Thinking
Writing at the frontier of CRM & Loyalty
Perspectives on loyalty economics, CRM maturity, CDP architecture, and AI in customer strategy.
Explore by Topic
Browse the core themes shaping this site: CRM leadership, MarTech and CDP strategy, CX with loyalty-led growth, and broader general perspectives.
CRM Leadership
Leadership lessons, operating models, lifecycle maturity, and team-building perspectives for CRM-led growth.
MarTech & CDP Strategy
Customer data, platform architecture, AI, and operational decisions behind modern customer technology ecosystems.
CX, Loyalty & Growth
Customer experience, loyalty economics, retention, and engagement strategies that build long-term commercial value.
General
Broader perspectives, essays, and adjacent ideas that inform customer strategy, leadership, and modern growth.
CRM Leadership
Leadership lessons, operating models, lifecycle maturity, and team-building perspectives for CRM-led growth.
Agentic AI in CRM: Real Innovation or Just a Rebrand?
“Agentic AI” is everywhere right now. But after years of working hands-on with CRM and Martech systems, one thing is clear: Most of what’s being labelled as agentic...
Read ArticleWhat I Look for When Hiring CRM Talent: Lessons from the Trenches
Hiring for CRM roles taught me one thing the hard way: Strength in one dimension is not enough. I’ve seen candidates who were deeply data-driven but couldn’t translate...
Read ArticleWhy CRM is No Longer a Marketing-Led Function?
CRM used to be about campaigns and communication. Today, it’s increasingly about data, systems, and infrastructure. Over the years, the role has quietly shifted from...
Read ArticleCRM Maturity: From Transactional to Predictive
A framework for evolving your CRM strategy from basic batch-and-blast emails to sophisticated, AI-driven predictive modeling that anticipates customer needs.
Read ArticleAI in CRM: Predictive Analytics for Customer Engagement
Practical applications of machine learning in lifecycle marketing, focusing on churn prediction, next-best-action modeling, and lifetime value optimization.
Read ArticleThe Power of Balance: Why Marketers Today Need Both Left and Right Brains
Marketing used to lean heavily on either numbers or creativity. Today, neither works in isolation. Data can tell you what is happening. Creativity defines how it is...
Read Article2-way APIs - The big small feature in Customer Engagement & Data Platforms
Most customer engagement platforms promise better personalisation and smarter communication. But none of that works without one thing: Clean, consistent, and connected...
Read ArticleMarTech & CDP Strategy
Customer data, platform architecture, AI, and operational decisions behind modern customer technology ecosystems.
When AI Model Quality Isn’t Enough: The Operational Cost of Usage Limits
Claude is often praised for its reasoning and writing quality, and rightly so. But after a month of consistent, real-world usage, one constraint stood out far more than...
Read ArticleAgentic AI in CRM: Real Innovation or Just a Rebrand?
“Agentic AI” is everywhere right now. But after years of working hands-on with CRM and Martech systems, one thing is clear: Most of what’s being labelled as agentic...
Read ArticleDo you really need AI in your CDP?
AI in CDPs sounds like a no-brainer. Better insights. Predictive models. Personalisation at scale. But here’s the uncomfortable question: Do you actually need it? If your...
Read Article"This is Not AI": Unmasking the Pretenders in Martech and Customer Tech
“AI-powered” has become the default label for almost every Martech product. But here’s the reality: Automation is not AI. Rules are not learning. A recommendation engine...
Read ArticleCustomer Data Strategy: Building a Customer 360
The architectural and organizational challenges of implementing a true Customer Data Platform across enterprise silos, and how to overcome them.
Read ArticleUnleashing the Power of Customer Insight: How a CDP Transforms Tech Architecture into a Customer-Centric Powerhouse
Customer-centricity is not built on campaigns. It is built on data. And more importantly, on how well that data is unified, structured, and made accessible across...
Read Article2-way APIs - The big small feature in Customer Engagement & Data Platforms
Most customer engagement platforms promise better personalisation and smarter communication. But none of that works without one thing: Clean, consistent, and connected...
Read ArticleCX, Loyalty & Growth
Customer experience, loyalty economics, retention, and engagement strategies that build long-term commercial value.
Why CRM is No Longer a Marketing-Led Function?
CRM used to be about campaigns and communication. Today, it’s increasingly about data, systems, and infrastructure. Over the years, the role has quietly shifted from...
Read ArticleLoyalty Economics: Building Sustainable Reward Models
Exploring how to balance customer perceived value with program liability to create loyalty programs that actually drive bottom-line growth rather than just discounting.
Read ArticleUnleashing the Power of Customer Insight: How a CDP Transforms Tech Architecture into a Customer-Centric Powerhouse
Customer-centricity is not built on campaigns. It is built on data. And more importantly, on how well that data is unified, structured, and made accessible across...
Read ArticleAI in CRM: Predictive Analytics for Customer Engagement
Practical applications of machine learning in lifecycle marketing, focusing on churn prediction, next-best-action modeling, and lifetime value optimization.
Read ArticleGeneral
Broader perspectives, essays, and adjacent ideas that inform customer strategy, leadership, and modern growth.
Research
Academic work at the edge of AI and CRM
Alongside executive practice, I have pursued rigorous academic research into how AI methods can be made more interpretable and actionable in customer-facing applications.
My MSc research at the University of Liverpool explores Explainable AI (XAI) in CRM — specifically, how SHAP and LIME techniques help practitioners trust, audit, and act on predictive churn and propensity models.
The goal: bridge the gap between data science output and marketing decision-making.
MSc Data Science & AI · University of Liverpool
Explainable AI in CRM: Interpretable Models for Customer Retention