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How PayLater Travel Unified Sales, Deposits & Performance

  • Writer: GrowthBI
    GrowthBI
  • Nov 28, 2025
  • 3 min read

Updated: Feb 17

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.


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 Insight

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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