Digital Marketing

Modern digital marketing relies on data and AI to optimize campaigns, personalize customer experiences, and maximize return on investment (ROI). Missions include analyzing customer behavior, automating campaigns, optimizing digital channels, and measuring the effectiveness of marketing actions.

Core Responsibilities

a. Data Governance and Collection for Marketing

• Data Centralization

  • Collect, clean, and structure data from analytics tools (Google Analytics, Adobe Analytics), advertising platforms (Google Ads, Meta Ads, LinkedIn Ads), CRMs (Salesforce, HubSpot), and external sources (social media, emails, websites).

• Key Performance Indicators (KPIs)

  • Define and track marketing KPIs (e.g., conversion rate, cost per acquisition, advertising ROI, customer engagement, lifetime value).

b. Reporting and Visualization for Decision-Making

• Dashboard Design

  • Create visualization tools (Power BI, Tableau, Google Data Studio, Python) to monitor campaign and digital channel performance in real time.

• Automated Reporting

  • Use AI to generate reports on marketing performance, trends, and optimization opportunities.

c. Modeling and Optimization of Marketing Campaigns

• Model Development

  • Explanatory Models: Analyze factors influencing customer behavior (e.g., purchase journey, content interactions).

  • Predictive Models: Anticipate market trends, future purchasing behaviors, or churn rates.

  • Prescriptive Models: Recommend actions to optimize budgets, target audiences, or personalize messages.

• AI and Machine Learning Applications

  • Advanced audience segmentation for targeted campaigns.

  • Real-time automatic optimization of advertising bids.

  • Generation of personalized content (e.g., emails, dynamic ads) using generative AI.

  • Sentiment and trend analysis on social media.

d. Cross-Functional Collaboration and Digital Transformation

• Interface with Business Teams

  • Work with marketing, sales, product, and design teams to integrate data insights into communication and sales strategies.

• Technological and Regulatory Watch

  • Monitor innovations in martech (e.g., CDP, DMP, marketing automation tools) and regulations (e.g., GDPR, data protection laws).

• Change Management

  • Train teams to use data/AI tools and promote a data-driven culture.

Concrete Project Examples

• Campaign Personalization

  • Use machine learning to segment audiences and personalize messages, increasing conversion rates by 20%.

• Advertising Budget Optimization

  • Develop a predictive model to automatically allocate budgets across channels (Google Ads, Meta Ads, LinkedIn Ads) based on ROI.

• Email Automation

  • Implement an AI system to send personalized emails based on user behavior, improving engagement by 30%.

• Sentiment Analysis

  • Deploy an NLP tool to analyze customer reviews and social media mentions, identifying product improvement opportunities.