AI Case Study
BlaBlaCar optimises conversion rate and improves retention with machine learning predictive analytics that integrate data from multitudes of sources
BlaBlaCar leveraged Dataiku Data Science Studio, which provides analytics solution allowing users to connect to a wide range of data to build predictive models. The company is aimed at increasing its business intelligence productivity and develop a better understanding and grasp on data lead, which led to improvement in retention and conversion rates.
"Automatic cleansing and centralisation of data for global on- demand access:
With Data Science Studio, one developer and one BI Data Manager were able to build a stream that automatically retrieves data from multitudes of sources (SQL databases, external data such as social network data, user reviews, partner logs...), aggregates it, and stores it in a Vertica database optimized for analytical calculations and complex queries in Big Data environments.
Subsequently, business, marketing, and BI teams can build and view reports without regenerating complex and expensive queries on SQL databases. The BI teams use Tableau Software, which is connected to the Vertica database, to create visualizations of the data."
BlaBlaCar states the following results:
* BI teams around the world easily collect & use performance indicators on demand
* Huge increase in BI productivity
* Decrease in delivery time
* Quick and accurate BI reports translate into optimized conversion rates and improved retention
"Dataiku Data Science Studio (DSS) is a powerful predictive analytics solution that allows users to connect to a wide variety of data, quickly clean that data (in the GUI or with code), and enables them to creatively factor-in datasets to create predictive models. These models can be configured and tweaked, as needed, in order to visualize your own unique business scenarios. The analytics process uses a rich machine learning interface to empower your company to build predictive services based on past and incoming data."
"Business intelligence (BI) teams are dependent on technicians for reporting & analytics:
When BlaBlaCar’s BI teams need to access data, their queries depended on IT teams. IT teams have to generate repetitive and time-consuming queries to deliver requested data. The process between request and delivery of data can take days.
BlaBlaCar wants a solution that can help them clean, consolidate, and then centralize heterogeneous data sources for on demand access by BI teams around the world.