Advanced Sales & Marketing Analytics Training — Customer Analytics, MMM, and Decision Agents

Train sales finance, marketing analytics, and RevOps teams to run the customer, MMM, churn, and next-best-action systems they own.

Advanced training in customer analytics, segmentation, churn modeling, marketing mix modeling, attribution, and the AI decision systems that run on top of them. Built for mid-market sales finance, marketing analytics, and RevOps teams.

Overview

This 3-day comprehensive program offers a deep dive into advanced sales and customer analytics, predictive modeling, and marketing optimization techniques. With practical, hands-on training in R and Python, participants will learn to harness data for strategic decision-making and growth

Target Market

Marketing, Sales Ops, Pricing, Revenue Management, and Commercial Finance team members (Analyst to Director).
Business Analysts and Data Scientists who are aligned with Sales, Marketing, Pricing, Finance, or Supply Chain domains.

Learning Outcomes

By the end of this course, participants will be able to:

Master complex techniques in Customer Segmentation, Customer Churn Modeling, Cross-Sell Optimization, and Customer Lifetime Value (CLV) Modeling.
Leverage Machine Learning for advanced Sales and Customer Analytics.
Understand and apply sophisticated Marketing Analytics methodologies, including Marketing Mix Modeling, Knowledge Graphs, and Multi-Touch Attribution.
Conduct customer lookalike modeling to identify new opportunities and revenue streams.
Gain hands-on experience with R and Python for cutting-edge customer and marketing analytics and predictive modeling.

Training Agenda

DAY 1

Session 1: Advanced Techniques in Customer Churn Modeling & Sales Optimization (3 hours)

Advanced Customer Churn Modeling Techniques
Implementing Customer Up-Sell and Cross-Sell Optimization Strategies
Hands-on labs with R and Python Case Study: Driving Organic Growth through Proactive Churn Management

Session 2: Mastering Customer Lifetime Value (CLV) Modeling (2 hours)

Advanced CLV Modeling Techniques
Practical Applications of CLV Models
Case Study: Making Smarter Sales & Marketing Decisions with Predictive CLV

Session 3: Customer Lookalike Modeling (3 hours)

Foundations of Lookalike Models
Machine Learning methods with examples in R and Python
Case Study: The benefits of owning your marketing audience

DAY 2

Session 1: RFM Analysis (2 hours)

Understanding RFM Analysis
Implementing RFM Analysis for Customer Engagement and Marketing
Hands-on Labs in R and Python
Case Study: Leveraging RFM Analysis for Better Customer Experience and Increased Revenues

Session 2: Marketing Mix Modeling (4 hours)

Introduction to Marketing Mix Modeling (MMM)
From Foundational to Advanced Methods in MMM Frequentist and Bayesian Modeling approaches
Hands-on Labs with R and Python
- Case Study: Marketing Budget Optimization with MMM

DAY 3

Session 1: Knowledge Graphs and Multi-Touch Attribution Modeling (4 hours)

Introduction to Multi-Touch Attribution (MTA)
From Foundational to Advanced Methods in MTA
Introduction to Marketing Knowledge Graphs
Hands-on Labs:
- - Multi-Touch Attribution with Python
  - Marketing KnowledgeGraph demo with Neo4j

Session 2: Case Study and Group Discussion (2 hours)

Detailed review of a real-world case study for Advanced Sales & Customer Analytics
Group discussion to brainstorm strategies and solutions for your company
Developing a mock action plan on building enhanced Sales & Customer Analytics capabilities in-house
Developing a mock action plan on building enhanced Sales & Customer
Analytics capabilities in-house

About Your Instructors

Armin founded Revology Analytics, bringing extensive expertise in advanced analytics and Revenue Growth Management. With over 15 years of experience in B2C and B2B Revenue Growth Analytics, he has a distinguished record of developing in-house commercial analytics capabilities across several industries as an advanced practitioner, executive, and expert advisor.

As former Vice President, Head of Advanced Analytics Commercialization at a leading consumer durables distributor in North America, Armin co-founded an analytics subsidiary, providing SaaS solutions and introducing new revenue streams through data monetization. Before this role, he led Revenue Growth Management and Pricing Science teams in CPG and Retail.

At Revology Analytics, Armin specializes in guiding businesses to independently implement analytics and machine learning solutions to optimize Revenue and Profit growth and reduce dependency on external vendors for this core competency.

He earned his MBA from the University of Virginia in Decision Analytics, with postgraduate studies in Artificial Intelligence and Machine Learning at MIT and the University of Washington. He stays actively involved with the analytics community, running a widely-read Commercial Analytics newsletter and regularly conducting insightful webinars on topics related to Revenue Growth Analytics.

Rudy is the co-founder of Reliancy and Clarity Data Insights, a leading AI/ML solutions firm for Sales & Marketing Enablement.

He is a recognized expert in AI and Machine Learning (including AI & Industry 4.0 Tech), named a 2021 “Key Opinion Leader” by Onalytica.

Rudy has a successful track record of architecting and deploying AI/ML solutions for Sales & Customer Growth projects across various industries, including mid- and large-cap Retail, Industrials, CPG, Healthcare and SaaS.

Specifically, his expertise is in augmenting Sales and Marketing capabilities with AI, including advanced Customer Journey and Path Analytics and incorporating domain-specific, client-side LLMs into Sales and Marketing analytics solutions.

Rudy holds a PhD from the University of Minnesota and has published extensively in top-tier conferences on AI and machine learning.

Advanced Sales & Marketing Analytics Training — Customer Analytics, MMM, and Decision Agents

Overview

Learning Outcomes

Training Agenda

About Your Instructors

Armin Kakas

Rudy Agovic, PhD

Who We Are

Advisory Services

Insights

Tools

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