Growth Marketer

AI repriced the marketing skill market. An honest inventory of which capabilities gained value, which collapsed, and how to reposition — for individuals and for hiring managers.

A clear-eyed mid-year assessment of AI in marketing: which capabilities crossed into production, which promises stalled, and where the next twelve months are heading.

B2B's long cycles, small audiences, and committee buying change what AI is good for. A practical map of the B2B use cases that pay off — and the B2C imports that don't.

Where AI image generation genuinely works in marketing, where it embarrasses brands, and the brief-to-asset process that keeps quality and consistency high.

Turn one webinar or event session into a month of content — recap article, clips, social posts, email sequence, and FAQ — with AI handling the transformation.

Perplexity matters to marketers twice — as a daily research tool with citations built in, and as an answer surface where your brand is either present or absent.

Synthetic data is artificially generated data that mimics real data's patterns — used in marketing for testing, privacy-safe analysis, and simulated audience research.

A mid-2026 stocktake: what actually changed in AI marketing this half, what was noise, and the one capability gap that will define H2.

Should your team buy packaged AI agent products or build on frameworks and automation platforms? A decision framework based on what actually predicts success.

A practical guide to AI research tooling for marketing — deep research agents, NotebookLM-style workspaces, and Perplexity — and how to use them without inheriting their errors.

How to use AI to run continuous competitor intelligence — positioning shifts, pricing changes, content strategy, and AI-answer presence — without a research team.

Set up an AI agent that automatically researches every new lead, fills in firmographic and intent context, scores fit, and routes the best ones to sales with a briefing.

Agent traffic becomes a real audience segment, plus notes on machine-readable pages, analytics hygiene, and agent-friendly conversion paths.

A context window is the amount of text an AI model can consider at once — the working memory that limits how much brand, data, and campaign context you can supply.

The metrics that actually capture AI's impact on marketing — from AI-answer visibility share to workflow unit costs — and the vanity numbers to retire.

AI agents that research, compare, and buy on a user's behalf are emerging — and they change who marketing actually has to persuade.

An honest analysis of CrewAI for marketing teams — what the multi-agent 'crews' framework actually delivers, what it costs, and who should adopt it.

An advanced closed-loop system where AI generates ad creative variants from a concept matrix, structured tests pick winners, and performance data trains the next generation round.

AI moves into lifecycle and CRM marketing — adaptive sends, generated segments, and the new discipline of reviewing what the model decided.

An agentic workflow is an AI process where a model plans, uses tools, and iterates toward a goal — deciding its own steps rather than following a fixed script.

A practical walkthrough for shipping your first AI marketing agent — a no-code path and a code path, with scoping advice, guardrails, and a realistic timeline.

A working review of the AI ad creative stack — generation, iteration, and pre-flight testing tools — and how paid teams should actually deploy them.

A staged path for paid media specialists: work with platform automation instead of against it, build an AI creative engine, and automate analysis and reporting.

How paid media teams use AI across creative generation, automated bidding, and testing in 2026 — what to automate, what to keep human, and where budgets leak.

A step-by-step workflow for turning a single webinar, podcast, or long-form video into clips, shorts, social posts, and an article using AI tools — in about two hours.

Where Claude and ChatGPT each genuinely excel for marketing tasks — writing, research, analysis, and workflow — without fanboy scoring.

A staged learning path for marketers building AI-powered video and creative production: from first generations to a repeatable creative pipeline.

AI answers collapse the research phase of buying journeys. What that compression really means for funnel strategy — and what survives it.

AI-simulated customer personas are entering the research workflow — fast and cheap for early exploration, risky as a substitute for real customers.

AI made one-to-one personalization technically possible. The teams making it work treat it as a data and governance problem, not a copy problem.

Build an AI agent that monitors brand mentions and sentiment across social platforms and communities, classifies what matters, and routes each mention to the right action.

An honest look at AI analytics copilots for marketing teams — where natural-language querying delivers, where it hallucinates, and how to adopt without breaking trust in your data.

Build an email nurture sequence that rewrites itself: AI drafts variants, engagement data picks winners, and the losers get replaced automatically every cycle.

Marketing automation rebuilds around AI-native workflows, plus notes on context management, connector sprawl, and a stat on time reclaimed.

When AI answers satisfy the query, the answer itself becomes the touchpoint — and marketing has to work without the visit.

A repeatable workflow for auditing your existing content's visibility in AI answers and systematically optimizing it for citation in ChatGPT, Perplexity, and Google AI Overviews.

A head-to-head comparison of n8n, Make, and Zapier for building AI-powered marketing automations — pricing models, AI capabilities, and which teams should pick which.

Prompt engineering is the practice of designing inputs to AI models — context, examples, instructions, and constraints — to reliably produce useful, on-brand outputs.

Practical prompt patterns for marketing tasks — briefs, rewrites, analysis, and campaign ideation — with copy-paste templates and the mistakes to avoid.

A staged learning path for social media managers who want to use AI across ideation, creation, scheduling, listening, and reporting — without their channels going generic.

AI agents that browse the web on users' behalf are redefining what a 'visitor' is — and what websites must do to convert one.

How to apply AI across your email program — ideation, copy, personalization, send-time, deliverability, and reporting — with realistic expectations at each step.

Set up an AI agent that monitors competitor websites, pricing, ads, and content every week and delivers a short brief of what changed and why it matters.

AI is turning small social teams into full media operations, plus notes on comment intelligence, format testing, and creator disclosure norms.

Marketing loops are self-improving AI workflows that feed performance results back into the next run, so campaigns learn and improve automatically over time.

Marketing loops are AI workflows that feed performance data back into the next run, so campaigns improve automatically. Here's how to design and ship your first one.

A staged path for marketers who want to go beyond prompting and actually build AI agents that monitor, research, and act on marketing tasks autonomously.

A pragmatic blueprint for the AI stack of a sub-10-person marketing team — what to buy, what to skip, and how to sequence adoption without drowning in tools.

AEO is the practice of structuring content so AI answer engines like ChatGPT, Perplexity, and Google AI Overviews select and cite it as a source in their responses.

Answer Engine Optimization (AEO) is the craft of earning citations in AI-generated answers. Learn the tactics that get your pages quoted by ChatGPT, Perplexity, and AI Overviews.

A clear-eyed guide to AI features in email marketing platforms — which capabilities move revenue, which are demo-ware, and how to evaluate the 2026 field.

A staged learning path that takes you from understanding what generative engine optimization is to running a full GEO program with measurement, optimization, and reporting.

A five-stage blog production workflow that uses AI at the brief, research, draft, edit, and publish stages — while keeping a human editor in charge of quality.

Marketing teams are moving from AI chat to AI agents with defined scopes, plus notes on approval workflows and agent-readable content.