Campasuns
How a multi-location campsite operator achieved 35% reduction in admin workload and 20% revenue increase through AI-powered automation and dynamic pricing
The Challenge
Managing 8 campsites across the South of France, Campasuns faced significant operational inefficiencies that were holding back growth and profitability.
Communication Bottlenecks
Manual email handling led to delayed responses, inconsistent communication quality, and overwhelmed staff during peak seasons
Static Pricing Limitations
Fixed pricing models couldn't adapt to market fluctuations, competitor changes, weather patterns, or local events—leaving revenue on the table
Operational Inconsistencies
Varying processes across different campsite locations created inefficiencies and made scaling difficult
Our Solution
We implemented a comprehensive automation and optimization strategy that addressed each challenge systematically:
Process Mapping & Optimization
Used Miro to map out all business processes across campsites, identifying inefficiencies and standardizing best practices
AI Email Automation
Developed custom Python application integrated with OpenAI API to automatically handle, categorize, and respond to customer emails 24/7
Operational Systems Automation
Automated repetitive administrative tasks and created consistent workflows across all 8 campsite locations
Custom Dynamic Pricing Software
Built the industry's first AI-powered dynamic pricing engine specifically designed for campsites—monitoring competitors, weather, events, and historical data to optimize revenue
Dynamic Pricing Innovation
The crown jewel of this transformation was our custom-built dynamic pricing platform—a sophisticated ML system that doesn't exist anywhere else in the campsite industry. Traditional pricing tools couldn't handle the unique complexities of campsite management, so we built one from the ground up.
Competitor Intelligence
Automated competitor discovery and price tracking using camping-and-co.com, monitoring market rates within customizable radius zones
Multi-Source Data Enrichment
Real-time integration of weather forecasts, holiday calendars, local events, and temporal features to identify pricing correlations
Machine Learning Predictions
Advanced ML algorithms analyze historical patterns, capacity management, and market conditions to predict optimal prices aligned with business goals
Flexible Pricing Strategies
Choose from Conservative, Balanced, or Aggressive pricing approaches with fine-tuned controls for demand sensitivity and price aggression
The Platform Features
Intelligent Pricing Engine
- Multi-strategy pricing (Conservative, Balanced, Aggressive)
- Customizable demand sensitivity and price aggression
- Occupancy target optimization (65%-90%)
- 14-day to 60-day forecast horizons
- Real-time price optimization timeline visualization
Data-Driven Intelligence
- Automatic competitor discovery within custom radius
- Weather data integration (temperature, precipitation, sunshine)
- Holiday and school break overlays
- Historical booking pattern analysis
- Revenue and occupancy forecasting
"Jengu built something that simply didn't exist in the campsite industry—an AI-powered pricing engine that actually understands our market. The system monitors competitors, overlays weather and holiday data, analyzes years of booking patterns, and uses machine learning to predict optimal prices. It's transformed how we manage pricing across our 8 locations. This level of intelligence was previously only available to hotels, and now we have it tailored specifically for campsites."
Inside the Platform
Explore the AI-powered features that make intelligent campsite pricing possible
Competitor Discovery
Automatically discover and track competitor campsites within a customizable radius using camping-and-co.com data. The system monitors 10+ competitors in real-time, tracking their pricing strategies and availability to inform intelligent pricing decisions.
Multi-Source Data Enrichment
The platform enriches historical booking data with weather information (temperature, precipitation, sunshine hours), holiday calendars, school breaks, and temporal features (day of week, season, weekend indicators). All data sources are automatically synchronized and processed for ML analysis.
Strategic Pricing Controls
Choose from Conservative, Balanced, or Aggressive pricing strategies with fine-tuned controls for demand sensitivity (30%-90%), price aggression (40%-100%), and occupancy targets (65%-90%). Each strategy adapts dynamically based on forecasted demand and market conditions.
ML-Powered Price Optimization
Advanced machine learning algorithms analyze demand forecasts, competitor pricing, weather patterns, and historical correlations to predict optimal prices up to 60 days ahead. The visualization shows current vs. optimized pricing overlaid with demand forecasts, enabling data-driven pricing decisions.
Revenue & Occupancy Forecasting
Dual forecasting charts compare current revenue/occupancy projections against ML-optimized predictions. The system provides 14-day forecasts showing potential revenue uplift and occupancy improvements, helping managers make informed capacity and pricing decisions.