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Four Worlds, One Language

Restaurant data lives in silos. Guest profiles sit in loyalty systems. Menus live in ordering platforms. Nutrition facts hide in spreadsheets. Transaction history scatters across POS systems. EveryBite connects these worlds—and the key that unlocks everything is food. Food Connection Diagram

Guest

Who they are, what they want, how they behave

Food

Menus, recipes, ingredients, nutrition, allergens

Ordering

What they ordered, how they customized, when & where

Loyalty

Points, tiers, tags, segments, campaigns
The insight: You don’t truly know a guest until you understand their relationship with food. Loyalty points tell you they’re valuable. Order history tells you they visit Tuesdays. But food tells you they’re managing a wheat allergy, building muscle, feeding a family, or celebrating a birthday with something indulgent.

The Four Domains

1. Guest

Who is this person? The guest domain captures identity, preferences, and behavior:
DataSourceExample
IdentityLoyalty ID, Passport, device fingerprint”This is Sarah, a returning customer”
DemographicsInferred from behavior patterns”Young professional, health-conscious”
PreferencesExplicit settings or observed patterns”Avoids dairy, prefers high-protein”
BehaviorSession analytics, interaction patterns”Browses thoroughly, customizes often”
But identity alone is shallow. Knowing Sarah is a “Gold member who visits twice a week” doesn’t tell you what she wants to eat.

2. Food

What can they eat? The food domain is the Ingredient Intelligence layer—a seven-level hierarchy from menu down to ingredient specification:
LevelWhat It Captures
MenuWhat’s available today
DishWhat guests see and order
RecipeHow the dish is assembled
Prep RecipeHouse-made components
IngredientIndividual items with allergens
Ingredient DataNutrition facts, dietary classifications
Ingredient SpecificationExact products and brands
This depth is what makes EveryBite different. We don’t just know “Caesar Salad”—we know the dressing contains anchovy and egg, the croutons have wheat, and the parmesan is dairy. We trace allergens through every layer.

3. Ordering

How do they buy? The ordering domain captures transactions and customization:
DataSourceExample
Order HistoryPOS, ordering platforms”24 orders, $18.50 average”
Frequent ItemsTransaction analysis”Honey Garlic Stir-Fry, ordered 8 times”
CustomizationsModifier selections”Always adds extra protein, removes sauce”
TimingOrder timestamps”Tuesday lunch, Thursday dinner”
Order data shows what happened. But without food intelligence, you can’t answer why they customized, or what else they might like.

4. Loyalty

What do their programs know? The loyalty domain pulls data from third-party systems:
DataSourceExample
Tier & PointsThanx, Punchh, Paytronix”Gold tier, 2,450 points”
TagsLoyalty program segmentation”birthday_month”, “protein_lover”
OffersCampaign targeting”Eligible for free dessert promo”
PreferencesStated in loyalty profile”Prefers no onions”
Loyalty platforms know value and engagement—but they don’t understand food. They can’t tell you if a “high-value customer” can actually eat your new menu item.

Food: The Connective Tissue

Here’s the key insight: Food is how you understand people. Without food intelligence, the other domains are disconnected:
DomainWithout FoodWith Food
Guest”Sarah visits Tuesdays""Sarah avoids wheat, loves high-protein, customizes for her macros”
Ordering”She orders the stir-fry""She orders the stir-fry because it’s her highest-protein wheat-free option”
Loyalty”Gold tier, 2,450 points""High-value guest who needs wheat-free options—show her the new grain bowl”
Food turns data into understanding. It answers:
  • Why does she order that dish? (It fits her dietary needs)
  • What else would she like? (Other high-protein, wheat-free options)
  • How should we personalize? (Highlight compatible dishes, warn about allergens)
  • When is she at risk? (If we remove her favorite dish, she might churn)
“EveryBite” — The name isn’t accidental. Every bite tells you something about the person. What they choose, what they avoid, how they customize—these are signals that reveal who they are and what they want.

How the Domains Connect

Guest + Food = Personalization

When a guest opens the menu, we know their dietary restrictions before they search:
Guest: "wheat-free", "high-protein"

Food:  Traverse ingredient hierarchy

Result: Dishes safe for this guest, ranked by preference match
The guest sees a personalized menu from the first screen—not because we guessed, but because food intelligence lets us trace compatibility through every ingredient.

Ordering + Food = Understanding

When a guest customizes, we understand why:
Order: "Remove croutons, add extra chicken"

Food:  Croutons contain wheat, chicken adds protein

Insight: Guest is likely wheat-free and protein-focused
This inference feeds back into the guest profile, improving future personalization.

Loyalty + Food = Actionable Segments

Loyalty tags become meaningful when combined with food:
Loyalty: "Gold tier", "weekday_regular"

Food:    Observes wheat-free, high-protein ordering pattern

Segment: "High-value health-conscious regular"

Action:  Send new protein bowl promo, not pasta special
Without food, you’d send the pasta promo to someone who can’t eat it.

Guest + Ordering + Loyalty + Food = GuestIQ

When all four domains connect, you get complete guest intelligence:
1

Data Sources Flow In

Guest (identity & behavior) + Ordering (history & customization) + Loyalty (tags & tiers)
2

Food Intelligence Processes

The Ingredient Intelligence layer analyzes everything through the lens of food—what they can eat, what they prefer, what they avoid.
3

GuestIQ Delivers

Complete Profile · Smart Segments · Targeted Dishes
This is what GuestIQ returns at session creation—the guest’s complete profile, understood through the lens of food.

What This Means in Practice

For Menu Personalization

A guest opens your app. Before they search, you already know:
  • Their restrictions: Wheat-free, peanut allergy
  • Their preferences: High-protein, prefers lunch portions
  • Their patterns: Usually customizes, price-sensitive
  • Their favorites: Ordered the Power Bowl 6 times
The menu they see is already filtered, with compatible dishes highlighted and allergen warnings in place.

For Campaign Targeting

You’re launching a new high-protein grain bowl. Who should see the promo?
Traditional TargetingFood-Informed Targeting
”Active loyalty members""Wheat-free + high-protein segment"
"Frequent visitors""Guests who order protein modifications"
"High spenders""Guests whose favorites are being discontinued”
Food intelligence makes campaigns precise, not spray-and-pray.

For Staff Alerts

A VIP guest walks in. Your host stand shows:
Sarah M. — Gold member, 24 visits
  • Wheat allergy (verified)
  • Prefers: Power Bowl, Stir-Fry
  • Usually adds: extra protein
  • Note: Birthday this month
The staff can greet her by name and recommend something she can actually eat.

For Product Development

Which dishes should you add to the menu?
QuestionFood Data Answers
”What’s missing?""12% of guests are wheat-free but only 3 dishes fit"
"What’s underperforming?""This dish matches many profiles but has low reorder rate"
"What’s trending?""High-protein customizations up 40% this quarter”

The Data Model Summary

DomainWhat It KnowsKey Insight
GuestIdentity, demographics, behaviorWho the person is
FoodIngredients, nutrition, allergensWhat they can eat
OrderingTransactions, customizationsWhat they chose
LoyaltyPoints, tiers, tagsHow valuable they are
Food is the key. It transforms:
  • Anonymous visitors into understood guests
  • Transaction data into dietary insights
  • Loyalty tiers into actionable segments
  • Generic menus into personalized experiences

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