Smart User Segmentation for Targeted Recommendation
Company Size
1,000+
Region
- Europe
Country
- Belgium
- France
- Italy
- Poland
- Spain
- Switzerland
- United Kingdom
Product
- Dataiku Data Science Studio (DSS)
Tech Stack
- Machine Learning
- Data Analysis
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Revenue Growth
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Machine Learning
Applicable Functions
- Sales & Marketing
Services
- Data Science Services
About The Customer
Voyage Privé is the #1 exclusive members-only travel club, offering up to 70% off 4 and 5-star hotels. The company started its operations in France and now has over 25 million members worldwide with operations in both Belgium and Switzerland, and offices in France, UK, Spain, Italy, and Poland. Voyage Privé uses advanced customer data analysis to offer personalized highly-relevant travel recommendations to its members.
The Challenge
Voyage Privé, a boutique vacation retailer, faced the challenge of creating personalized offer displays for its customers. The company needed to expand the range of customer signals that could be captured and analyzed to offer travel options that were appropriate for their members. This required a software solution that could capture and make sense of large amounts of data, develop effective customer segmentation, and implement a new non-rule-based approach for analyzing incoming and historical data. The end goal was to increase customer satisfaction by providing users with personalized offer selections while simultaneously boosting the total transaction value by customer.
The Solution
Voyage Privé implemented Dataiku Data Science Studio (DSS) to understand their customers better. The strategy started with establishing a mechanism for collecting data from customers’ online behavior, such as click paths and bookmarking. With the collected data, the focus shifted to creating a machine learning-derived score for each customer — a value that reflected the likelihood of members pursuing specific travel offers. The process of using Dataiku DSS empowered the company’s teams to collaboratively work together on specific types of data before merging it. Its drag & drop interface simplified data diagnostics while facilitating the iteration process. Ultimately, Dataiku DSS helped the company’s IT teams to develop a machine learning approach to address customer data. This coupling of online behavioral data and tailored offer selections enabled Voyage Privé to automatically present relevant buying opportunities that had the highest likelihood of customer acceptance.
Operational Impact
Quantitative Benefit
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