Guests answer six quick questions
Each question identifies a different dimension of the guest's palate.
Personalized cocktail recommendations that turn guest indecision into confident drink orders.
PROOF is a digital cocktail menu for restaurants that matches each guest with drinks they're likely to enjoy, while giving operators clearer insight into what their customers actually want.
Cocktail menus are getting better — and harder to navigate.
Guests want to try something new. But most of them don't know what clarified milk, amaro, aquavit, or fat-washed bourbon is going to taste like.
So they hesitate. They ask for a generic recommendation, or they fall back on the same order they always place. When they do take a chance, they often end up with a drink that tastes nothing like they expected.
Six questions. Three personalized recommendations.
PROOF matches them to your menu
Each guest receives three personalized recommendations, scored against their palate profile.
Your restaurant sees the patterns
Aggregated preference data reveals what guests are looking for and where your menu may have gaps or opportunities.
More than a survey.
Question design
PROOF is built on in-depth research into taste, preference measurement, psychometrics, and survey design. Each question is designed to reveal the contours of a guest's palate, not simply to ask which spirits or flavors they already know they like.Cocktail scoring
Every drink on a restaurant's menu is evaluated with PROOF's proprietary cocktail scoring system. The platform maps guest preferences and menu items across the same set of taste dimensions, then measures the distance between those two points.The result
A recommendation based not on popularity or broad drink categories, but on the specific relationship between one guest's preferences and the drinks actually available on your menu.Better ordering on the floor. Better information behind it.
On the floor
Make the menu easier to navigate
Give guests a starting point, even when the cocktail list feels unfamiliar.Turn uncertainty into orders
Help guests choose something new without ordering blindly or defaulting to the familiar.Higher check averages
When guests enjoy the first drink, they explore the next recommendation with more confidence.Create a more personal experience
Make each guest feel understood without adding friction to service.Behind the bar
Help staff recommend at scale
Every guest gets a personalized starting point without a long conversation with the server.Turn preferences into data
See which flavors, ingredients, and drink styles appeal most to the people in your room.Discover unmet demand
Identify preferences your current menu doesn't serve and what to build next.Fill the gap with a new recipe
Gaps in the menu can be filled by custom craft cocktail recipes, designed in our proprietary Menu Lab.See what your guests want.
What guests are drawn to, which drinks are getting recommended, and where demand isn't matching the current menu.
Sample data — illustrative only
Preference report · Last 30 days
1,284 profiles
Flavor demand
Bitter & herbaceous31%
Bright & citrus-forward26%
Rich & spirit-forward22%
Light & effervescent14%
Sweet & dessert-leaning7%
Menu signal
Paper Plane312 recs
Oaxaca Old Fashioned241 recs
Garden Spritz96 recs
Unmet demand
Guests are asking for bitter, low-ABV drinks at nearly twice the rate your menu can currently serve.
Founder & CEO
Michael Campanella
Michael Campanella is a culinarian and mixologist obsessed with exploring why people like what they like. He studied philosophy at NYU, with a focus on philosophy of mind, personality, and epistemology, and has spent seven years studying taste science as part of his broader culinary interests. He is an award winning cook, caterer, recipe developer, and the author of Theater of the Kitchen, a cookbook that teaches readers how to use taste science and creative instinct to cook without a recipe. He is a passionate mixologist and has created over 500 original craft cocktail recipes.Co-founder & CTO
Jake Huffaker
Jake Huffaker combines a background in computer science, behavioral economics, and optimization science to understand how people make choices and how those choices can be translated into useful patterns. He studied economics and computer science at Princeton, with a focus on behavioral economics, optimization, and data-driven decision systems. He was personally mentored in clustering and personality-based marketing by Chris Kuenne, an industry leader in customer segmentation. At PROOF, Jake leads the data architecture behind the recommendation engine, palate profiles, cocktail scoring system, and restaurant analytics.Become a pilot
Bring personalized drink discovery and clearer customer insight to your restaurant.
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