Unified Customer Journey for a Leading Tourism Group

Challenge

A leading European tourism group wanted to build a comprehensive view of the customer journey, consolidating booking components from hotels, flights, and other travel services across multiple disconnected systems into a single, customer-centric perspective.

The existing data integration relied on a 15-year-old ETL implementation built on Informatica PowerCenter and IBM DB2. Batch processing alone consumed over six hours per run, frequently ran unstable, and could not keep pace with the business need for timely customer insights. With the legacy vendor’s tooling approaching end of support on the target cloud infrastructure, operating costs were rising while flexibility declined. The marketing department required customer activity ratings to identify cross-selling opportunities across travel bookings, but the fragmented data environment and slow processing made this impossible on a daily basis.

Approach

Alligator Company redesigned the data integration architecture from the ground up, migrating from traditional ETL to a modern ELT approach on AWS Snowflake. The first priority was eliminating the legacy tooling bottleneck: the team replaced Informatica PowerCenter and IBM DB2 with an ingestion pipeline feeding directly into AWS Snowflake.

With the new platform in place, Alligator Company analyzed and harmonized data from the disparate booking systems and established consistent structures across all travel service providers. Building on this harmonized foundation, the team consolidated the different booking components (hotels, flights, transfers) into a unified customer journey using modular SQL transformation steps in dbt. Each transformation is versioned, tested, and documented as code.

The unified customer view then enabled the final objective: deriving customer activity ratings for the marketing department. These ratings power targeted cross-selling and retention initiatives across travel bookings.

Outcome

Daily customer insights replaced the previous weekly or ad-hoc batch outputs, and customer activity ratings for marketing went live as the first use case on the new platform. The modular dbt-based transformation layer provides a stable foundation for future extensions without the brittleness of the legacy monolithic ETL.

• Processing time reduced by 97%: from over six hours to ten minutes
• Same-day analytics enabled for the first time
• Data-driven cross-selling across travel bookings now operational