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Marketing Efforts 360° View
Technology Category
- Analytics & Modeling - Real Time Analytics
- Analytics & Modeling - Big Data Analytics
Applicable Industries
- Transportation
Applicable Functions
- Sales & Marketing
Use Cases
- Real-Time Location System (RTLS)
- Supply Chain Visibility
Services
- Data Science Services
The Challenge
Trainline, Europe’s leading independent train travel platform, was facing a 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 tool for accurate marketing insights. They had invested in many different services and solutions to sustain their growth, but these were not always easy to manage. The company decided to build a centralized, global, real-time dashboard to get a global understanding of their marketing acquisition. The challenge was to start a big data project from scratch, ensuring that the technical team ended up with a tool that allowed them to improve and upgrade their own skills while also satisfying the marketing department’s requests quickly and efficiently.
About The Customer
Trainline is Europe’s leading independent train travel platform and retailer of rail tickets. The company 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, bringing together all major train companies onto one platform and providing customers with a complete set of travel options. The company makes it easy for customers to find the best price and book their journey.
The Solution
To meet the unique challenges and needs of both the technical and marketing teams, Trainline turned to Dataiku Data Science Studio (DSS). This tool allowed them to save time by using Dataiku’s workflow development features to duplicate workflows across teams and across projects. It also enabled them to blend multiple data sources and create dedicated custom connectors to gather all data formats, thanks to Dataiku’s flexibility and coding features. Dataiku’s whitebox interface allowed them to instantly detect and solve 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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