Launchmetrics provides the First AI powered Brand Performance Cloud for Fashion, Lifestyle and Beauty (FLB) companies to make smarter decisions around their brand marketing efforts.
Our suite of SaaS leverages AI and data to help our customers plan, execute and measure brand marketing initiatives. With over a decade of industry expertise, we have helped more than 1,200 customers create inspiring, impactful and measurable experiences.
Founded in NYC and with operating headquarters in Paris, we have employees in ten markets worldwide. We have been the trusted brand performance technology to brands worldwide such as Dior, Fendi, Shiseido, NET A PORTER and Adidas as well as industry partners like IMG, the Council of Fashion Designers of America, the British Fashion Council, and Camera Nazionale Della Moda Italiana.
ABOUT THE ROLE
At Launchmetrics, our data is the backbone of our products and the core of the value we bring to our customers.
The Data Strategy team works on 3 main pillars :
* Exploring new data value propositions to drive business growth
* Developing our coverage methodology and roadmap to ensure the relevance of our data asset
* Defining our taxonomy and working on automating some of the enrichments to increase data quality and profitability
These pillars aim to provide the most qualitative and advanced insights to our customers through our offers and products. Combining Data Analysis skills and Industry Expertise, we explore and validate new methodologies that will leverage all the potential of our data asset for Brand Performance.
Reporting to the Data Strategy Manager, as Data Strategy Analyst, you will be a key contributor to our first pillar to explore our new data value propositions and make sure we can provide the most advanced insights tailored to FLB markets.
WHAT YOU WILL DO
Strategic analysis :
Conduct market watch and monitor industry trends to inform strategic decision making for our teams and help make sure we align with the unique requirements of Fashion, Lifestyle and Beauty brands.
Perform competitor analysis to understand their strategies and gain a deep understanding of the competitive landscape. This will include attending webinars, reading white papers and identifying their value proposition.
Exploration of new data value propositions :
Identification and scoping of new Data / Gen AI use cases : this will include doing some discovery and talking with our customers to understand their needs, running some ad hoc analysis to assess value.
For Gen AI use cases, craft and refine prompts to enrich our data. Define the right testing approach and confirm results quality.
Work closely with Data Scientists to define the right processes and ensure feasibility (technic wise, cost wise and process wise). Document this process for next steps.
Run some POC collaborating with the