marketing Automation & Lead Management

Introduction

• Introduction of marketing automation and modern lead management.
• Changes in the customer journey and the impact of AI on the purchasing process.
• Cooperation marketing- sales alignment.

• The Three Types of AI in Marketing Automation:

  • Analytical AI (scoring & forecasting),
  • generative AI (content & personalization), 
  • Agent-based AI (autonomously controlling workflows).

• Determine the AI maturity level of your marketing automation and define the next phase of expansion. 

Inventory/analysis

• Your challenges.
• Customer and market structures.
• Target scenarios: Leads, cross-selling and up-selling sales, etc.
• AI-powered data and potential analysis: Identify patterns in existing data and determine campaign priorities. 

Strategy canvas marketing automation/lead management

• Digitalization in marketing and sales.
• Combination of inbound marketing and outbound activities.

Customer profiling:

• Target Customer Profiling and In-Depth Buyer Persona Profiles.
• Customer journey analysis.
• AI-Driven Buyer Persona Research and Validation: Refining Assumptions with AI and Testing Them Against Real Customers 

Automated Development Processes (The Engine Room)

• Automated lead/customer processes (nurturing).
• Qualification of customers in the automation process - lead scoring.
• Profile building using progressive profiling and intent data.
• Lead routing: transfer of leads to the sales department.
• Optimal lead/customer support in sales.
• Predictive Lead Scoring with AI: Automatically prioritize leads based on purchase likelihood and intent signals.

• Next Best Action: AI recommends the appropriate next step in the nurturing process for each contact. 

AI in Marketing Automation 

• Applications of AI in automation workflows. 
• AI-powered scoring, hyper-personalization, and content creation. 
• Real-time hyper-personalization: Dynamically tailor content based on segment and behavior. 

Measure and optimize

• AI-powered analysis and reporting: Aggregate campaign and funnel data, identify patterns, and derive actionable insights. 
• AI-Powered Early Churn Warning: Detect signs of customer churn early and take automated countermeasures. 

Implementation

• Interaction and integration of systems: marketing automation, CRM, CDP, etc.
• Building a scalable revenue engine. 
• Tips for implementation in practice. 
• AI-powered lead summaries for a seamless handoff to sales