Cargo: Information Systems
Tipo de posição: Permanent
Tipo de emprego: Full - Time
Local: FR - Ile De France
Data Product Manager
Performance at the core
L’Oréal 20-50-100 digital strategy is measured through a Digital Performance Cockpit, which outlines performance for the different facets of the business. 100% Love Brand – how the Group is performing on Owned site audiences, Share of organic and paid search, Share of Owned Social, Share of Earned Media. 50% Direct Relationship with Consumers : how we perform in the Precision Advertising space, from the quality of targeting to the ROI of campaigns, the productivity of our Identified Consumers Databases. 20% eCommerce : Growth vs. Market, Direct vs. Indirect growth, Channels performance, Share of e-Merchandising visibility, leading to Market share evolution.
Analytics Performance journey initiated
The first Digital Performance Cockpits have been launched in 2015 and share across the organization with Top 200 Executives exposed. The Digital Performance team supports 20+ Countries & 20+ Brands for their Top Management visits, with reports production, data analysis and strategic business recommendations. Cockpits automation has been kick-started in 2016, and the next step is to fully automatize the 20-50-100 Digital Performance measurement to allow integration in all business meetings, and allow Digital Performance team to focus on value-added business recommendations and coaching to enhance business performance across the organization, changing mindsets to “Data Driven Decision Making”.
Building the Marketing Data Factory
Digital Cockpit is now opened to 3500 users, targeting 5000 users in 12 months and transitioning from a Digital Cockpit to a Marketing Cockpit in the digital age.
Cockpit is the visible output of a Marketing Data Factory, processing data from raw inputs to business outputs, foundations being a sustainable & scalable platform, ensuring the following steps:
1) clear assessment of inputs raw data (sourcing / accuracy / quality)
2) alignment to internal master data management
3) set up of data injection & sustainability of storage (keep history)
4) data processing: development & ETL to deliver output datasets (from new sources or thru data crossing of existing sources) for cockpit product & for data science lab
5) creating output product: data visualization (out of the box & custom developments) adapted to roles & scope, offering self BI capabilities
6) monitoring tool usage & offering training to drive adoption
Data Factory is co-built by 3 sub-teams within the organization:
We are recruiting our Cockpit Product Manager to lead the existing Cockpit Product team
Cockpit Product Team management