A Canadian airline sought to modernize its marketing and operational decision-making through a more sophisticated use of data and analytics.

Key challenges included:

• Disconnected internal teams and external partners with varying data needs
• Limited access to external tourism and travel trend data
• Underutilization of AI for marketing optimization
• Lack of user-friendly tools for non-technical stakeholders to access insights
• Organizational need for greater understanding and enthusiasm around data initiatives

The airline needed a clear data and analytics strategy — and expert leadership to bring it to life.

CVM led the engagement to design and implement a comprehensive AI & Analytics Strategy tailored to the airline’s goals.

Key aspects of the solution included:

• Stakeholder Collaboration: Worked closely with internal departments and agency partners to align data priorities and define use cases.
• External Data Sourcing: Identified and procured high-value external datasets, such as tourism trends and market intelligence, to enrich internal data assets.
• AI Model Development: Built machine learning models to optimize ad targeting, improving personalization and marketing ROI.
• Visualization and Workflow Tools: Implemented dashboards and workflow automation solutions to make data insights accessible and actionable for non-technical users.
• Data Evangelism: Led internal education efforts to promote a data-driven culture, including executive briefings, workshops, and communications.

Throughout the project, CVM emphasized practical, scalable solutions to ensure long-term adoption and success.

• More Targeted Marketing: AI-driven models enabled more efficient and effective customer targeting, improving advertising outcomes.
• Expanded Data Ecosystem: External tourism data provided new insights to inform planning and campaign strategy.
• Increased Data Accessibility: User-friendly visualization tools empowered broader teams to leverage data in day-to-day decision-making.
• Cultural Shift Toward Data-Driven Thinking: Organization-wide initiatives helped embed a stronger understanding of and commitment to data and analytics.

• A Strategy is Only as Good as Its Adoption: Success required not just building tools, but engaging people across the organization.
• External Data Adds Value: Carefully sourced third-party datasets can significantly enhance internal decision-making.
• AI Models Must Be Actionable: Models built for real-world marketing teams need to be integrated into workflows, not left in isolation.