Strategy & delivery / Selected essay
Why recommendations fail
(and what to do instead).
A good recommendation is a proposed change. What gives it somewhere to land?
Read the essayInsights / Jay Mandel
Question the promise.
Look at the evidence.
Writing on the gap between what organizations say and what people experience—and the decisions that can close it.
Explore the articles
A place to start
Thinking you can put to work.
Why recommendations fail
MarTech / Growth & Innovation
The cost of silence in marketing is too high
Read on MarTechMarketing Accountability Council / Data & AI
How Bad Math and Synthetic Empathy are Ruining Customer Service
Read on Marketing Accountability CouncilThe article library
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18 articles in Data & AI
MarTech · August 27, 2026
Better data starts with treating people like people
Treating people with respect improves the data relationships marketing depends on.
MAC · August 14, 2026
Howard Stern, Data Brokers, and the Danger of Mistaking a Profile for a Person
I’ve been listening to Howard Stern for most of my life.
MAC · July 31, 2026
How Bad Math and Synthetic Empathy are Ruining Customer Service
Customer service is deteriorating not because AI is inherently evil, but because corporate executives are using AI to turbocharge an obsolete, extractive financial model.
MAC · July 13, 2026
What Used to Be True About Finding a Fair Apartment Is Now a RealPage Algorithm
When we dropped our pieces on the ticketing and travel monopolies, a clear psychological profile emerged.
MAC · July 6, 2026
How gig platforms and data brokers run the same broken playbook — and what a positive-sum version looks like
Modern platforms like Uber Eats prioritize instant gratification, delivering items swiftly, boosting metrics like conversion rates and reducing costs.
MarTech · June 24, 2026
Why trust belongs at the center of your data strategy
More customer data once looked like an advantage. AI is exposing the risk of data built on inference, opacity and extraction.
MAC · May 25, 2026
The Illusion of the Holiday Discount
Don't Trust the Brand, Trust the Data
MAC · May 25, 2026
Is That AI Barbecuing Your Burgers?
Happy Memorial Day! It’s the unofficial start of summer.
MAC · May 21, 2026
Why Asking the Right Questions Transforms Marketing Accountability
A grocery receipt became the catalyst for a data analysis that reveals the hidden tax of geography on consumer spending.
MAC · April 28, 2026
Beyond the Prompt: Why Your AI Content Needs a Context Engine
Lashay Lewis on bridging the "Trust Gap" by grounding LLMs in your proprietary Product Truth.
MAC · February 11, 2026
Karma Has an API Key: How AI Is Eating SaaS
B2B SaaS spent years chasing “efficiency” by cutting humans out of the equation. Now AI is doing to software what software once did to everything else.
MarTech · January 12, 2026
The myth of brand community in the age of data agency
Clean metrics stop masking the gap between engagement and real commitment.
MAC · January 7, 2026
AI Has a PR Problem
The backlash against AI is a mirror, reflecting how far marketing has drifted from storytelling, empathy, and serving real human needs and why audiences are finally pushing back.
MarTech · December 3, 2025
How dirty data broke marketing
Clean data restores context, consent and meaning.
MarTech · October 28, 2025
Rethinking marketing’s relationship with data
Clean data offers a route back to trust.
CDA · August 14, 2025
Welcome to the Clean Data Alliance
Why dirty data is a business and social failure—and why people need more control over the information used to describe and decide for them.
MarTech · January 21, 2025
Are AI tools shaping your intentions more than you realize?
How AI tools influence the intentions behind your choices.
MarTech · December 30, 2024
Lessons from AI’s 2024 rise and a pragmatic path for marketing in 2025
A practical approach to using AI in marketing.
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The book / Kogan Page · 2023
Brand Strategy
in Three Steps.
Identity. Intention. Implementation. A framework for connecting your values, your offer, and the way you deliver.
Explore the book and sample chapterKeep exploring
From reading to doing
Bring your question
into the room.
Tell me what you are working through. We can decide together what needs to happen next.