AI-Powered Email Marketing Strategist | Klaviyo Advanced Analytics Pioneer | Turning Customer Data Into Predictable Revenue for Beauty, Health & Fashion Brands

I lead a specialized team that builds AI-driven email marketing systems using Klaviyo's most advanced features, delivering measurable revenue growth through intelligent automation and predictive customer insights.

Why brands choose us for AI-powered marketing:

• Klaviyo Advanced Analytics Expert: Certified in RFM analysis, predictive CLV modeling, and AI-powered campaign optimization
• Predictive Revenue Intelligence: We implement machine learning models that predict customer behavior, optimal send times, and next-best-product recommendations
• AI Automation Architect: Building sophisticated flows that automatically segment, personalize, and optimize based on real-time customer data
• Industry AI Specialization: Deep expertise in beauty, health, and fashion customer psychology combined with advanced AI implementation

Our AI-driven methodology:
While other agencies send generic campaigns, we deploy intelligent systems that learn from every customer interaction. Our AI models analyze purchase patterns, engagement behavior, and lifecycle stages to automatically deliver the right message at the perfect moment.
Advanced AI implementations we deliver:

• Predictive churn prevention with automated win-back sequences
• Dynamic product recommendation engines based on behavioral AI
• Smart segmentation that evolves automatically as customers change
• Multi-touch attribution AI that optimizes budget allocation in real-time

Proven AI Results:
Our clients typically see 3-5x improvement in customer lifetime value and 30%+ increases in email revenue within 90 days of implementing our AI-driven systems.

AI Content & Education:
I share cutting-edge AI marketing strategies through my YouTube channel, breaking down complex automation workflows and Klaviyo's latest AI features for e-commerce growth.

Ready to implement AI that actually drives revenue? Most brands are barely scratching the surface of what's possible with intelligent email marketing.

🤖 Let's discuss how AI can transform your customer data into predictable growth
📊 Specialized AI Solutions: Predictive Analytics | Smart Automation | Revenue Intelligence
🌍 Serving: US Market | European Expansion | GDPR-Compliant AI

Today the first lesson of my Claude guide is live on Substack.

It's called "Claude Mastery for E-commerce Operators" - everything I've learned about using Claude for email marketing and e-commerce over the last 7 months, while transitioning my agency to run autonomously.

A new lesson drops daily.

But before you dive in, I made something to help.

A glossary of 50+ AI and Claude terms - explained simply for non-technical people.

If words like "context window," "MCP," "few-shot," or "schema" feel unfamiliar, this will help you follow along without getting lost.

I organized it from foundational to advanced:

→ Level 1: Start Here - The basics everyone should know 
→ Level 2: Getting Comfortable - Concepts you'll use regularly 
→ Level 3: Building & Connecting - For creating workflows and integrations 
→ Level 4: Under the Hood - Technical concepts for deeper understanding 
→ Level 5: Deep Technical - For those who want to understand AI deeply

You don't need Level 5 to get value from the guide. Start at Level 1 and go as deep as you want.

If you would like to get a link to both the guide and the glossary, 
- CONNECT WITH ME
- LIKE THIS POST and 
- comment below GLOSSARY 

and  I'll share the link with you to both.
(sorry, doing this because i need the reach)

Kinga Dow

AI Email Marketing | Klaviyo Advanced Analytics Specialist | Predictive Customer Intelligence

Great news for Klaviyo users! 🎉

You can now connect Klaviyo to Claude via Connectors—no terminal required. 

Just go to Settings > Connectors in Claude.ai, add https://lnkd.in/dmZvg3V2, complete the OAuth flow, and you're done.

But I ran into some issues and had to do a deep research session with Claude to figure out what was actually going on.

Here's my aha moment:

There are actually TWO different Klaviyo MCP servers—and they're designed for different environments:

☁️ Remote server → for Claude.ai in your browser (OAuth, zero setup) 
💻 Local server → for Claude Desktop app (requires terminal, API key)

They work in parallel. Not interchangeable.

The error that confused me:

"Server with this URL already exists"

Turns out, when you add the remote connector in Claude.ai, it automatically syncs to Claude Desktop. So if you try adding the same URL again? Blocked.

The solution isn't to force the remote URL into Desktop—it's to use the local server there instead. Different environments, different server types.

The takeaway:

For most non-technical folks, the browser connector is all you need. One-click OAuth, no terminal, no API keys.

This is what I found through my research—but if anyone has discovered something different or has a workaround I missed, I'd love to hear it in the comments 👇

I did it. I actually created a course, and it goes live tomorrow on Substack.

Claude Mastery for E-commerce Operators is everything I've learned over seven months of building Claude-powered workflows—distilled into a comprehensive course for anyone ready to move from chatting with AI to building systems that actually run parts of their business.

This isn't a how-to filled with prompting tricks. It's an explanation of fundamentals—how Claude actually thinks, why it behaves the way it does, what makes agentic AI different from the chatbot experience most people know. I'd argue this foundation matters more than any tutorial, because once you understand the underlying logic, you can build anything.

The course draws from my work in e-commerce email marketing—years of Klaviyo experience translated into AI-powered workflows. But the principles apply far beyond email. It takes you from the mental models that make Claude click, through building your first agents, all the way to multi-agent systems that coordinate across your tools. It's for anyone curious about what the shift to agentic AI actually looks like in practice—not the hype, but the real operational transformation.

Available on Substack tomorrow—I'll share links then. 🚀

I just built this chart using Claude.

This demo diagram was generated automatically by Claude in under a minute - and it's fully editable. Everything can be changed.

It shows:
✓ Every flow organized by customer lifecycle stage
✓ Every email in sequence with timing
✓ Customer progression paths (the dashed arrows)

This is just a demo of what's possible. However, with direct MCP access, Claude can see all the flows in Klaviyo and map this out by itself. 

What used to take hours of manual work → Now 1 hour automated.

The best part? I have the capabilities to not only show what EXISTS but also show what's MISSING and how much revenue is being left on the table.

For e-commerce brands with 50-100+ flows, this is game-changing visibility.

Are you convinced yet that Claude + email marketing = superpowers?

Just added a major upgrade to my Klaviyo Flow Audit System.

💬 Quick background: I built an AI-powered audit tool that connects directly to Klaviyo accounts via MCP, pulls all flow data, analyzes performance, and generates full audit and optimization recommendations automatically in your CRM.

What used to take 6-8 hours now takes under an hour.

But the system just got more powerful.

➡️ New capability #1: Customer Lifecycle Mapping

Claude now categorizes every flow by customer journey stage - Acquisition, Activation, Conversion, Retention, Reactivation.
Then generates a complete diagram automatically.
Full visualization of the entire email ecosystem in under a minute. Editable. Professional. Gaps in lifecycle coverage become immediately obvious.

➡️ New capability #2: Unused Metrics Analysis

This is the one I'm most excited about.
The system pulls every metric from the Klaviyo account - Shopify events, review triggers, form submissions, everything being tracked.
Then cross-references against actual flow triggers.
The output: a list of high-activity metrics that aren't being used in any automation.

🚀 From a recent audit:
→ "Viewed Collection" - thousands of events monthly, no flows using it 
→ "Submitted Search" - valuable intent data, no follow-up automation 
→ Typeform integration active, data flowing into Klaviyo, zero automation built on it

These are metrics already being collected. The data is there. It's just not being activated.

Each one is a revenue opportunity waiting to be built.

👉 Who this is especially useful for:

DTC brands running email in-house without a dedicated Klaviyo specialist.

Marketing teams that know flows but haven't had time to dig into every available metric.

Agencies onboarding new clients who need a fast, thorough account snapshot.

More capabilities coming soon.

What metrics have you found sitting unused in Klaviyo accounts?

====================
Hi, I'm Kinga. I run an email marketing agency and help e-commerce businesses transition to autonomous operations with Claude AI.

💾 Save this for later
♻️ Repost if this clicked for you

Today I'm sharing a little hack: How I created a Customer Language Bank so my email copy speaks directly to customers.

This is part of my "AI Email Marketing Setup - a Business Intelligence Foundation" I build with Claude for each client. It's what helps us both understand their customers.

What is a Customer Language Bank?

It's a document filled with the exact words, phrases, and emotions your customers use - mined directly from their reviews.

Not what you think they say. What they actually say.

How I built it:
Exported customer reviews from Klaviyo Reviews (you can do the same with Yotpo, Judge.me, Okendo, or any review platform)

Fed them to Claude with a simple prompt: "Extract the exact language customers use, organized by theme"

Refined into 9 actionable categories

The categories that make this actually useful:
→ Praise Phrases - Copy-paste ready quotes for social proof 
→ Product-Specific Language - How customers describe what you sell 
→ Emotional Triggers - The feelings that drive purchases 
→ Pain Points & Objections - What to address proactively in copy 
→ Repeat Purchase Triggers - Language that signals loyalty 
→ Customer Segment Language - Different words for different buyer types 
→ Subject Line Swipe File - Ready-to-use, derived from real feedback 
→ CTA Variations - Calls-to-action in their language 
→ Quick Reference Cheat Sheet - Top phrases + marketing words to avoid

The insight that changed everything:
Customers don't say "curated" or "elevate" or "premium experience."
They use simple, direct words. Real reactions. Specific details.

Now when I write campaigns:

➡️ Subject lines come from actual customer quotes
➡️ Body copy addresses real objections
➡️ CTAs use words they already use

The Language Bank lives in Claude's project knowledge. Every campaign speaks the customer's language, not the marketer's.

This is one piece of a larger system. But it's the piece that makes all the other pieces work better.

Want to learn more tricks like this?

Tomorrow I'm releasing a guide/manual on Substack - an introduction to Claude for e-commerce and email marketers operators. Everything I learned over 7 months while transitioning my agency to run autonomously.

New lesson will drop every day for the next 40 days.

DM me for the link.

Tomorrow I'm leading an Expert Session—and I can't believe I'm the one teaching in this amazing community.

Last year I joined Grace Leung's community because I wanted to learn from her.

If you haven't discovered Grace yet, you need to. She's a digital growth YouTuber (link in the first comment) with over 100,000 subscribers—and growing steadily month over month. Her content on AI and digital marketing is genuinely valuable. Not fluff. Not hype. Real workflows you can actually use.

When I joined, I also discovered she has a community where we have regular sessions and learn from different people. It's been incredibly valuable to me.
Now Grace has invited me to lead an Expert Session on how I use Claude AI for email marketing and project management.

I'll be sharing the actual workflows I use in my agency—including how I turn content directly into Asana tasks. This is the part of my setup I consider most valuable, and I'm excited to give back to a community that's given me so much.

If you're already in Grace's community, I'll see you tomorrow.

If you're not—go check out her YouTube channel and subscribe. And if you want to go deeper, join her community. I know you'll get incredible value from it.

📅 Wednesday, January 21st 🕒 3:00 PM - 4:00 PM CET

— 
Hi, I'm Kinga. I run an email marketing agency and help e-commerce businesses transition to autonomous operations with Claude AI.

♻️ Repost so more people can discover Grace and her community 
✉️ Follow me on Substack for free AI agent tutorials

I just closed the full loop: from email conception to complete Klaviyo setup — automated.

Here's the workflow I've been building:

📌 Figma MCP → Get component + image URLs
📌 Klaviyo MCP → Upload images (permanent hosting)
📌 Claude → Convert to email HTML with Klaviyo image URLs
📌 Klaviyo MCP → Create template with HTML
📌 Klaviyo MCP → Assign to campaign

But this is just the final piece.

The full process now covers:

🔸 Building marketing calendars
🔸 Creating copy
🔸 Setting up tasks in Asana
🔸 Building email campaigns and templates in Klaviyo based on your Figma layouts

All of it can be orchestrated through Claude AI agents.

Agencies, DTC brands, business owners — how much time do you currently spend on this workflow manually?

I'm still testing the final phase, but I'd love to know: would automating this actually help with your workload, or is the creative/strategic piece what takes the real time?

Drop a comment or DM me. Genuinely curious.

Kinga Dow I AI Klaviyo Email Marketing

I wrote Claude AI Course for E-commerce Operators | Find it on Substack | Klaviyo Gold Partner Agency Owner | Open to New Contracts

The trend for 2026 is clear: agencies are going agentic.

In the last 30 days, I've talked to many agency owners and operators. The pattern is obvious - everyone wants to systematize AI across their team, not just dabble with it.

Here's my strong recommendation:

Make Claude your primary operational base.

Set up a Team or Enterprise account. Get everyone working in the same space.

Yes, different LLMs have different strengths. Maybe you use Gemini for deep research, or another tool for specific functions. That's fine - use them as supplements.

But your operational core? That should be centralized. One platform. One command center. Not one person using ChatGPT here, another using a Gemini gem there, with knowledge scattered everywhere.

When your whole team works in the same space, Claude becomes the brain of your agency - all your resources, knowledge, and context combined across departments but unified in one place.

Here are some of the benefits:

💥  No more cold starts - Claude already knows your processes, frameworks, and preferences. No re-explaining every time.

💥  Shared knowledge base - Upload your SOPs, style guides, client briefs once. Everyone on the team benefits automatically.

💥  Consistency across the team - Same custom instructions, same context, same quality. No more different outputs because someone prompted differently.

💥  Error margin shrinks - When everyone works from the same knowledge base with the same instructions, mistakes get caught and outputs stay consistent.

💥  Management has visibility - See what's happening across accounts, set spending controls, manage access centrally.

💥  Knowledge survives turnover - Context lives in the system, not in someone's head. New hires ramp up in hours, not weeks.

💥  Your advantage compounds - Every project, every conversation makes Claude smarter about your agency. The intelligence builds over time.

I've been doing this for several months now. Early on, I explained everything from scratch. Now Claude knows my benchmarks, my frameworks, my preferences. It's like working with a team member who's been there from day one.

The sooner you start, the faster you build that intelligence.

2025 was experimentation. 2026 is systemization.

The agencies that figure this out first will be hard to catch.

(random picture attached, as it helps getting wider reach)

My course went live last Monday.

Claude Mastery for E-commerce Operators — and I wanted to share what's inside for anyone considering the shift to agentic AI.

I'm releasing it one lesson at a time. 43 lessons total, so there's still a lot to go. 

But this pace is intentional — easy to digest, not overwhelming.

This isn't your typical course.

It's more of a guide and manual for transitioning to Claude and actually understanding how it works when it comes to email marketing and AI.

➡️ What's inside: 
→ How Claude actually thinks (not prompting tricks — fundamentals) 
→ When to use Claude vs. when it's the wrong tool 
→ Prompting for agents, not conversations 
→ Native tools: artifacts, web search, code execution 
→ MCP — connecting Claude directly to Shopify, Klaviyo, Notion, Asana, Fireflies.ai 
→ Building your first agent 
→ Multi-agent systems 
→ Real-world applications and productizing your workflows

🟢 Who it's for: Anyone in e-commerce ready to move from chatting with AI to building systems that run parts of their business.

🔴 Who it's not for: People looking for copy-paste prompts. This is about understanding the underlying logic so you can build anything.

I attached the full course overview below.
Currently free → substack.com/@kingadow

====================
Hi, I'm Kinga. I run an email marketing agency and help e-commerce businesses transition to autonomous operations with Claude AI.

💾 Save this if you're ready to stop being the bottleneck 
♻️ Repost if this clicked for you

AI-powered e-commerce Claude mastery

MCP connectors in Claude are being updated almost daily now.

I keep checking back and there's always something new. Just recently: ClickUp and Klaviyo were added. And the pattern is clear — CRMs and productivity tools are racing to integrate.

Why? Because they understand the value of working directly from Claude.

Think about it: Claude essentially becomes your project manager. Instead of manually creating tasks, logging into different platforms, copy-pasting information — you just tell Claude what needs to happen and it creates the task directly in your system.

Here's my current connector stack:

☁️ Web Connectors (browser-based, OAuth — zero setup):

Asana — task and project management
ClickUp — task and project management (yes, I use both depending on the client)
Google Drive — file search and access
Fireflies.ai — meeting transcripts and notes
Jotform — form creation and submissions
Klaviyo — email marketing flows, campaigns, analytics
GoMarble AI — ad analytics for Meta, Google, Shopify
Notion — docs, databases, wikis
Gamma — AI-powered presentations and documents

🖥️ Desktop Extensions (Claude Desktop app):

Figma Dev Mode — design file access
Filesystem — local file access
Apple Notes — read and write notes

⚙️ Local Dev / Custom MCP Servers (technical setup, API keys):

GA4 Analytics — Google Analytics data
Klaviyo — direct API connection
Notion — direct API connection
Shopify — store data and analytics

The bigger picture:

We're watching the shift happen in real-time. Every SaaS tool that wants to stay relevant is building their MCP connector. It's becoming the new API standard for AI-first workflows.

What connectors are you using? Any favorites I'm missing? 👇

I'm old enough to remember when businesses said "we don't need a website."

Then WiFi. Then social media. Then mobile. Then cloud. Then e-commerce platforms.

Every single time, the same conversation: "We'll wait and see."

And every single time, the same outcome: 5-7 years from mainstream viability to competitive necessity.

So I did a deep dive into 30 years of technology adoption data to show you exactly how this pattern plays out.

The 5-7 Year Rule Across Six Major Waves:

📍 Websites (1995 → 2000-2002): Amazon founded 1995, internet hit 52% U.S. penetration by 2000, businesses without websites invisible by 2002.

📍 WiFi (1999 → 2010): Launched as 802.11b standard in 1999, became free/expected by 2010 when McDonald's and Starbucks made it standard.

📍 Social Media (2004 → 2010-2012): Facebook founded 2004, by 2012 influenced 52% of purchases while Myspace lost 1M users/month and sold for $545M loss.

📍 Cloud (2006 → 2012-2015): AWS launched 2006, by 2015 90% of SMBs adopted cloud, market grew 535% in decade.

📍 Mobile (2007 → 2015-2016): iPhone launched 2007, mobile surpassed desktop 2016, Nokia went 49% → 3% market share, BlackBerry collapsed from 80M users.

📍 E-commerce (2010 → 2015-2017): Crossed viability threshold ~2010, by 2017 the "Retail Apocalypse" killed 154 chains including Borders, Blockbuster, Toys R Us, Sears.

The timeline from "experimental" to "existential" is remarkably consistent.

The Adapters vs. The Casualties:

Those Who Thrived:

⬆️  Amazon: Reinvested profits for years, now dominant in retail, cloud, streaming
⬆️ Netflix: 7-year cloud migration enabled 260M+ global subscribers
⬆️ Best Buy: Digital transformation → market value $11B to $32B
⬆️ Walmart: $3.3B Jet.com acquisition → became #2 online retailer

Those Who Fell:

⬇️ Nokia: Dismissed touchscreens, 49% → 3% market share in 6 years
⬇️ Borders: Outsourced e-commerce to Amazon, liquidated 2011
⬇️ Blockbuster: Rejected Netflix's $50M offer, bankrupt 2010
⬇️ BlackBerry: 80M users → 0.2% market share

The difference? Winners treated emerging technology as fundamental operating philosophy. Losers treated it as "nice to have."

Claude Mastery for E-commerce Operators is live on Substack.

Seven months of building Claude-powered workflows — distilled into 10 modules for anyone ready to move from chatting with AI to building systems that actually run parts of their business.

This is NOT:

🔴 A collection of prompting tricks
🔴 A technical tutorial on how to do a Klaviyo audit
🔴 Another "10 ChatGPT hacks" post

This IS:

🟢 An explanation of fundamentals — how Claude actually thinks, why it behaves the way it does

🟢 What makes agentic AI different from the chatbot experience most people know

🟢 The foundation that lets you build anything once you understand the underlying logic

The course draws from my work in e-commerce email marketing — years of Klaviyo experience translated into AI-powered workflows. But the principles apply far beyond email.

It takes you from mental models → first agents → multi-agent systems that coordinate across your tools.

👍  Who it's for: Anyone curious about what the shift to agentic AI actually looks like in practice. Not the hype. The real operational transformation.

👎 Who it's not for: People looking for copy-paste prompts or tool-specific tutorials.

Modules 1-4 are live. 👉 substack.com/@kingadow

How do you build retention when customers only buy once or twice a year?

No subscription. No loyalty program. No repeat consumables.

This is the reality of gift-based e-commerce. 

People buy for occasions — holidays, birthdays, corporate thank-yous. Then they're gone until the next occasion.

Here's how I rebuilt the entire retention system — with Claude as my strategist.

➡️ The Challenge

I've been working with a premium gifting brand since 2024. The business is seasonal and occasion-driven:

→ Heavy holiday seasons 
→ Spikes around gifting occasions 
→ Long gaps between purchases 
→ No natural replenishment cycle

Traditional retention playbooks don't work here. You can't send "time to reorder" emails when there's nothing to reorder.

➡️ The Rebuild (Claude as Strategist)

Since May, I've been working with Claude daily. Not just for ideas — for execution.

Claude did the heavy lifting. I'd bring the business context, Claude would break it down into strategy and structure everything for implementation.

The best part? Claude set up the entire strategy in Asana. Each task had a detailed brief with the objective, target segment, trigger logic, email sequence, copy direction, and success metrics.

For Klaviyo, every flow was outlined with exact trigger conditions, filter logic, time delays, conditional splits, and exit conditions.

I wasn't guessing. I was executing a system.

➡️ What We Rebuilt

1. RFM + CLV Segmentation

Segments based on Recency, Frequency, and Monetary value — plus Customer Lifetime Value calculations.

CLV is tricky for gift businesses. Claude made it easy to calculate and segment by:

→ Holiday-only buyers 
→ Corporate gifters (predictable timing) 
→ Multi-occasion buyers (the VIPs) 
→ One-and-done (win-back targets)

Each segment got dedicated flows AND campaigns.

2. Trigger-Based Flows Around Occasions
Instead of "time to reorder," we built flows around:

→ Upcoming holidays (reminder sequences) 
→ Anniversary of last purchase 
→ Corporate gifting seasons 
→ Post-purchase cross-sell (REVIEWS.io integration)

3. Pop-Up Strategy by Segment

→ New visitors (gamified welcome flow) 
→ Returning visitors by RFM segment 
→ Occasion-specific landing pages 
→ Zero-party data collection for existing subscribers (preferences, gifting occasions, recipient types)

4. Marketing Analytics Infrastructure

Custom website meant working within limitations. We added:

→ Klaviyo Marketing Analytics integration 
→ REVIEWS.io  for social proof and cross-sell triggers 
→ Proper attribution tracking

➡️ The Lesson

Retention isn't about frequency. It's about relevance.

If your customers only buy twice a year, your job is to be there at exactly the right moment — with exactly the right message.

Claude helped me map those moments, build the systems, and create implementation-ready briefs I could actually execute.

Using AI as your strategic partner? I'd love to hear how you're working with it.

Okay Wispr Flow, you got me.

I officially cannot live without you anymore. I just upgraded to the paid version.

Here's the thing about working with AI in 2026:

Context is everything.

Claude needs details. Nuance. Background. The more I give, the better results I get.

But typing all that context?

That's where I was losing time.

I don't want to spend my energy on inputting ideas. I want to spend it on executing them.

Wispr Flow changed that equation for me.

Now I just... talk.

And my thoughts become text - clean, punctuated, ready to go - in any app, instantly.

Why I upgraded:

→ Works everywhere (Claude, Slack, Notion, email - everywhere I type) 
→ Learns how I speak (no more awkward corrections) 
→ 3x faster than typing (and my hands thank me) 
→ Cleans up my "ums" and rambling automatically 
→ Offline mode for sensitive client work

If you're building with AI every day, the bottleneck isn't the AI.

It's how fast you can communicate with it.

Here's the truth:

I was skeptical at first.

Then I started noticing YouTubers using it in their tutorials.  So I tested the free version.

For weeks, I thought "nice to have."

Then something shifted.

I got accustomed to just... talking my ideas out. No friction. No typing fatigue.

And when I hit my free limits? I couldn't go back.

That's when I knew: this is the new way of working.

Anyone else a Wispr convert? 🎙️ Drop a comment below

Stop Being the Bottleneck: A System for Getting Your Knowledge Out of Your Head

So many business owners are the bottleneck in their own company. Every decision runs through them because all the knowledge is trapped in their head. I know this because I struggled with it at my agency for years.

Here's the system I developed to systematize my work and transfer what's in my head into accessible documents. This helps with processes, training new hires, and scaling operations.

🔴 The Problem

Your business knowledge lives in your brain. When someone asks "how do we handle X?" you have to stop what you're doing and explain it. Again. This doesn't scale.

🟢 The Solution: A 3-Part System

➡️ Part 1: Organize Your Business Intelligence
Create a Google Drive structure that mirrors how your business actually works.
This becomes your single source of truth. Everything documented, nothing in your head.

➡️ Part 2: Create Specialized AI Agents
Build two Claude Projects (AI agents) with specific jobs:
→ SOP Creation Agent
→ Turns your brain dumps into proper documentation
→ Follows your formatting standards automatically
→ Saves everything to the right folder
→ Operations Logger Agent
→ Records completed work
→ Updates your CRM/project management
→ Maintains consistent records

Both connect to your Google Drive through MCP (Model Context Protocol) so they can read and write directly to your system.

➡️ Part 3: Add Skills Files
Skills are simple markdown files that teach the AI your exact workflow. It's like training an employee, but you do it once.

Your SOP Creation Skill contains:
→ How you structure processes
→ Your writing standards
→ Where files get saved
→ What metadata to include

Your Operations Logging Skill contains:
→ What gets tracked after each client interaction
→ How tasks get categorized in your CRM
→ Your naming conventions
→ Next action protocols

🟡 Why This Works

Once everything is cataloged in your organized system, the AI can find it instantly. No more searching through Slack messages or email threads.

When you hire someone new, they can ask the AI agent "how do we handle X?" and get the exact process you'd explain—without interrupting you.

When a process changes, you update one document and everyone (human and AI) has the new version.

✅ The Real Benefit

You stop being the bottleneck. Your knowledge becomes organizational knowledge. Your team can operate independently because the system contains what used to only exist in your head.

That's how you scale without losing quality.

Start with organizing your Google Drive. You can't systematize what isn't structured.


=====================================

Hi, I'm Kinga. I run an email marketing agency and help e-commerce businesses transition to autonomous operations with Claude AI.

💾 Save this if your found value in this
♻️  Repost if this framework clicked for you 
📧 I just published a course: Claude AI for E-commerce Email Marketing on Substack → Find me: substack.com/@kingadow

Is your time invested in ChatGPT holding you back from switching to Claude?
There's a way around it.

I've been talking to a lot of business owners and agency owners lately.

Their biggest concern about switching to Claude? All the time they've invested in ChatGPT. All the conversations. All the context.

Starting over feels like losing months of work.

But there's a way around it.

ChatGPT lets you export all your data: 
Settings → Data controls → Export data

Upload it to a Claude Project, and you give Claude all that context about your business, your decisions, your thinking.

You could create a "Brain Trust" project with your ChatGPT history plus your key documents - SOPs, client briefs, brand guidelines. All your institutional knowledge in one place.

It won't replace your custom GPTs. But it solves the "starting from scratch" problem.

♻️ Share this with someone who's been on the fence about switching.

----------------
Follow me for more on Claude for e-commerce 🤖

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