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CASE STUDY

How PayLater Travel Unified Sales, Deposits & Performance

PayLater Sales Dashboard (1).png

Industry: Travel & Leisure (Buy Now Pay Later Segment)

Solution Area: Sales Performance & Customer Insights

Client: PayLater Travel Services

Tools Used: Power BI, BigQuery, Data Integration via APIs

Business Impact

Improved Visibility

Leadership now has a real-time view of total and active bookings, repeat %, and cancellations.

Better Forecasting

Deposit % trends help predict cash inflows and improve recovery planning.

Performance Benchmarking

MoM and regional comparison highlight growth opportunities and risks.

The Challenge

PayLater Travel faced difficulty tracking sales performance across multiple regions (Australia, US, and company-wide). Key challenges included:

  • No unified visibility of bookings, deposits, cancellations, and repeat customers.

  • Difficulty comparing performance month-over-month (MoM) and regionally.

  • Lack of actionable insights into deposit behaviors and booking size trends.

  • Limited ability to measure sales recovery and predict revenue flow.

Manual reports and Excel-based summaries were time-consuming, inconsistent, and unable to provide the real-time analytics required for effective decision-making.

Our Solution

We designed a centralized Power BI Sales Dashboard powered by BigQuery, integrating booking, deposit, and sales data through API-based pipelines.

The solution provided:

  • KPI Snapshot: Real-time metrics for total and active bookings, repeat %, cancellation %, deposits, and average booking size.

  • MTD vs Previous MTD Comparison: Instant benchmarking of bookings, deposits, and sales performance.

  • Trend Analysis: Month-over-month tracking of key metrics across AU, US, and company-wide performance.

  • Customer Behavior Insights: Identification of repeat customers and deposit patterns to detect loyalty and risk signals.

This created a unified, near real-time reporting layer that empowered leadership and finance teams to monitor performance with precision.

Dashboard Walkthrough

1. KPI Snapshot

Purpose: Provide a single-glance summary of business performance.

Key Visuals:

  • KPI Cards for Bookings, Active Bookings, Repeat %, Cancellations, Deposits, and Average Booking Size.

  • MoM change indicators using color-coded deltas.

  • Power BI Features: Custom KPI visuals, dynamic date slicers, and variance indicators.

  • Impact: Provided immediate insight into booking health and deposit trends across all markets.

​

2. Monthly Trends

Purpose: Track performance trajectories and seasonal trends.

Key Visuals:

  • MoM line charts for Sales, Deposits, and Cancellations.

  • Monthly booking trends with regional overlays.

  • Power BI Features: Drill-through to specific regions or timeframes, dynamic legends, and tooltip comparisons.

  • Impact: Helped identify recovery patterns and seasonality across key markets.

​

3. Regional Comparison

Purpose: Benchmark regional performance (AU vs US vs global).

Key Visuals:

  • Comparison tables and bar charts for sales and deposits by region.

  • Conditional highlights for regions above/below target.

  • Power BI Features: Cross-region filters, comparative visuals, and export summaries.

  • Impact: Highlighted regional growth gaps and informed marketing and pricing strategies.

​

4. Customer Insights

Purpose: Track repeat and new customer performance.

Key Visuals:

  • Repeat % vs Deposit % scatter charts.

  • Segmentation by customer type, region, and booking channel.

  • Power BI Features: Drill-through to customer-level detail, repeat segmentation, and retention analysis.

  • Impact: Identified loyal customers contributing to 32.9% of total bookings, enabling targeted retention campaigns.

PayLater Sales Dashboard (1).png

Technical Architecture & Process

[Booking & Deposit APIs]
        │
        ▼
[Data Pipeline – Fivetran / Custom API Sync]
        │
        ▼
[BigQuery Data Warehouse]
  - Bookings Table (Booking ID, Date, Region, Amount)
  - Deposits Table (Deposit %, Amount, Date)
  - Customers Table (Customer ID, Repeat Flag)
  - Regions Table (AU, US, Company-Wide)
  - KPIs Table (Sales, Cancellations, Repeat %, Avg Booking Size)
        │
        ▼
[Power BI Dashboards]1️⃣ KPI Snapshot  
  2️⃣ Monthly Trends  
  3️⃣ Regional Comparison  
  4️⃣ Customer Insigh​

1) Data Extraction:

  • Data pulled from booking and deposit APIs using Fivetran connectors and scheduled syncs.

  • Data stored and refreshed daily in Google BigQuery as the single source of truth.

​

2) Transformation & Cleansing:

  • SQL scripts in BigQuery prepared MoM metrics, region-level aggregates, and customer segmentation.

  • Derived measures for Average Booking Size, Deposit %, Cancellations, and Repeat Ratio.

​

3) Data Modeling:

  • Power BI connected to BigQuery via Direct Query for near real-time refresh.

  • Relationships built across Region, Date, and Customer dimensions for seamless slicing.

​

4) Visualization Layer (Power BI):

  • Dynamic KPI visuals, MoM trendlines, and regional benchmarks.

  • Role-Level Security (RLS) applied for region-based access control.

  • Export-ready reports configured for leadership and finance users.

Conclusion

The PayLater Sales Dashboard unified global sales, deposits, and customer data into a single analytics view powered by BigQuery and Power BI.

By automating data refreshes and enabling real-time comparisons across regions and months, the dashboard transformed PayLater’s sales visibility and forecasting accuracy. It empowered leadership to make data-driven decisions, reduce cancellations, and strengthen repeat customer engagement—becoming the single source of truth for the company’s sales and performance reporting.

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