The Modern Bar Cart Podcast

Episode 311 – Flavor Attractors with Dr. Kevin Peterson
Date: March 27, 2026
Host: Eric Kozlik
Guest: Dr. Kevin Peterson (Castalia & Sfumato)

Episode Overview

This episode continues Eric Kozlik’s in-depth, data-driven exploration of flavor and memory with Dr. Kevin Peterson, blending the worlds of psychology, complex systems science, culinary aesthetics, and on-the-ground bar experience. Building on part one, this session investigates how individual personality traits shape flavor preferences, the tension between archetype and individuality, and the science (and art) of matching each person with their ideal cocktail. Dr. Peterson draws from years of survey data from Castalia (his cocktail bar/fragrance shop hybrid) and discusses concepts from his forthcoming book, Data Driven Drinks.

Featured Cocktail: Kafka Dreams (00:57–02:34)

• Kafka Dreams is presented to set the flavor landscape for later discussion.
• Ingredients:
  • 1 oz Singani (Bolivian grape spirit)
  • ½ oz Gentian liqueur
  • ½ oz coffee liqueur
  • ¼ oz cherry liqueur
  • ¼ oz chocolate liqueur
  • 1 ml cricket tincture
• Preparation: Stir with large ice; garnish with orange twist.
• Hack: The cricket tincture doesn’t add flavor, but erases harshness from Singani, acting as a "selective flavor eraser" (01:52).
• Notable Moment (01:42):
  • “The crickets, which have a flavor reminiscent of sunflower seeds, act as a selective flavor eraser… Try making this drink without the cricket tincture, take a few sips, then add the crickets and experience how the off notes get masked.” — Dr. Peterson

Key Themes & Discussion Points

Matching Humans and Cocktails: Archetypes & Personality (05:16–09:55)

• Big Five Personality Index: Peterson explores the idea of using "OCEAN" traits (openness, conscientiousness, extraversion, agreeableness, neuroticism) to better tailor cocktails to customers.
• Novelty vs. Comfort: Some patrons crave unfamiliar experiences; others are loyal to classics (07:00).
  • “Some people want a new weird drink…because they want ingredients they don’t know. How can you list that? That’s my job as a bartender.” — Dr. Peterson (06:13)
  • Baijiu as an example: Midwestern customers intrigued by unfamiliar ingredients signal a drive for novelty.
• Bartender’s Dilemma:
  • “Bartenders don’t know who just sat down in front of them… there’s a total lack of appreciation for how many ways you can slice preference.” — Kozlik (08:26)

Data, Philosophy, & The Cocktail Experience (10:06–16:08)

• Quantitative Meets Aesthetic:
  • Peterson strives for both data-driven precision and the capturing of beauty/tension in drinks (11:27).
  • “For the drinks people loved the most, it was rarely just the drink…it was always pushing them. There was always some tension built and then released.” — Dr. Peterson (12:55)
• Aesthetics of Experience: Even guests who didn’t love every drink appreciated the overall journey (14:36).
  • “You don’t have to get every drink right…” — Dr. Peterson (15:14)
• Philosophical Parallel:
  • Kozlik shares a quote about archetypes and autobiography (16:13), highlighting the balance between universal types and individual expression.

Collective vs. Individual Taste: Patterns in the Data (18:24–22:32)

• Archetypes Dominate the Average:
  • Sweet, sour, familiar drinks (e.g., margarita/gimlet types) rate highest on average, but rarely as the favorite for individuals (18:24).
    • “The highest rated drink on average was always an archetype drink… but almost never an individual’s favorite.” — Dr. Peterson
  • Polarizing drinks (like an aquavit/absinthe/spicy Old Fashioned) create both the most passionate fans and detractors (19:27).
    • “No drink is inherently good or bad. It’s the matching of the drink to the person…that’s where the improvement needs to happen.” — Dr. Peterson (21:41)
• Flavor Attractors: A Physics Analogy (22:32–27:57)
  • Kozlik introduces "flavor attractors" from complex system science.
    • “If we think of flavor archetypes as attractors…then the attractor status allows us to be sufficiently mathy that we can study it, but also sufficiently in touch with reality that everybody gets to be their own person.” — Kozlik (24:10–24:58)
  • Dr. Peterson notes the challenge in mapping cocktail "space," as so many flavor qualities are nonlinear.

Menus, Memory & The Limits of Prediction (28:20–29:52)

• Self-Prediction Fails:
  • Less than half of guests correctly predict which menu drink they’ll like best—even at a data-driven bar (28:47).
    • “People got those answers right less than half the time… For some, the one they thought they’d like least became the favorite.” — Dr. Peterson

Lightning Round & Notable Personal Moments

Transcendence in Flavor (31:17–36:24)

• Eric Kozlik: Describes being moved to near tears by pomegranate-lamb at Zahav restaurant (34:10).
  • “I just almost blacked out for a second because it was just the most perfect bite that had ever hit my palate.”
• Dr. Peterson: Recounts a similar experience with a mind-blowing cauliflower dish, emphasizing context, emotion, and memory over technical description (31:43).
  • “I felt it in different parts of my head and body than I ever felt flavor before… something happened in other deeper parts of my body where flavor doesn’t normally exist.”
• Theme: Surprising oneself or invalidating expectations is often the most memorable aspect of a tasting journey (35:36–36:41).

Favorite Menu Creations (37:33–39:56)

• Reversing Day and Night: Aquavit, absinthe, spicy Old Fashioned riff — highly polarizing.
• Kafka Dreams: The "cricket tincture" drink — remembered for novelty; most guests only recalled the presence of crickets, not the other ingredients.
  • “It was the cricket one. Couldn’t remember what kind of glass, what kind of ice… That was such a novel element that literally everything else dropped away.” — Dr. Peterson (39:23)

Wild Cocktail Science: The Ultimate Experiment (40:47–42:30)

• Dr. Peterson dreams of a longitudinal "acquired taste" experiment: repeatedly exposing guests to flavors they initially dislike (e.g., Malört), to see if and when preferences shift.
  • “Do you just have to keep subjecting someone to a flavor and eventually they enjoy it? Is it the right context?” — Dr. Peterson (41:00)
• Kozlik jokes: “What degree of Stockholm syndrome needs to exist in order for you to start liking Malört?” (42:30)

Memorable Quotes

• "No drink is inherently good or bad. It’s the matching of the drink to the person, right? Whether that’s through a menu, questionnaire, or algorithm—that’s where the improvement needs to happen." – Dr. Peterson (21:41)
• "You don’t have to get every drink right...as long as you nail at least one or two points in the experience, and offer a breadth of flavors, people appreciate the journey." – Dr. Peterson (15:14)

Ways to Follow Dr. Kevin Peterson (30:33–31:17)

• Instagram: @dr.kevinpeterson
• Website: sfumatofragrances.com (book preorders, fragrances, first book “Cocktail Theory”)

Timestamps for Important Segments

| Segment | Timestamp | |---|---| | Featured Cocktail: Kafka Dreams | 00:57–02:34 | | Archetypes / Novelty in Cocktails | 05:16–09:55 | | Data & Bartending: Between Numbers and Aesthetics | 10:06–16:08 | | Individual vs. Average Preferences | 18:24–22:32 | | Flavor Attractors | 22:32–27:57 | | Menu Prediction Failure | 28:20–29:52 | | Lightning Round (Personal moments, Memorable drinks, Experiments) | 31:17–43:00 |

Summary

This episode dives deep into the intersection of personality, psychology, and the elusive quest to give every person their ideal drink. Peterson and Kozlik’s dialogue ranges from rigorous data analysis and complex systems theory to storytelling about transcendent flavor experiences in both food and cocktails. The key takeaway? The ultimate value in hospitality is not in "perfect" drinks, but in guiding people toward surprising, memorable, and resonant experiences—sometimes with a little help from a cricket.