Plate-forme
Découvrez les possibilités de Palisis
Élargissez votre audience et augmentez vos ventes
Solutions
Guichet unique
Rationalisez vos opérations commerciales dans le secteur du voyage
Augmentez votre portée commerciale avec TourCMS
Des boutiques en ligne aux widgets, en passant par les API personnalisées
Intégrations
Aperçu
Découvrez comment Palisis soutient votre secteur d’activité
Découvrez, grâce aux témoignages d’opérateurs, comment nous soutenons votre entreprise.
Secteurs
Contrôlez vos foules sans effort
Billetterie en ligne instantanée pour les opérateurs de trains touristiques
Réduisez les files d’attente et simplifiez les réservations
Faites passer votre présence en ligne au niveau supérieur
Études de cas
Entreprise
Catégories
Articles en vedette
What happens after the booking? Understanding refunds and unused tickets reveals where revenue leaks — and how to plug them.
On average, 2.9% of tickets were refunded in 2024. While this seems small, it represents nearly 170,000 tickets and over €3.9 million in lost revenue across all operators. Add the 5% of tickets that went completely unused, and the opportunity cost becomes significant.
Refund patterns reveal actionable insights. Winter months (January-February) see refund rates of 4%, dropping to just 2% by October. And while APIs drive only 14% of bookings, they account for over one-third of all refunds—a clear signal for tighter cancellation policies on indirect channels.
Explore the interactive charts showing refund patterns across months, channels, and passenger categories.
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This is just a preview. The full State of the Industry report includes monthly breakdowns, channel-specific strategies, and recommendations to reduce refund losses.
Insights, data visualizations, and actionable recommendations.
Who books hop-on hop-off tours? Discover the demographics and preferences driving the industry.
When do travellers book? Understanding the shift between online and onsite purchasing.
What are travellers willing to pay? Regional pricing variations and optimal price points.