Dataiku Case Studies Lifetime Value Optimization through Data Centralization: A BlaBlaCar Case Study

Edit This Case Study Record

	Lifetime Value Optimization through Data Centralization: A BlaBlaCar Case Study Dataiku

Lifetime Value Optimization through Data Centralization: A BlaBlaCar Case Study

Dataiku

Technology Category	Analytics & Modeling - Big Data Analytics Infrastructure as a Service (IaaS) - Cloud Databases
Applicable Industries	Cement Transportation
Applicable Functions	Logistics & Transportation Sales & Marketing
Use Cases	Demand Planning & Forecasting Last Mile Delivery
Services	Data Science Services
Challenge	BlaBlaCar, the world's first online carpooling booking service, faced a significant challenge in accessing and utilizing their data. The company's Business Intelligence (BI) teams were heavily dependent on IT teams for reporting and analytics. The process of data retrieval was time-consuming and repetitive, often taking days to deliver the requested data. The company's data sources were heterogeneous and scattered, making it difficult for the BI teams to access the data on demand. The challenge was to find a solution that could clean, consolidate, and centralize these data sources for easy and immediate access by BI teams globally. Read More
About Customer	BlaBlaCar is a pioneering company that launched the world's first online carpooling booking service. This innovative approach transformed carpooling into a viable means of transportation. The company has experienced rapid growth, boasting over 10 million members and operations in 13 countries. It continues to expand at a rate of 200% per year. BlaBlaCar operates in the online car sharing platform industry, primarily in the European and Indian markets. The company's primary use case for data science is Lifetime Value Optimization (CRM). Read More
Solution	BlaBlaCar adopted Data Science Studio to automate the cleansing and centralization of data for global on-demand access. A developer and a BI Data Manager built a stream that automatically retrieves data from various sources, including SQL databases, social network data, user reviews, and partner logs. The data was then aggregated and stored in a Vertica database, optimized for analytical calculations and complex queries in Big Data environments. This solution allowed business, marketing, and BI teams to build and view reports without regenerating complex and expensive queries on SQL databases. The BI teams used Tableau Software, connected to the Vertica database, to create visualizations of the data. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Infrastructure as a Service (IaaS) - Cloud Databases

Applicable Industries

Cement

Transportation

Applicable Functions

Logistics & Transportation

Sales & Marketing

Use Cases

Demand Planning & Forecasting

Last Mile Delivery

Services

Data Science Services

Challenge

BlaBlaCar, the world's first online carpooling booking service, faced a significant challenge in accessing and utilizing their data. The company's Business Intelligence (BI) teams were heavily dependent on IT teams for reporting and analytics. The process of data retrieval was time-consuming and repetitive, often taking days to deliver the requested data. The company's data sources were heterogeneous and scattered, making it difficult for the BI teams to access the data on demand. The challenge was to find a solution that could clean, consolidate, and centralize these data sources for easy and immediate access by BI teams globally.

About Customer

BlaBlaCar is a pioneering company that launched the world's first online carpooling booking service. This innovative approach transformed carpooling into a viable means of transportation. The company has experienced rapid growth, boasting over 10 million members and operations in 13 countries. It continues to expand at a rate of 200% per year. BlaBlaCar operates in the online car sharing platform industry, primarily in the European and Indian markets. The company's primary use case for data science is Lifetime Value Optimization (CRM).

Solution

BlaBlaCar adopted Data Science Studio to automate the cleansing and centralization of data for global on-demand access. A developer and a BI Data Manager built a stream that automatically retrieves data from various sources, including SQL databases, social network data, user reviews, and partner logs. The data was then aggregated and stored in a Vertica database, optimized for analytical calculations and complex queries in Big Data environments. This solution allowed business, marketing, and BI teams to build and view reports without regenerating complex and expensive queries on SQL databases. The BI teams used Tableau Software, connected to the Vertica database, to create visualizations of the data.

Impact #1	The implementation of Data Science Studio has had a significant impact on BlaBlaCar's business operations. The BI teams around the world can now easily collect and use performance indicators on demand. The automated cleansing and centralization of data have led to a huge increase in BI productivity and a decrease in delivery time. The ability to quickly and accurately generate BI reports has translated into optimized conversion rates and improved retention. The solution has also fostered collaboration among the entire data team, making automated queries and data centralization easier.

Impact #1

The implementation of Data Science Studio has had a significant impact on BlaBlaCar's business operations. The BI teams around the world can now easily collect and use performance indicators on demand. The automated cleansing and centralization of data have led to a huge increase in BI productivity and a decrease in delivery time. The ability to quickly and accurately generate BI reports has translated into optimized conversion rates and improved retention. The solution has also fostered collaboration among the entire data team, making automated queries and data centralization easier.

Benefit #1	Significant increase in BI productivity
Benefit #2	Substantial decrease in data delivery time
Benefit #3	Optimized conversion rates

Benefit #1

Significant increase in BI productivity

Benefit #2

Substantial decrease in data delivery time

Benefit #3

Optimized conversion rates

Download PDF Version

Overview

Lifetime Value Optimization through Data Centralization: A BlaBlaCar Case Study

Operational Impact

Quantitative Benefit