AI-Powered Pricing Delivers 1–3% Revenue Uplift and More Bookings for Leading Airline
Smarter Fares, Higher Yield:
Aeroméxico
1-3%
Total revenue uplift from AI-driven continuous pricing and dynamic offers
PrimeAI helped Aeroméxico replace rigid fare buckets with AI-driven demand and price elasticity models, enabling continuous pricing and personalized bundles that captured 1–3% more revenue with higher booking conversion.
By treating demand as a function of price, PrimeAI’s solution delivered faster, data-backed pricing decisions, more relevant offers across channels, and a scalable foundation for future dynamic offer innovation.
The Challenge
Legacy revenue management treated each fare class as if demand would be the same, regardless of price, ignoring real customer sensitivity and competitive dynamics. Aéromexico struggled to react quickly to demand surges, competitor promotions, and seasonality, leaving money on the table or discounting too deeply.
Static price points forced “take it or leave it” jumps between fare classes, causing mid-willingness-to-pay customers to defect or not book at all. Further, teams lacked clear elasticity insights by route, cabin, and channel, making it difficult to defend pricing decisions with data in executive discussions.
PrimeAI’s Solution
PrimeAI implemented AI/ML models that jointly forecast demand and estimate price elasticity, treating demand as a function of price instead of a fixed assumption. Continuous pricing algorithms identified optimal fares between existing price points, smoothing sharp jumps and capturing revenue.
Dynamic bundling engines assembled personalized packages—seats, bags, ancillaries—priced to each customer segment’s willingness to pay and trip purpose.
PrimeAI delivered a production-ready, real-time pricing service within 3–6 months, integrating with existing revenue management and e-commerce channels with minimal disruption.
Revenue teams gained route-level elasticity and performance insights, enabling faster experimentation and more confident pricing decisions in weekly yield meetings. By modernizing pricing with AI/ML, Aéromexico built a scalable foundation for future dynamic offer innovations, strengthening competitiveness and customer satisfaction.
Aeroméxico achieved a 1–3% increase in total revenue, driven by smarter fares and higher conversion at profitable price points.
Booking conversion improved on targeted routes, as customers saw more relevant price options and personalized bundles instead of rigid fare ladders.
The Results
Customer Success Stories
-
![Man working at a desktop computer in a busy office, wearing a headset, with multiple monitors and laptops around him.]()
Marmic Technician Scheduling & Routing
Marmic struggled with inefficient manual technician scheduling & routing caused lost technician availability, overtime, and excessive travel costs. By using our workforce scheduling & routing optimizer, they increased revenue 10%, cut overtime by 91%, and enabled 90 days of forward visibility instead of just 48 hours.
-
![Street cleaning vehicle with orange and gray exterior, parked on city street with buildings in the background.]()
CheckSammy Pricing Optimization & Workforce Routing
CheckSammy’s manual routing, scheduling, and non-optimized pricing limited capacity and profitability. With our scheduling, routing, and pricing optimization, they doubled operational and revenue capacity without adding headcount or infrastructure, supporting a $150M capital raise as revenue rose and costs fell.
-
![A woman with curly hair is sitting at a desk in front of six large monitors displaying spreadsheets. She is smiling and wearing a white shirt, working in a bright, modern office space.]()
LexisNexis De-Identification & Risk Mitigation
LexisNexis wanted to grow revenue by offering HIPAA-compliant enriched healthcare data products and risk insights. Using our de-identification and risk-scoring platform, they scaled compliant data products, reduced privacy risk, and accelerated regulatory certification and customer onboarding cycles.
-
![Laptop screen displaying a flight search website, with options to enter departure and return dates, and number of adults and children, under a sky background with an airplane.]()
Aeroméxico Dynamic Pricing
Aeroméxico’s rigid fare classes failed to reflect real customer price sensitivity across routes and seasons. Our dynamic pricing optimization algorithm improved offer relevance, demonstrated higher conversion, and lifted passenger revenue by approximately 1–3% on targeted flows.
-
![Group of friends with luggage at airport, smiling and talking.]()
Hotel Demand Forecasting & Price Optimization
A Major Hotel Group struggled with static pricing and weak demand forecasts that left rooms underpriced or empty. After deploying our forecasting and dynamic pricing optimizers, this hotel group grew revenue by 2.7% and significantly increased adoption of advanced pricing tools among global hotel managers.
-
![A worker wearing a hard hat looks at a tablet on a highway with moving trucks, with digital location markers and network lines overlaying, representing smart logistics and connected technology.]()
Forto Demand Planning & Pricing Optimization
Freight forwarder Forto faced inaccurate container demand forecasts and suboptimal pricing that constrained margins and growth. By using our demand forecasting and dynamic pricing optimizers, they added over $1M in monthly revenue, enabling a profitable, scalable growth trajectory.
