Client Marketing

Client Marketing relies on data and AI to strengthen customer relationships, maximize retention, and optimize the customer experience throughout their journey. Missions include analyzing customer behavior, personalizing interactions, managing loyalty programs, and optimizing retention and engagement strategies.

Core Responsibilities

a. Data Governance and Collection for Customer Insights

• Data Centralization
  • Collect, clean, and structure data from CRMs (Salesforce, HubSpot, Microsoft Dynamics), loyalty platforms, customer interactions (emails, chats, calls), transactions, and external sources (social media, satisfaction surveys).
• Key Performance Indicators (KPIs)
  • Define and track customer KPIs (e.g., retention rate, Customer Lifetime Value (CLV), Net Promoter Score (NPS), engagement rate, purchase frequency).

b. Reporting and Visualization for Decision-Making

• Dashboard Design
  • Create visualization tools (Power BI, Tableau, Google Data Studio, Python) to monitor customer relationship health, loyalty trends, and improvement opportunities in real time.
• Automated Reporting
  • Use AI to generate reports on customer satisfaction, recurring purchase behaviors, and disengagement risks.

c. Modeling and Optimization of Customer Experience

• Model Development
  • Explanatory Models: Analyze factors influencing customer satisfaction, loyalty, or attrition (e.g., customer journey, touchpoints, complaints).
  • Predictive Models: Anticipate churn risks, future customer needs, or upsell/cross-sell opportunities.
  • Prescriptive Models: Recommend actions to personalize offers, improve customer experience, or enhance loyalty programs.
• AI and Machine Learning Applications
  • Dynamic customer segmentation based on value and behavior.
  • Real-time personalization of communications (emails, notifications, offers).
  • Automation of loyalty programs and behavior-based rewards.
  • Analysis of customer feedback (NLP) to identify improvement areas.

d. Cross-Functional Collaboration and Digital Transformation

• Interface with Business Teams
  • Work with marketing, customer service, sales, and product teams to integrate data insights into customer relationship strategies.
• Technological and Regulatory Watch
  • Monitor innovations in Customer Data Platforms (CDP), Customer Experience Management (CXM) tools, and regulations (e.g., GDPR, data protection laws).
• Change Management
  • Train teams to use data/AI tools and promote a customer-centric culture.

Concrete Project Examples

• Churn Reduction
  • Develop a predictive model to identify at-risk customers and implement targeted actions (e.g., personalized offers, proactive support), reducing churn by 15%.
• Loyalty Program Personalization
  • Use machine learning to tailor rewards based on customer behavior and preferences, increasing engagement by 25%.
• Onboarding Optimization
  • Automate communications and offers during the onboarding phase to improve retention of new customers.
• Customer Feedback Analysis
  • Deploy an NLP tool to analyze reviews and complaints, identifying priority areas for product service improvement.