Tue – Wed
Field
Survey deployed to the brand's customer database. Real responses from real customers. Aim for 200–400 completes.
- 03 · Thursday
Analyse
Full diagnostic dashboard available the moment data hits target. Charts, segment cuts, methodology indices, exportable to PowerPoint, Word, Excel.
- 04 · Friday
Decide
Winners promoted from concept screener to menu optimiser. Losers killed. Refinements briefed in. Board pack ready.
"We tested five concepts with 250 customers last week. Two are launch-ready. Two need repositioning. One we're killing. All five would have made the menu under our old gut-feel process."
Built on methodology global brands trust.
Every analysis in Pare is built to the same standard agencies and enterprise platforms use. The difference is access, speed, and specificity to hospitality.
| Pare uses | Also used by |
|---|---|
| Sequential monadic concept testing | BASES, Nielsen, Quantilope |
| BASES five-pillar attribute battery | Ipsos, GfK, McKinsey |
| TURF analysis (greedy & exhaustive solvers) | Sawtooth, Displayr |
| Van Westendorp Price Sensitivity Meter | Quirks, Conjointly |
| Highlighter testing for ingredient diagnostics | Quantilope, Ipsos |
| Top-2-Box reporting and segment cuts | Industry standard |
All methodologies implemented to industry-standard specifications. Full methodology documentation available on the How It Works page.
Built for menus. Not retrofitted from FMCG.
Generic survey tools don't understand menu structure, cannibalisation dynamics, or how a customer thinks about a dining decision. Enterprise research firms are built for FMCG launches that take a year and cost hundreds of thousands.
Pare is built for the decisions hospitality marketing teams make every week.
- Spring/summer menu refreshes
- Limited-time offers and seasonal launches
- Range extensions and new categories
- Price changes in response to cost pressure
- Concept generation for innovation pipelines
- Brand extensions and white space
- Children's menu refreshes
- Plant-based and dietary expansions
- Late-night and daypart additions
See it on real menu data.
The fastest way to understand Pare is to see it running. The demo study contains 250 responses tested across a hospitality starter menu with concept screening and TURF analysis fully populated.
Built and being refined. Currently in evaluation with hospitality groups.