AI Won’t Replace Your Creativity. But Marketers Who Use It Well Will Replace You.
The B2B marketer’s practical guide to working with AI, not around it.
Using AI to Build and Refine Customer Personas
A customer persona is a semi-fictional profile of your ideal buyer, built from a mix of demographics, behaviors, motivations, and pain points. Traditionally, these personas were assembled through interviews, surveys, …
AI is Changing the Rules of Paid Media in 2026
The role of a paid media manager in 2026 isn’t about clicking around in campaign dashboards. The skills that matter now are understanding what signals to feed the system, building creative testing pipelines, owning first-party data strategy, and knowing how to interpret why the AI made the decisions it did.
Using AI for Customer Sentiment Analysis: Tuning Into the “Vibe” of Your Customer Base
Sentiment Analysis, also known as opinion mining, is a specialized branch of Natural Language Processing (NLP) that focuses on identifying, extracting, and quantifying the emotional states expressed in digital text. …
The Infinite Content Graveyard: Why More AI Output Is Killing Your Marketing Strategy
Every marketer is producing more content than ever. Most of it is going nowhere. Here’s why human strategy is the only way out.
Using E-E-A-T to Optimize AI Assisted Content
The rush to integrate AI into everyday marketing workflows has left many teams wrestling with a critical challenge: how to scale production without sacrificing the distinct brand voice that actually …
AI Tools: Replacing vs. Augmenting Marketers
Discover an honest look at what AI can and can’t do and what tomorrow’s marketing team actually looks like.
Using AI to Identify Content Gaps and Own Your Niche
For digital marketers, staying ahead means knowing exactly what your rivals are saying, and more importantly what they’re not saying. AI-driven competitor content auditing is the process of using large …
Ethical AI in Marketing
Bias in AI systems is one of those issues that tends to get treated as someone else’s problem. That’s a mistake. When an algorithm generates unfair or discriminatory outputs, the consequences show up in the marketing P&L before they show up anywhere else. Campaigns get mistargeted based on inaccurate assumptions. Products get positioned toward the wrong audiences. Spend goes to segments that don’t reflect who your customers are.
AI and Marketing Attribution
Stop Guessing Which Channels Are Working. AI Can Tell You. Sarah stared at the dashboard on her screen. Her team had just wrapped up a successful quarter. Lead volume was …
