Last April in Paris, more than 80 attendees came together for the first CAYZN International User Group. Over two days, 32 sessions were held — 23 workshops, 6 presentations, and 3 creative sessions — spanning 22 themes across 5 tracks. The conversations were above all insightful and practical, and across sessions, similar ideas kept surfacing.

Analysts proposed more customized ways to navigate the platform. Ancillary teams defined simpler approaches to managing add-ons and total product complexity. Superusers mapped out safer and faster ways to test and execute business rules. And across the board, users collectively identified ways to prioritize more effectively, get better guidance, and be more confident in the yield actions they take day-in-day-out.

Those conversations shaped the past year of product development. Since the User Group, the team has shipped 50+ features directly mapped to the themes raised. This article walks through what changed and why it matters for teams running revenue management at scale.

Greater Interface Consistency, Faster Workflows

Across multiple sessions, a consistent theme emerged. Even in a platform already designed to facilitate navigation, small inconsistencies in layout, interaction patterns, or component behavior can add up across a day of high-frequency decisions. In dedicated rail, bus and LCC, and broader UX workshops, participants found ways to simplify layouts and workflows further, and identified greater flexibility in how information is displayed for their specific business cases.

What changed

Over the past year, these inputs translated into the rollout of a New Design System, along with targeted improvements for LCC, bus and rail workflows. Feature releases included a more coherent and simplified layout, the removal of underused views, and notifications redesigned to be more subtle and useful. New decision-facilitating views were also introduced, including an expandable view to easily manage multiple legs, which is especially beneficial for rail and bus operators handling big networks.

What impact it has

The impact is practical across all use cases: Analysts move faster with a more consistent, seamless interface, boosting their day to day productivity. New users reach adoption sooner. And for everyone, this means greater efficiency and fewer friction points when it matters most — during high-pressure periods.

KPIs and Views That Reflect How Analysts Work On Their Day-To-Day

One of the more consistent themes at the User Group was KPI ownership and layout flexibility. A platform that reflects those customization features unlocks greater confidence, control, and adoption. Participants also pointed toward the need for maintaining alignment across teams.

What changed

Customizable views give each analyst the ability to personalize what they see and how — selecting KPIs, configuring layouts, and setting sorting preferences and conditional formatting — while admins maintain a shared default view for organizational consistency. Custom KPIs are coming next, taking personalization a step further by letting teams define their own performance metrics. Full RM layout personalization is also underway, extending that same flexibility to the entire core working environment.

What impact it has

Teams can work in a setup that matches their preference, while staying aligned around a shared framework. The result is greater data confidence, sharper decisions, and a platform that works the way the business works.

Making Network Complexity Easier to Act On

For teams working with multi-leg or multi-market networks, the main challenge was not access to data but the time required to interpret it. Their day to day is defined by switching between different views, understanding how they relate to each other, and acting quickly when conditions change. This surfaced in discussions around rail and bus use cases, where complexity is structural.

What changed

The introduction of the new leg view surfaces network context more directly, making it easier to read O&D signals alongside leg-level constraints and understand the trade-offs between them. Hybrid OD/leg management is also in development, bringing both perspectives into a unified workflow.

What impact it has

The goal is to shorten the path from reading the network to acting on it. Analysts can identify trade-offs more clearly, act on them more quickly, and spend less time piecing together context across multiple views.

Managing Ancillary Performance Dynamically at Scale

Ancillaries represent one of the fastest-growing areas of revenue complexity for airlines. As ancillary catalogs expand, managing those products at a service or date level calls for a more tailored approach with views that reflect an analyst’s performance-evaluation. Teams also pointed toward dynamic pricing as a way to better respond to demand and market conditions.

What changed

In response, ancillary capabilities have been strengthened in three steps: Capacity management improvements give teams earlier visibility and better control over availability. The introduction and extension of category handling supports larger, more structured catalogs without the need for manual handling, while also providing a better robustness in how ancillary data is structured and managed. Dynamic pricing has been introduced, adding a more responsive way to adjust ancillary prices as demand shifts.

What impact it has

These changes make it easier to manage larger ancillary portfolios without added manual effort, with better control over availability. Dynamic pricing extends this further — giving teams the agility to respond to demand and market conditions as they evolve, capturing more revenue opportunities while the system remains stable at all times.

AI in CAYZN: Sharper Signals, Trusted Decisions

The User Group revealed also something important about how analysts wished to interact with AI: teams wanted AI that helps them focus on what matters most, with enough transparency to act on it confidently and quickly.

What changed

Some significant AI capabilities have been shipped since the User Group: New CAYZN AI filters help analysts cut through signal overload by surfacing the markets and services that require attention most urgently. An AI Strategies feature has been introduced, letting teams define preset or custom strategies and apply them to services directly from the main interface in just one click, enabling greater analyst reactivity. And a risk-based overbooking recommendation engine now delivers scenario-based recommendations — giving teams the confidence to act on routes with no-show potential.

What impact it has

Together, these advances improve above all the interaction analysts have with CAYZN’s AI module: For analysts the time they spend triaging is reduced, allowing them to move from manual task execution to taking strategic decisions, while the quality of the decisions they make improves, as the platform surfaces the right signals, explains why they matter, and supports teams in acting with greater speed and confidence.

More Control & Confidence for Your Business Rules Management

For users managing business rules, the balance between autonomy and operational safety is key. Ideas that surfaced during the user group centered around this notion: greater visibility into rule context and execution, a way to debug issues, and the need to understand the impact of a change before applying it.

What changed

The evolution of the Business Rule Engine includes the introduction of a debugging feature, a centralized multi-BR execution feature for streamlining workflows, a module for tracking the consumption and activity of BRs, and the ability to reuse templates that define how rules automatically monitor and react to competitor moves. The BRE interface also has been significantly enriched — with clearer execution context, and additional rule building parameters — enabling more sophisticated rule configurations that can be more easily understood.

What impact it has

Together, these changes give teams the tools to manage business rules with greater speed, confidence, and autonomy — while significantly reducing the time spent on execution management.

Areas Where Development Is Ongoing

Some themes from the User Group represent longer-term investments, and progress is building steadily:

• Continuous Pricing remains a priority: rather than replacing the bucket paradigm entirely, the direction is to preserve it — maintaining the operational control and system compatibility teams rely on — while enabling greater granularity within each bucket. The goal is to eliminate price cliffs: those sharp jumps from one fare step to the next that leave revenue on the table and create friction for customers. By moving toward continuous pricing within existing bucket structures, CAYZN aims to capture willingness-to-pay more precisely, smooth the price curve, and improve conversion — without requiring a full overhaul of how operators manage and distribute fares today.
• Simulation and Scenario Planning turns complex strategic questions into decisions teams can act on with confidence. The direction is to make it easier to define scenarios clearly — from a single service-date all the way to a full network — run them rapidly, and interpret results through decision-ready outputs that go beyond raw data: what changed, why it matters, and what to do next. With the Simulation Lab, a scenario can be defined, run, and refined in minutes — delivering revenue impact, load factor estimates, cannibalisation analysis, and sensitivity bands in a single view. The goal is to move from analyst-days to analyst-minutes.
• Horizon continues to evolve as CAYZN's Commercial Intelligence layer — a decision hub for executives built around macro views for real-time data. Horizon V2 already brought additional configurable KPIs, advanced filter capabilities, and more flexible time windows. Horizon V3 takes this further, introducing AI Agent Reports that let analysts ask questions and get answers in seconds by browsing all RM data in CAYZN. Disruptive KPIs unlock new performance dimensions — including comparison vs. objectives, ancillary performance, and positioning across carrier types; and a dedicated Mobile App brings your custom KPIs and dashboards into a pocket-sized format, built for on-the-go performance monitoring.
• AI Agents are being developed as intelligent assistants embedded directly into CAYZN workflows — accelerating execution, sharpening pricing decisions, and keeping users in full control throughout. A Business Rules Agent is underway to help write, explain, and debug rules, with human validation ultimately driving the execution. A Pricing Recommendation Agent is being designed to surface clear, actionable recommendations — supporting analyst judgment at every critical decision point.

What This Reflects About How We Build

Over the past 12 months, the team has shipped 50+ features — and 84% are already live today.

One thing remains clear: The CAYZN roadmap is customer-shaped by design. The User Group wasn't a listening exercise — it was a planning input, and the features shipped over the past year are a direct reflection of that.

Beyond the roadmap impact, the User Group reminded us what a strong user community can unlock: shared thinking, collective ambition, and a product that gets sharper with every conversation.

That community is what drives this process forward — and why we'll keep building the next User Group on the same foundation: direct conversations with the people doing the work, feeding into what gets built next.

‍