Master of Science Data Analytics & Marketing Manager

The business game is played using a business simulator. Groups of students are responsible for running a business in real time. All major business functions are covered. Students will make decisions to maximize the profitability of the business.

• CV writing, recruitment interview techniques for the search for an internship, professional project management, team management and meeting management.
• Negotiation techniques, transactional analysis and NLP, speaking and stage fright management, management and leadership techniques (PRADITUS).
• Skills assessment, coaching, digitalisation of the CV and job search techniques at national and international level, preparation for the oral presentation of the applied research thesis.

Presentation of the professions in the sector by professionals.

The objective is to acquire key skills in terms of budget management and reporting. The focus will be on budget architecture, with the implementation of summary documents, project management control and its link with budget management, and the creation and steering of performance indicators.

The objective of this module is to learn how to draw up a business plan: Designing a costed project for the creation or development of a company.

Several steps are covered: feasibility study, market targeting, opportunities and risks, strengths and weaknesses, communication, financing plan and profitability.

A precise methodology for analyzing customer needs, market structure and competitor dynamics to identify opportunities and threats in the environment is presented.

This seminar focuses on a negotiation in a national and international context.

In particular, it will be necessary to take into account the cultural dimension and define its impact in an international negotiation. The national negotiation will focus on the sales process through role playing.

To perfect English language comprehension and communication skills in a wider context than just business English. Students are required to take the TOEIC test.

This module aims to deepen students’ skills in IT to meet the needs of companies in terms of budgetary or commercial monitoring, project management, personnel management and communication: Excel, Word, Powerpoint, teamwork tools, business software.

It aims to be efficient with office automation tools, identify and correct errors quickly, customize existing tools or create your own tools.

The business game is played using a business simulator. Groups of students are responsible for running a business in real time. All major business functions are covered. Students will make decisions to maximize the profitability of the business.

What makes a successful business person?

Internal and external communication skill; managing your priorities and deadlines; organization and time management skills; how to be a great listener, writer and speaker; effective sales techniques; effective group dynamics and project management skills; understanding international business culture.

Through case studies, this module aims to master the tools of marketing and communication on the Internet, mainly by addressing :

– The latest trends in e-commerce (m-commerce / f-commerce …).

– The integration of Web 2.0 in marketing strategies.

– Presentation and mastery of Web analytics tools.

– Development of a marketing and sales strategy on the various social media.

Define and implement a digital communication strategy to optimize interactions between different channels (advertising, blog, advert gaming, social networks, content sharing…).

Implementing digital solutions that are integrated into global communication and generate value.

Overview of website creation solutions (CMS, PHP development, WYSIWYG tools…).

Presentation of the different analysis tools, of the frequentation of a website, main indicators: origins, conversion rate, time spent…

Knowledge and mastery of the main social media, uses and best practices by companies. Presentation of the different analysis and monitoring tools, adaptation of the message to the company’s strategy (positioning, targeting, key performance indicators and evaluation).

The objectives of this course are to present a panorama of statistical methodologies and data visualization methods in order to be able to describe in a synthetic way and to bring out the information of data sets. The data are composed of one or more quantitative variables and/or one or more qualitative variables, measured on the same sample of individuals.

The following topics will be covered: descriptive statistics, data analysis, classification of individuals or variables, inferential statistics.

The theoretical aspects of the approaches and methodologies presented will be briefly addressed and discussed. These statistical approaches and methodologies will be illustrated on practical cases and implemented on the statistical software R.

The objective of this course is to give an overview of the Big Data ecosystem and how these technologies can help achieve new goals through new data analysis techniques, by providing a fundamental introduction to the main components of all new data-related technologies and their use cases in various fields

The programming languages R and Python will be presented and implemented in order to understand their interest from a managerial point of view and thus be able to choose the most relevant analysis methods.

CV writing, recruitment interview techniques for the search for an internship, professional project management, team management and meeting management.

Negotiation techniques, transactional analysis and NLP, speaking and stage fright management, management and leadership techniques (PRADITUS)

Skills assessment, coaching, digitalisation of the CV and job search techniques at national and international level, preparation for the oral presentation of the applied research thesis.

LinkedIn workshops.

Software (Excel, Word, VBA, professional software).

Presentation of the professions in the sector by professionals.

From large amounts of data, coming from very diverse sources, deduce regular or potential behaviors, through modern techniques of targeting, segmentation and scoring of e-consumers. Master real-time behavioral analysis to promote multi-channel promotions and influence consumer behavior directly at the point of sale (or on the website).

Digital technology allows us to obtain a colossal amount of information on individuals. However, without immediate processing, this data quickly becomes obsolete. To know the sources of information available to the Marketer to accurately describe the situation or the desires of his customers and prospects in real time.

Analyze large volumes of data at the right time to evaluate data from new sources, such as traffic from social media or clicks made by a prospect on a company’s website, making targeting and segmentation of profiles as accurate as possible. Know the consumer’s position in real time. Use the right tools to collect and use this information. Study analysis and implementation simulation models. Analyze the consumer’s frequentation or purchase behavior in order to optimize the decision making process.

Analysis of study data: descriptive, explanatory or predictive analyses of simple or complex treatments. Text Analytics and CRM: understanding the possibilities offered by text analytics tools to understand data with a high degree of automation.

Improve the quality of the database (homogeneity, qualification, management of inactive contacts, etc.).

Determine the value of customers and prospects by developing business-specific scores based on all available data. Develop an acquisition or loyalty strategy according to the defined objectives. Use scoring to better target, avoid SPAM complaints, email churn, and manage marketing pressure in real time. Beyond targeting, the real added value of data also lies in the predictability of consumer behaviour. Predicting future customer behaviour. Identify the most profitable, the most influential.

Monitor and analyze online data that is most relevant to the business. Identify the right information at the right time and in the right place to improve decision making and optimize organizational performance.

Choose the appropriate tools to understand and capitalize on this new reality. Anticipate changes in markets and customer behaviour. Data Mining applied to Customer intelligence. Implement a customer intelligence project in a company.

Putting the consumer and the shopper back at the centre of our thinking, in order to optimise decision-making and the relevance of the actions to be implemented. Analyze, segment and manage customers more effectively (consumer insights) to create tailored loyalty programs. Influencing strategic business decisions through knowledge of consumer expectations and needs (Consumer Insight), markets, brands and customers (Shopper Insight).

Marketing research is becoming more operational and strategic at the same time.

To know the main phases of the design of a website.

Master the international regulatory environment of data management, both in the context of collection and sharing. Identify the different approaches to personal data protection. The consent of individuals to their personal data. Integrate the rapid changes in legislation at the state level and their impact on the use and strategies of tomorrow’s companies.

Use anonymous data with a scoring system to combine predictive analysis on user behaviour. Master the technique of online advertising to engage visitors who have left a website to accomplish several types of objectives. Increase the conversion rate. The benefits of retargeting. Implementation of a retargeting campaign. Adapt a PRM (Partner Relationship Management) and CRM (Customer Relationship Management) strategy to intentional prospects and personalise communications according to their browsing habits.

Know the basic tools of data analysis. Explore, describe and interpret data in its multidimensional aspect. Ask the right statistical questions in relation to a marketing problem. Carry out simple statistical processing in order to make marketing recommendations.

Algorithm issues in the value chain of companies. Algorithms now allow machines to learn to detect patterns among millions of data: search for groups of similar elements. Forecasting a sequence. Prediction of a continuous attribute.

To process large quantities of comments left by users or messages exchanged on social networks, text analysis techniques have emerged.

Understanding how these tools work allows the data marketer to understand text data with a high degree of automation.

Communicating about massive data involves in-depth work on advanced tools and representation methods. To represent study data in a multidimensional way in order to highlight phenomena that are not visible through numbers, and by highlighting the relationships that exist between different study variables.

The Data Marketer must master the trends in order to guide the creatives in the production of syntheses by putting the user experience at the center of his practice. Finalizing a presentation for a client or modeling the result of a data processing requires basic knowledge of DTP. Introduction to narrative data representation.

To know the various solutions available on the market in order to optimize the choices of heavy investments generated by the Big Data: benchmarking of the services, knowledge of the tariffs, clauses and sources to keep up to date. Overview of the technologies that are revolutionizing daily life and customer relations (RFID – Radio Frequency Identification, NFC – Near Field Communication). To know the information transmitted in mass in order to build new strategies.

Overview of the different types of data. Unstructured or semi-structured data, public data or data contained in the cloud (online storage), whether it be social network interactions, videos, Excel files or email attachments. Development and administration of massive databases. Knowledge of the tools behind the great advances in massive data management. Understanding of the basic technological architecture in order to anticipate investments. Hadoop, Map Reduce, NoSQL tools. Consolidate and reconcile data for optimal marketing ROI.

Data is a new source of value for the companies that collect it. Assessing the value of databases in a file buying and selling context: finding a market, assessing selling prices and the costs of buying and storing databases.

Valuing and monetizing data and supporting the company in the strategic choices that this implies. Anticipate the evolution of the data market in a perspective of disruption of the business model.

Impact of Big Data on the transformation of business models of “consumer centric” companies at all levels of the organization: production, logistics, finance, marketing, etc. Consequences of Big Data on siloed organizations and transformation of decision processes. Need to strengthen the bridges between IT and marketing.

Organization and deployment of the CDO (Chief Data Officer) function in companies.

Whether it is an Agile environment or a more traditional structure, implement a fine management of projects and teams. Taking into account the impact of the techniques used and the measurement of the return on investment in the management of such projects. Define and negotiate cost, quality and deadline objectives. Break down a project and set up a concurrent engineering. Organize a project. Define responsibilities and tasks. To steer a project and manage human and financial resources. Accompany the change. Set up a Data Management Platform.