Coco Community — Co-living booking & automated operations
We designed a complete apartment booking platform in Paris: live availability, dynamic pricing, Stripe payments, and centralized back-office operations in one execution system.
Bubble
Stripe
Airtable
AI email ops
Context
Coco Community operates high-demand co-living apartments in Paris. The challenge was to deliver an Airbnb-level booking experience while keeping operational constraints, occupancy volatility, and community quality standards under strict control.
The initial requirement was broader than a booking UI. The business needed one coherent operating model connecting acquisition, availability, pricing, payment, and execution workflows.
Without that structure, teams were spending time on manual arbitration and data reconciliation, with a high risk of mismatch between what users could book and what operations could actually deliver.
Approach
We built the booking layer in Bubble with a configurable pricing engine driven by check-in date, stay duration, real availability, and business constraints. Payments and deposits are managed through Stripe with explicit validation states.
In parallel, we structured Airtable as the operational backbone: apartment sourcing, owner intake flows, qualification, reservation governance, and execution tracking across internal teams.
We then connected AI-assisted response workflows to absorb repetitive inbound requests (equipment, availability, recurring pre-booking questions), while keeping rule-based safeguards for sensitive cases.
Technical architecture
The system is intentionally split by responsibility: Bubble for conversion and booking UX, Stripe for transactional reliability, and Airtable for operational governance and data consistency.
This separation keeps the customer journey fast while preserving full control of business logic on the operations side. Pricing rules, statuses, priorities, and follow-up workflows remain adjustable without degrading front-end clarity.
We also formalized reservation states and critical transitions: availability check, pre-validation, payment confirmation, and operational handover. This reduces manual rework and makes every decision point traceable.
Execution model
The rollout followed short increments: booking + payments first, then data governance, then support automation. This sequencing delivered value quickly while preserving continuity for day-to-day operations.
The team now runs with one unified cockpit: centralized visibility, explicit pricing logic, controlled booking flows, and stronger throughput during demand peaks.
Results
Coco Community now operates on a full execution architecture for booking, payment collection, and operational delivery at scale. Data is aligned, decisions are faster, and service quality remains stable through high-demand periods.
Automation of low-value inbound requests frees the team for strategic cases while preserving business control on sensitive interactions.
Dynamic pricingPrecise prices according to dates and duration
After rollout, Coco Community gained a faster booking operating system: better pricing control, smoother response handling, and clearer availability management.
Time saved7 to 11 hours/week recovered on request handling and reservation follow-through.
Booking reliabilityFewer errors on pricing rules, durations, availability, and collections.
Client supportLower repetitive manual replies thanks to targeted email automations.
Business steeringUnified Airtable operations view for faster, clearer decisions.
Tracking consolidated across Bubble, Stripe, Airtable, and internal operational reporting.
Constraints and decisions
The booking engine had to handle real-world complexity: variable stays, dynamic pricing, and high request volume.
ConstraintBalance booking speed with strict control over business pricing and availability logic.
Architecture choiceTransactional Bubble layer, Stripe for payments, Airtable for operational governance.
Execution decisionAutomate repetitive requests while keeping human validation on sensitive cases.
Impact: higher operational velocity without reducing service quality.
Continuous steering and decisions
Steering runs on a short loop: booking quality, workflow incidents, support load, and the real usefulness of automation coverage.
Roadmap decisions are made ahead of demand peaks to avoid team saturation during high-pressure periods.
Outcome: a platform that stays performant as volume grows, without operational drift.
CadenceWeekly review of critical reservation workflows
ReliabilityTracking anomalies and manual recovery rate
ProfitabilityJoint view on conversion, processing cost, and margin
ScalabilityPrioritized roadmap before peak-demand windows
Goal: keep a booking engine fast, controllable, and profitable over time.
