CASE STUDY
How PayLater Travel Unified Global Sales Analytics to Improve Forecasting and Customer Retention
AT A GLANCE
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Client: PayLater Travel Services
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Industry: Travel & Leisure (Buy Now Pay Later)
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Location: Global Operations (AU, US)
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Solution: Sales Performance & Customer Insights
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Key Impact: Real-time visibility, improved forecasting, customer behavior insights
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Background
PayLater Travel Services operates in the rapidly evolving buy-now-pay-later segment of the travel industry, offering flexible payment solutions for vacation bookings across multiple markets. The company serves customers in Australia and the United States, processing thousands of bookings monthly while managing complex deposit schedules and payment plans.
As a technology-enabled financial services provider in the travel sector, PayLater required sophisticated analytics to balance risk management with growth objectives while maintaining visibility into customer behavior patterns and regional performance variations.
The Challenge
PayLater Travel faced significant challenges in tracking sales performance across their multi-regional operations. The company lacked unified visibility into critical metrics including bookings, deposits, cancellations, and repeat customer rates. This fragmented view made it impossible to accurately assess business health or make informed strategic decisions.
The absence of month-over-month comparative analytics meant leadership couldn't identify trends or seasonal patterns that were crucial for capacity planning and risk management. Regional performance comparisons between Australia and US markets were manual and time-consuming, preventing quick identification of market-specific opportunities or challenges.
Without actionable insights into deposit behaviors and booking size trends, PayLater struggled to optimize their risk models and pricing strategies. The company had limited ability to measure sales recovery rates or predict revenue flow, creating uncertainty in financial planning. Manual Excel-based reports were inconsistent, error-prone, and couldn't provide the real-time analytics required for effective decision-making in a dynamic market environment.
The Solution
GrowthBI developed a centralized Power BI Sales Dashboard powered by BigQuery, integrating booking, deposit, and sales data through automated API-based pipelines. The solution created a unified, near real-time reporting layer that empowered leadership and finance teams to monitor performance with precision.
The KPI Snapshot provided real-time metrics for total and active bookings, repeat percentage, cancellation rates, deposits collected, and average booking size. The dashboard featured MTD versus previous MTD comparisons for instant benchmarking of all key performance indicators.
Key capabilities included:
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Monthly Trend Analysis: Comprehensive tracking of sales, deposits, and cancellations with regional overlays for AU, US, and company-wide performance
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Regional Comparison Tools: Detailed benchmarking visualizations comparing performance across markets with conditional formatting to highlight above or below-target regions
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Customer Behavior Analytics: Advanced segmentation identifying repeat customers contributing to revenue, with scatter plots showing relationships between repeat rates and deposit percentages
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Predictive Revenue Modeling: Forecasting tools projecting cash inflows based on booking patterns and historical deposit behaviors
Results
The unified sales dashboard transformed PayLater's operational visibility and decision-making capabilities. Leadership gained real-time insight into business performance across all markets, enabling rapid response to emerging trends or challenges. The automated reporting eliminated manual data compilation while providing superior accuracy and timeliness.
Forecasting accuracy improved significantly through deposit percentage trends and customer behavior analytics. The identification that repeat customers contributed 32.9% of total bookings enabled targeted retention campaigns and loyalty program development.
Key performance outcomes included:
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Real-time visibility across global operations
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Improved forecasting accuracy for cash flow planning
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Reduced reporting time from days to minutes
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Enhanced risk assessment through deposit pattern analysis
The regional comparison capabilities revealed market-specific opportunities that informed differentiated marketing and pricing strategies. Finance teams could now predict revenue flow with greater confidence, improving working capital management and investment decisions.
Looking Forward
PayLater Travel continues to enhance their analytics platform with plans to integrate external data sources including economic indicators and travel trend analytics. The company is developing predictive models for customer lifetime value and default risk, further strengthening their competitive position in the travel fintech market.
The unified sales dashboard has become the foundation for all strategic decisions, with the company now exploring machine learning models to predict booking patterns and optimize deposit requirements.
Want to see the technical details behind this implementation? Read our technical deep-dive to learn how we integrated BigQuery with Power BI using API pipelines for real-time analytics.