Technology Category
- Analytics & Modeling - Real Time Analytics
- Automation & Control - Human Machine Interface (HMI)
Applicable Industries
- Equipment & Machinery
- Transportation
Applicable Functions
- Sales & Marketing
Use Cases
- Public Transportation Management
- Real-Time Location System (RTLS)
Services
- Data Science Services
- Training
The Customer
Trainline
About The Customer
Trainline is Europe’s leading independent train travel platform and retailer of rail tickets. It sells tickets worldwide on behalf of 48 train companies, helping their customers make more than 100,000 smarter journeys every single day in and across 24 countries. Trainline is a one-stop shop for train travel, providing customers with a complete set of travel options. As an online marketplace, Trainline has always been convinced that data adds value for marketing teams. That’s why early on, they created a technical team within the marketing department tasked with creating aggregated, centralized dashboards focused on Trainline marketing acquisition efforts.
The Challenge
Trainline, Europe’s leading independent train travel platform, faced a significant challenge in monitoring and improving their marketing acquisition. With paid campaigns running 24/7 and users interacting with those ads around the clock, static dashboards were no longer sufficient. The company needed a dynamic, real-time data solution to provide the most accurate marketing insights. They had a technical team within the marketing department tasked with creating aggregated, centralized dashboards focused on Trainline marketing acquisition efforts. However, this ambitious endeavor required data science skills and a tool robust enough to blend and support multiple data formats and sources to track acquisition according to certain parameters. The challenge was to find a tool that would allow the technical team to improve and upgrade their skills while also satisfying the marketing department’s requests quickly and efficiently.
The Solution
To address these challenges, Trainline turned to Dataiku. This tool allowed them to save time by using its workflow development features to duplicate workflows across teams and projects. This eliminated the need for data scientists to continually repeat processes when creating similar workflows. Dataiku's flexibility and coding features enabled Trainline to blend multiple data sources and create dedicated custom connectors to gather all data formats. The tool's whitebox interface allowed for instant detection and resolution of data process hiccups without having to start the whole process again from the beginning. Furthermore, Dataiku’s collaborative features, web interface, and click-and-drag options empowered teams to work together regardless of technical ability. Without Dataiku, the marketing team would have to rely on the technical team to continually provide or update data, which would be inefficient and ineffective for both teams.
Operational Impact
Quantitative Benefit
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