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National flag carrier Philippines Airlines (PAL) was hit hard by COVID. To drive business growth, PAL partnered with Thinking Machines to develop a Customer Data Analytics Platform for a deeper customer understanding and to accelerate data-driven culture within the organization.
We merged several key internal resources such as flight information, loyalty member activities, and customer experience/feedback with third-party sources such as Twitter.
Applied advanced analytics & machine learning techniques to business problems. We developed artificial intelligence (AI)/machine learning (ML) models to understand customer value, sentiments, and other key metrics.
Customized dashboards/user interfaces for tailored-fit data insights. This broad set of tools is customized for three key stakeholders–executive, business, and technical users.
Capability-building efforts across different functions through workshops and hands-on training.
impact
90% Faster Insighting
Reduced time spent to generate key reports
impact
Operationalizing Big Data
Our Customer Data Analytics Platform processes largescale data daily
Activating Data to Transform Customer Decision Making for Philippine Airlines
PAL carries the distinction of being the country's flagship carrier and Asia’s oldest airline. In mid-2020, the company faced multiple external and internal challenges:
COVID-19 had significantly reduced demand and regional operations. This led to an even greater need to make every dollar count. PAL needed real-time insights and data-driven decision-making to remain competitive.
Consolidating and analyzing data from multiple systems. This resulted in spending significant time and effort on data processing instead of analysis, making real-time insights difficult to obtain.
PAL saw these challenges as an opportunity to explore the applications of AI and build a data-driven culture from the ground up to empower all stakeholders.
An analytics platform that merged datasets across crucial data sources
Thinking Machines built a platform for PAL to integrate multiple data sources, analyze data and generate insights, and augment decision-making with AI. We achieved this by:
Deploying interpretable ML models: We developed modern analytics tools with easy-to-use user interfaces for real-time decision-making. This enabled the PAL team to better understand their customers beyond historical/past transactions and performance.
Creating a Single Customer Dashboard View: This business intelligence layer provided critical insights into different segments of customers, including that outside of the Mabuhay Miles program.
Conducting data strategy and capability-building sessions: We worked with PAL teams to conduct workshops and demos with attendees across various departments (e.g., Sales, Marketing, Strategy & Planning) in an agile manner. This enabled the PAL team to own the Platform and develop their cases for future use.
The first phase focused on business intelligence, where the setup of a data repository and dashboards supported the creation of descriptive and diagnostic business intelligence reports. The next phase covered AI/ML Development, which includes deploying custom AI/ML models for priority predictive use cases and initiatives. Data strategy and capability-building training were provided for various roles/departments during both phases.
Activating Data to Transform Customer Decision Making for Philippine Airlines
The data analytics platform was built with the following tools:
Google Cloud Platform: A suite of cloud computing services on the same infrastructure that Google uses internally for its end-user products (Google Drive, Gmail, Google Search)
Compute Engine: A computing and hosting service that runs virtual machines on Google infrastructure
Cloud SQL: A cloud database service that helps set up, maintain, manage, and administer relational databases on Google Cloud Platform
Cloud Storage: A cloud computing model that stores data on the web through a cloud computing provider
BigQuery: A big data analytics web service for processing very large data sets
Data Studio: An online tool that converts data into customizable informative reports and dashboards
Dagster: A data orchestrator for the development, production, and observation of data assets.
Dataform: An application to manage data in multiple data warehouses to build a single source of truth
Tableau: A visual analytics and business intelligence platform that creates data visualizations for more accessible interpretation
Google Colab: An executable document that allows users to write, run, and share code within Google Drive
A unified and proper data platform to propel data-driven decision making
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Activating Data to Transform Customer Decision Making for Philippine Airlines
Our Data Analytics Platform solved the challenge of having data spread out across multiple systems and teams. PAL can now fast-track its analysis and strategic planning for future initiatives by having a consolidated view of datasets across various sources. The Data Analytics Platform will easily facilitate data analysis and strategic thinking for future use cases. For example, the Sales, Marketing, and Loyalty dashboards can help PAL determine the revenue potential of different opportunities, implement targeted marketing, and improve customer experience. The successful implementation of the data analytics platform aligns with PAL’s roadmap towards becoming a more data-driven and customer-centric organization.