About Clément
- Oral presentation of results with associatedrecommendationsto meet client needs
- Data manipulation thanks to my knowledge of SQL and Python
- **In-depth statistical analyses**: segmentation, predictive models, A/B tests
- Conducting quantitative studies: design, programming, fieldwork, processing
- **Project management**: collaboration, creation and monitoring of the schedule, coordination
French
Native or bilingual
English
Fluent
Spanish
Fluent
Italian
Basic
Experience
- Projets de formation ou personnelsData Analysis ProjectsCONSULTING AND AUDITSJune 2024 - Today (2 years)To be viewed in my portfolio: https://clemfouchier.github.io/E-commerce Datavisualization: analyzing website data
- Datavisualization of 2 million data points from products ordered in the online grocery store The Hunter Grocery
- Recommendations to improve loyalty through an optimized experience.
- Tools: combined use of SQL (database creation & exploration) and PowerBI (data integration, transformations, modeling, DAX measure creation, and interactive dashboard development).
Banking Marketing: improving the effectiveness of a direct marketing campaign- Exploratory data analysis and initial insights
- Development of a predictive model to assess the likelihood of subscribing to a financial product. A score to be integrated into the CRM.
- Creation of clusters to identify 5 typical customer profiles, which sales representatives will use to personalize sales pitches.
- Tools: Python (Pandas, Plotly, Scikit-learn) and presentation of results via Streamlit
Campaign A/B testing: proving the success of promotional campaigns- A test was conducted by a fast-food brand to determine which of the 3 versions of a promotion was most effective.
- 2 versions generated 20% more revenue than the 3rd.
- Statistically validated results through Kruskal-Wallis and Tukey tests.
- Tools: Python (Pandas, Seaborn, Statsmodel)
Social Media & Emotions- Self-service data from a survey of 20-36 year olds worldwide from February to May 2024.
- Exploratory data analysis and implementation of a predictive model to predict emotions felt based on the social media used.
- Clustering that clearly distinguishes between 5 very different user profiles.
- Recommendations on communications based on the social media activated.
- Tools: Python (Pandas, Seaborn, Scikit-learn)
- iligoSENIOR MARKET RESEARCH CONSULTANTMarch 2019 - December 2023 (4 years and 10 months)Paris, Franceiligo is aresearch and consulting agencydedicated to understanding consumer behavior and **measuring marketing levers**, recognized for its culture of **innovation**.Sectors: media/communication, retail media, transport, insurance.Quantitative studies from A to Z
- Data analysis, visualization, and recommendations to meet client needs and presentation of results using the storytelling method
- Frequent studies: marketing campaign evaluations to track key KPIs related to brand communication, audience studies, transport usage studies, ad-hoc studies.
- Survey management: survey programming and fieldwork management to ensure usable data.
- Data processing, ensuring quality and consistency (Excel then the Askia Suite)
- Use of innovative technologies such as Eye-tracking.
Client and Project Manager- Client relationship management, 80% of whom are advertising agencies in transport, media, and retail.
- Project management: defining the appropriate methodology, questionnaire, budget, and schedule, managing suppliers, collaborating internally and with clients.
Communication- Conducting and supervising studies on trending topics in marketing and communication
- Writing and sending press releases
- Publications on the website and social media with monthly statistical monitoring via Google Analytics
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Education
- Data AnalyseDataScientest (certification Les Mines Paris)2024- Python pour nettoyer, préparer, s’assurer de la qualité des données et automatiser les tâches (librairies Pandas et NumPy) - Gestion des bases de données et requêtes (SQL) - Business Intelligence, dashboards/rapports interactifs (Power BI et Tableau) - Datavisualisation avec Matplotlib, Seaborn et Plotly - Mise en place de modèles de Machine Learning (scikit-learn) - Réduction de dimension et clustering (ACP, TSNE, Kmeans) - Text mining et webscrapping (Beautiful Soup, Selenium)
- (M2) - MARKETINGMontpellier Business School2019