课程

Define "Good": Marketing for Non-Marketers in an AI World

Vanina Schick · 授课老师

适合对象
Experts —Professional service vendors in any field: you'll get clarity and confidence you need to market yourself. Builders —You've made something you want to sell, digital or physical: you'll be ready to lead your own Go-To-Market. Solopreneurs —You're a team-of-one by design: you'll level up your Marketing better than any third-party can.

Vanina Schick Former VP Marketing at Maven (yes, here) Course is in session Covered by the Maven Guarantee We can all create anything with AI... But i…

课程内容

课程概览

Vanina Schick

Former VP Marketing at Maven (yes, here)

Course is in session

Covered by the Maven Guarantee

We can all create anything with AI... But is it "Good"?

There's now an AI tool for every part of Marketing: Design, Outreach, Email Automation, Social Content... But with every new workflow the same hard questions resurface:

> ⛔ Who is this actually for?

> ⛔ What makes my customer really want it?

> ⛔ What should it look & sound like?

With AI, execution is not the bottleneck. It's knowing what to execute, where, and why. The bottleneck is now deciding what "Good" means.

Despite what the high-ego marketers and AI-doomers out there say, understanding "Good" is not a mysterious, or exclusively human. "Good" simply means your Marketing:

> ✅ Speaks to the right customer

> ✅ Focuses on what they'll actually pay for

> ✅ Looks and feels coherently, uniquely yours

In this course your take the key strategic decisions owned by a marketing leader, defining "Good" in your unique context.

Across 8 hours of hands-on coaching you'll become the Marketing Director that your AI-Marketing execution needs.

Practically said, we will establish the objective criteria of quality for your marketing, so that you can:

> 🤖 Efficiently delegate it's execution to AI

> 🎨 Evaluate AI's output quality and skillfully prompt iterations

> 🚀 Rapidly test & learn in-market

What you’ll learn

1 hr/day of core marketing theory to rigorously shape & document your strategic marketing context, ready for use in AI-marketing execution.

MONDAY -> Position your offer

Articulate your customer need (Moesta's Jobs-to-be-Done method)

Write your positioning statement (Dunford's Obviously Awesome template)

TUESDAY → Define your social opportunity

Define the socio-cultural conversations your offer is part of

Find the POV that will earn you attention in the new media landscape

WEDNESDAY -> Define your brand codes

Identify your category's visual and verbal codes, how you fit or break them

Find your brand's personality archetype

THURSDAY -> Map your full customer journey

Document how your customer discovers and decides to buy-- or not

Identify their key behavioral truths: trigger, drop and stop points

FRIDAY -> Create your ICS (Ideal Customer Sim)

Explore and document your customer's attitudes and psychology

Build your AI-ready ICS that combines phycological and behavioral insights

MONDAY CAPSTONE CHALLENGE -> Test & refine

Create a real AI-marketing deliverable, using your new strategic marketing context as input

Run your first ICS evaluation: get AI to eval it's own work using your Ideal Customer Sim

Iterate in 2 different ways: on the input itself, and on the output

Learn directly from Vanina

Vanina Schick

Product Marketing Leader I Brand Context Engineering I Qualitative Research

When AI-Marketing slop emerged, I recognized the problem: execution with insufficient context.

I scaled one of Europe's best loved startups, managing dozens of regional marketers creating a new category. What made my teams effective was strategy encoded so clearly that execution quality held across language & channels, without me in the room.

Before that, I worked in a sector with some of the strongest brand & quality codes in the creative world: the French Luxury Houses.

Scross a multi-disciplinary career, spanning advertising, customer research, brand strategy & product design I've understood one key truth: creative work is the explainable result of intentional input.

AKA Input quality = Output quality.

In an AI-world, this understanding is powerful, and why I created this course.

Career highlights

Tripled Maven's total course sales volume;

grew directly-attributed sales from 20% to 33% of platform revenue

Drove Maven's upmarket reposition, increasing revenue per visitor by 100%

Built Lightning Lessons product and distribution strategy, now Maven's largest new-lead channel

Co-founded a Design Thinking consultancy applying ethnographic research methods to Fortune 500 innovation projects

Founding Product Marketer at major European scale-up, BlaBlaCar from 2M to 30M users across 14 markets, achieved 87% unprompted awareness (Series B through C)

Masters in Graphic Design, and first career as an Art Director in luxury advertising

课程大纲

  • 明确客户需求与产品定位

    识别社会文化话题与观点

    定义视觉语言及品牌风格

    梳理客户发现和购买路径

    整理理想客户背景及行为假设

    依据战略背景评估并改进输出

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