TL;DR

Most people experience marketing as a menu — a collection of disciplines to choose from, each one promising results, none of them quite connecting. This post offers a different frame: marketing is a system of systems. It always follows the same underlying logic, and once you understand it, all of the pieces just fall into place. AI didn’t create the system. It just made it a lot more obvious.

Everything is a System

There’s a moment — if you’ve ever tried to seriously integrate AI into your work — where something shifts.

You sit down to hand a task to a system and realize you can’t. Not because the tool isn’t capable, but because you can’t explain what you’re actually doing clearly enough to teach it. You don’t know the sequence. You don’t know what depends on what. You’ve been operating on instinct so long that the logic of your own work has become invisible to you.

That moment is uncomfortable. It’s also one of the most clarifying things that can happen to a marketer right now.

Draw the diagram. Name the layers. Understand what has to be true before the next thing can function.

And once you start doing that, you can’t stop. It becomes glaringly obvious: everything is a system. Your content workflow is a system. Your go-to-market motion is a system. Your customer acquisition strategy is a system. And all of those systems sit inside a larger one: your marketing operation as a whole.

The Code Behind the Disciplines

Here’s what the marketing advice ecosystem looks like from the outside: an endless feed of experts, each one making a compelling case for their own thing. Brand. Content. Go-to-market. Growth. Every lane has its champions. And every champion is, within their lane, correct.

What nobody shows you is the code running underneath all of it.

Marketing isn’t a menu of disciplines to choose from. It’s a system. A set of interdependent layers where what you build first determines what’s possible later.

The disciplines aren’t competing options. They’re the visible surface of something that has structure, sequence, and logic. A logic that operates whether you see it or not.

So, I am asking you to follow the white rabbit, take the red pill, and start seeing the system that runs everything. (Yes, I’ve made myself Morpheus in this Matrix-themed analogy. That means you are Neo.)

The Layers — And Why Order Matters

Let’s make the system visible.

Exhibit 1. Layers of the Marketing System

Brand is the foundation. It defines who you are, who you’re for, what you stand for — and just as importantly, what you don’t. It’s the layer that tells every other part of your marketing operation what it’s working with. Without it, you’re not making marketing decisions. You’re making guesses that occasionally work and wondering why you aren’t seeing more progress.

Content is how your brand thinks in public. It’s the expression layer — the ongoing articulation of your point of view across channels and formats. This is where tactics like social media, long-form content, and SEO live. Content only works when it has something real to draw from. Brand gives it that. Without a clear brand underneath it, content becomes an endless production problem — you’re always asking “what should we post?” instead of “how do we say what we already know to be true?”

Go-to-Market is how you take a specific offer to a specific audience at a specific moment. It borrows from both brand and content — the positioning, the voice, the proof points, the channels where your audience already lives. A go-to-market strategy built without those layers underneath it is just a launch plan. And launch plans without strategic underpinning tend to underperform.

Growth is the acceleration layer. Paid media, SEO investment, lead generation, conversion optimization — these are the tools you use to pour fuel on what’s already working. Which means they require the other layers to be working first. The math doesn’t lie: when your cost per acquisition keeps climbing and your conversion rates stay flat, the problem is almost never the ads. It’s what the ads are pointing to.

The sequence itself isn’t rigid. Real businesses don’t build in perfectly ordered phases — you iterate, you revisit, you refine. But, once the system is running, the sequence becomes a cycle. Brand informs content. Content surfaces what’s resonating in the market. Market signals inform how you evolve your positioning. Positioning sharpens the brand. The layers don’t just build on each other — they feed each other.

Exhibit 2. Interconnected Marketing System

Why The System Stays Hidden

Marketing has always been taught by discipline. You learn brand strategy from brand strategists. You learn SEO from SEO specialists. You learn growth marketing from digital marketers. Each body of knowledge is deep and legitimate and genuinely useful — inside the right context, at the right stage, on top of the right foundation.

But nobody teaches the sequence. Nobody explains that some of this advice applies to you right now, and some of it applies to a version of your business you haven’t built yet.

So operators do what any reasonable person does when confronted with an abundance of credible, conflicting advice: they pick the thing that sounds most urgent, or most interesting, or most like what their competitors appear to be doing. They execute it earnestly, get inconsistent results, and conclude — quietly, and usually incorrectly — that marketing doesn’t work.

But the tactic wasn’t wrong. The timing was.

What AI Is Clarifying About All of This

When you introduce AI into a marketing operation that has clear architecture — a solid brand layer, a content strategy that draws from it, a go-to-market approach that knows exactly who it’s talking to and why — it works remarkably well. AI can execute within constraints. It can accelerate production, maintain consistency, and scale what’s already working.

On the flip side, when you introduce AI into a marketing operation that doesn’t have that foundation, the gaps become impossible to ignore. Generic output. Messaging that could belong to anyone. Content that’s technically correct and completely unmemorable. Humans have always filled those gaps intuitively — an agency establishes a strategy, a copywriter tweaks the messaging, a founder provides comments because something felt off. But when AI has to fill the gaps, judgment gets lost and the work reads like AI slop.

I learned this firsthand.

A system I had to build from the ground up, starting with my brand. Everything else — the content workflow, the client-facing tools, the social distribution — moved downstream of that. Now, if I decide to change something about my brand, I do it within the foundation layer and everything else shifts. That’s how systems work.

A quick pause before we go further. If you're new here, Purpose Plays are how I connect the ideas in a post to the work you're actually doing. This one's worth sitting with — the layers will start to take shape once you start looking.

Purpose Play

Think about your marketing right now — not the strategy you intend to build, but the one you’re actually running.

Work through the layers from the bottom up and answer honestly:

• Do you have a brand strategy — a clear articulation of who you are, who you’re for, and what you stand for?

• Does your content have a strategic logic underneath it, or is it driven primarily by what you feel like posting, writing, or talking about?

• When you take an offer to market, do you have a deliberate go-to-market approach — specific audience, specific moment, specific message?

• Are you trying to scale or grow? If so, what part of your business are you trying to accelerate? Did you already validate the approach?

→ Marketing Tip: You don’t need to be running all of the systems. Just knowing which layer you’re on — and which ones you may have skipped — is the most clarifying thing you can do right now.

Free Your Mind

My point: If you take anything away from this post, know that marketing doesn’t feel overwhelming because you’re doing it wrong. It feels overwhelming because you’ve been handed the pieces without any instructions about how they relate.

Here’s what changes when you understand that: you stop asking “which of these things should I be doing?” and start asking “where is my system breaking down?”

That’s the question that actually moves things forward.

You can see where you are. You can see what’s missing. You can see what’s ready to move and what isn’t.

And, once you see that, you can’t unsee it.

About the Work

I’m Amy Zwagerman—brand strategist, fractional CMO, and founder of The Launch Box. I work with founders and marketing leaders to translate durable marketing principles into strategies and systems that fit their specific context, stage, and goals.

Marketing Jam sits alongside my client work as a place to explore ideas more openly. If the thinking here resonates and you’re curious about working together, you can learn more about my services or get in touch here.

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Integrity Pledge 🙋🏻‍♀️: The books, newsletters, shows, podcasts, and client work shared here are 100% reflective of my world. I will always disclose if and when I have a relationship with a brand I mention in a post or am sharing an affiliate link.

TL;DR

If you’re trying to figure out how AI fits into your own business, you’re in the right place. What follows is not an AI plan for you to replicate. It’s me naming the top 5 strategic choices I’m making—and why. My hope is that seeing these decisions will help you get clearer about your own.

1. Commit to an intentional AI learning path 🧠

2. Shift from prompt optimization to systems thinking 🔄

3. Treat AI governance as a non-negotiable 🛡️

4. Tie AI experimentation to real business outcomes 📊

5. Design AI-enabled work that firmly keeps humans in the loop 🤝

This is a longer reflection because these aren’t surface-level choices — they’re the ones that shape how AI actually shows up in a business over time.

Introduction: Why I’m Thinking About 2026 Now

I want to start by being upfront about where my head is at: I’m one of those all-in on AI people. Not as a fun tool to play with. Not as something to keep on the periphery. Not as an employee replacement. But as a technology I’m taking seriously—and using intentionally—inside my business.

Over the past year, I’ve gone from experimenting with AI to integrating it into how I actually work. Mostly in practical, unsexy ways: staying organized when I’m juggling multiple creative projects (all hail Notion), capturing conversations so I can stay present (my AI note-taker has changed my life), and accelerating work that used to slow me down (custom GPTs for the win). And in doing that, I’ve learned something important: the real work isn’t figuring out what AI can do—it’s deciding where it earns its place.

What’s changed recently is the urgency of that decision.

AI adoption isn’t theoretical anymore. It’s already woven into how work gets done, especially in marketing.

The question for business owners like me is no longer “Should I use AI?” but “How do I use it without losing the plot?”

So I’ve been getting explicit about my own decisions.

Decision 1. What Do I Need to Know?

The first thing on my 2026 AI strategy is “create a learning plan.” The genesis here is that I can’t make a statement like “I’m all-in on AI” and continue to ‘wing it’. The two concepts are at best an oxymoron and at worst, a recipe for disaster.

Don’t get me wrong. Experimenting with AI got me far. I just believe the next gains will come from learning more advanced capabilities on purpose—like how to think like a systems engineer and build agents.

And that requires a plan.

Right now, my goal is simple: get fluent enough to direct the technology instead of working around it. Once I reach that point, the plan will evolve. There will be another layer to learn, another capability to focus on. That’s fine. The point of my AI learning plan isn’t mastery—it’s intentional progression.

Purpose Play

For those who are new here, a Purpose Play is my way of helping you connect what I’m writing about to your own business. It’s a moment to step back from the ideas, check for alignment, and consider whether—and how—something applies to the work you are doing.

Take a beat and think about your own use of AI. Are you a novice, experimenter, or expert practitioner? What would change if you made time to learn the next level on purpose?

Decision 2. Build a Better Mousetrap

Once I’ve mastered systems thinking, I want to start connecting the literal dots of my business. Think Elle Woods—focused, confident, and all about AI workflow management.

Yes, having killer prompts is still going to be important. Custom GPTs, saved prompts, structured inputs—those things have all made my work faster and cleaner. But, big picture, they are helping to optimize my outputs.

So, instead of asking, “How do I get a better answer?”, I’m asking, “What’s the actual workflow here—and where does it break?” Where does momentum stall? Where does context get lost?

When I think this way, I see the architecture shifting in real time. AI unlocks something new that I haven’t quite put my finger on yet → that’s why this is my #2 focus. I need to explore what’s possible.

Decision 3. Ignorance is Not Bliss

Once systems enter the picture, the risks do too — and pretending otherwise isn’t a strategy.

I am generally more of a ‘cover your ass’ than an ‘act first and apologize later’ kind of girl, so, after spending much of January listening to experts talk about the state of Marketing AI in 2026, it’s no surprise that AI governance moved to the (almost) top of my to do list.

For anyone who isn’t familiar with the term, here’s a quick description from IBM:

Artificial intelligence (AI) governance refers to the processes, standards and guardrails that help ensure AI systems and tools are safe and ethical. AI governance frameworks direct AI research, development and application to help ensure safety, fairness and respect for human rights. (IBM)

For me, AI governance means moving beyond my current AI policy to account for broader ethical considerations. More specifically, it means thinking through questions like:

• How I document what I’m using AI for so it’s not invisible or ad hoc

• What happens when a workflow breaks, a tool changes, or an output is wrong—who owns that moment?

• What “human review” actually means in practice (and when it’s required, no exceptions)

• What I’m comfortable automating when trust is on the line

• How I stay accountable for tone, intent, and meaning when AI touches the work

Right now, I have a framework for how I use GPTs in my business—what they are and aren’t allowed to do, and who gets access based on where they sit: private, business-facing, or customer-facing. I also operate with a few non-negotiables around my use of AI: verifying factual data, protecting proprietary information, and transparency around use.

But those guardrails only cover so much, and, as I move into this next phase, I need to define a governance strategy that reflects how big of a role I’m giving AI in my business.

Purpose Play

Think about where AI is already touching your work today—are you currently using it to ideate, summarize, organize, draft, respond, or decide anything? If someone asked you to explain how you’re using AI and where human judgment steps in, could you answer clearly?

→ Psst: You probably don’t need a formal AI governance policy yet. But noticing where things feel fuzzy is usually the first signal that a line needs to be drawn.

Decision 4. Innovation Has to Earn Its Keep

This choice is all about practicing what I preach. I mean, I’m a marketing advisor, so tracking outcomes is always a priority.

The big idea: If I’m going to invest time and energy integrating AI more deeply into my business, it has to be tied to a real use case with a clear objective. Or, more specifically, I need to know what problem I’m trying to solve, what “better” actually means, and whether AI is helping me get there. Otherwise, it’s just an activity.

So, before I build anything, I’m tasking myself with being explicit about the objective and what success looks like. This means more questions:

• What is this supposed to make faster, clearer, or more consistent?

• What part of the workflow is it meant to improve?

• How will I know if it’s working—or if it’s just creating noise?

What I want are proof points. Clear examples of where AI actually changes how the business operates for the better. Over time, those experiments become case studies—not to show off, but to build conviction about where AI belongs and where it doesn’t.

Decision 5. Design Work That Keeps Humans in the Loop

As I think about integrating AI more deeply into my own workflows, I’m also clarifying how that thinking shows up in the services and programs I build for others. Not to teach people how to use AI in the abstract—but to help them use it the way I’m using it: strategically, intentionally, and with clear guardrails.

That distinction matters to me.

So the work I’m doing—and want to do more of—is helping people design their own AI systems with the end in mind. Systems that start with objectives, not tools. Systems that respect where human judgment needs to stay in the loop. Systems that make work feel more grounded, not more automated.

This isn’t about scaling AI. It’s about scaling good work—with AI in support, not in charge.

Purpose Play

Consider how AI is currently being incorporated in your own work. Does it genuinely make things feel easier or clearer, or does it subtly make you second-guess yourself? Is there a process you might need to fine tune?

Wrapup: Choosing Intention Over Acceleration

What I keep coming back to is this: being “ready” for AI isn’t about having the perfect plan.

It’s about being willing to make decisions.

Decisions about what you’re learning and why.
Decisions about how work flows, not just what gets produced.
Decisions about where guardrails matter.
Decisions about what success actually looks like.
Decisions about where human judgment stays firmly in the loop.

None of this is fixed. I expect these choices will evolve as the technology changes and as my business grows. But not making them isn’t neutral—it’s a decision too. And choosing to rely on the default settings, tools, and trends is not for me.

So this is where I’m landing right now.

Not with a master plan, but with a clearer sense of how I want to approach AI at the beginning of 2026.

If you’re thinking about how AI fits into your own business, my hope is that this post inspires you to pause and decide what your choices are.

Where This Thinking Shows Up Next

If going deeper with AI is on your 2026 action plan, here are a few ways you can explore it further with me:

• I am co-teaching two workshops on AI-powered growth marketing in entertainment, media, and sports through Pepperdine Graziadio at the end of this month. These sessions will be practical, hands-on, and focused on using AI to support real marketing work, not just talk about it. Learn more and register: Feb 25 or Feb 27.

• I’m building something new called The Brand + AI Jumpstart. It will be a first step for founders and marketing leaders looking to integrate AI into their brand and marketing systems with intention. Message me to learn more.

• I’ve just applied to do research on AI-mediated voice for a symposium in Switzerland this summer. If I’m selected, I’ll be on the hunt for people who are both a yes and a no on using AI as an extension of their personal brand. Reach out if you are interested in participating.

About the Work

I’m Amy Zwagerman—brand strategist, fractional CMO, and founder of The Launch Box. I work with founders and marketing leaders to translate durable marketing principles into strategies and systems that fit their specific context, stage, and goals.

Marketing Jam sits alongside my client work as a place to explore ideas more openly. If the thinking here resonates and you’re curious about working together, you can learn more about my services or get in touch here.

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Integrity Pledge 🙋🏻‍♀️: The books, newsletters, shows, podcasts, and client work shared here are 100% reflective of my world. I will always disclose if and when I have a relationship with a brand I mention in a post or am sharing an affiliate link.

Hi, I’m Amy Zwagerman—Founder of The Launch Box, marketing mentor, educator, and Fractional CMO with 25+ years of experience helping entrepreneurs find their marketing zwagger (and clarity). If you want custom strategy without the cookie cutter feel, you’re in the right place.

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TL:DR

Confused by marketing metrics like ROAS, CAC, and AOV? This guide breaks down the numbers that actually matter—when to use them, how to track them, and why they’re critical at different stages of growth. Skip ahead to:

• ROAS breakdown → “What Is ROAS (and Why It’s Not Just for Ads)”

• Metric cheat sheet → “The Other Metrics That Actually Matter”

• Stage-specific guidance → “Which Metrics Matter Most for You”

• Optimization tips → “How to Stop Getting Lost in the Numbers”

If terms like ROAS, CAC, and LTV make your eyes glaze over—you’re not alone. But if you’re trying to grow a business, you do need to know what they mean (and when they matter). The good news? You don’t need a marketing degree to understand the numbers. You just need a little context, a clear goal, and a solid strategy.

Let’s break down the most important marketing metrics (and their acronyms) in plain English now...

First, What Is ROAS (and Why It’s Not Just for Ads)

ROAS = Return on Ad Spend

Formula: Revenue generated ÷ Ad spend

Let’s say you spent $500 on Instagram ads and made $2,000 in sales. Your ROAS is 4:1. That means you earned $4 for every $1 you spent.

Not bad, right?

But here’s the part most founders miss: Are you paying a social media manager or an ad agency to help you? I’m sorry, but those costs count too. If you only include ad spend and ignore the people behind the work, your numbers are lying to you. Yes, it might sting—but awareness brings clarity, and clarity fuels better decisions.

Despite its celebrity status in marketing circles, ROAS is just one part of a much bigger picture. It tells you how your paid efforts are performing—but not what’s fueling long-term growth.

And ROAS is not a helpful metric if:

• You’re still building brand awareness – ROAS doesn’t measure visibility or audience growth. Those early impressions may not convert right away, but they’re still valuable.

• You’re testing new campaigns or channels – Expect lower ROAS while you experiment and learn what works. That’s normal—and necessary.

• You’re measuring organic performance – ROAS applies only to paid efforts. For organic, focus on metrics like engagement, growth rate, and conversion.

The Bottom Line: Consider ROAS as one way to measure your ad spend—not the only way. It’s most powerful when evaluated in context—alongside your broader ad strategy, goals, and stage of growth.

The Other Metrics That Actually Matter

Let’s face it: marketing is full of jargon—and acronyms like ROAS and CAC can feel like insider baseball for the ultra-indoctrinated. But just because they sound wonky doesn’t mean they’re superfluous. These metrics matter in the real world—and they can absolutely help you make better decisions, faster. So here’s a clear, founder-friendly round-up of the ones worth paying attention to (listed in alphabetical order, because, yes, in addition to being a #marketingnerd, I am a wee bit OCD):

AOV – Average Order Value

Formula: Total revenue ÷ Number of orders
Shows how much your customers spend on average per purchase. Useful when testing pricing or bundling strategies.

CAC – Customer Acquisition Cost

Formula: Total marketing spend ÷ Number of new customers
Tells you how much it costs to acquire one paying customer. Include ad spend, salaries, software tools, and agency fees.

Churn Rate – Rate of customer loss

Formula: (Lost customers ÷ Total customers at start of period) × 100
A high churn rate means people are leaving. Keep an eye on this, especially if you're subscription-based.

CVR – Conversion Rate

Formula: (Conversions ÷ Total visitors) × 100
Tells you how effective your marketing is at getting people to take action—like buying, signing up, or booking a call.

CTR – Click-through Rate

Formula: (Clicks ÷ Impressions) × 100
Measures how many people clicked on a link after seeing your ad, email, or post. It’s a good early indicator of interest.

Growth Rate – Rate of increase (can be used for any key metric)

Formula: ((Current period value − Previous period value) ÷ Previous period value) × 100
Used to evaluate momentum in your business or marketing performance.

LTV – Lifetime Value

Formula: Average purchase value × Number of purchases per customer per period × Average customer lifespan
Reveals how much a customer is worth over time. The higher your LTV, the more you can afford to spend on acquisition.

Net Revenue Per Customer – Your actual profit per customer before overhead

Formula: AOV − CAC
This shows how much you're really making once you subtract what it costs to acquire a customer.

Retention Rate – Percentage of customers who stick around

Formula: ((Customers at end of period − New customers) ÷ Customers at start of period) × 100
High retention = strong brand loyalty.

The Bottom Line: You don’t need to master every acronym, but knowing these key formulas puts you back in control. Use them to guide smart decisions—not to stress yourself out.

Which Metrics Matter Most for You?

Not every metric matters equally at every stage—but there are smart indicators that can help you track what matters most to you at any given time. Here is how I tend to look at things:

→ If you're just starting (awareness + learning phase):

• Reach – Track impressions, followers, or views to gauge visibility.

• CTR (Click-through Rate) – Understand how often people are engaging with your content.

• CVR (Conversion Rate) – Track early signals of action (signups, downloads, etc.).

• Qualitative feedback – DMs, replies, and survey results help refine your message.

→ If you're growing (testing + optimizing phase):

• CAC (Customer Acquisition Cost) – Measure how much you're spending per customer.

• AOV (Average Order Value) – See how much each customer is spending.

• ROAS (Return on Ad Spend) – Evaluate how your paid media is performing.

• Net Revenue Per Customer – Identify actual profit after acquisition costs.

This is your optimization stage—improving results, tightening your funnel, and preparing to scale.

→ If you're scaling (efficiency + expansion phase):

• LTV (Lifetime Value) – Understand customer longevity and worth.

• LTV:CAC Ratio – Assess acquisition sustainability (3:1 is ideal).

• Retention Rate + Churn Rate – Know how many customers stick (or leave).

• Growth Rate – Measure month-over-month or year-over-year momentum.

• Net Revenue Per Customer – Ensure you're profitable at scale.

• ROAS (cross-channel) – Review and optimize channel-specific spend.

You’re looking for cost-effective growth, strategic clarity, and investor-friendly metrics at this stage.

The Bottom Line: Metrics only matter when paired with context and intention. Know where you are, what you’re trying to achieve, and measure accordingly.

💁🏻‍♀️Pro tip: Seeking funding? Investors love metrics like LTV:CAC, Runway, and Payback Period. Get the full breakdown of these (plus other investor favorites) inside my free Marketing Metrics Cheat Sheet. More info. below ⬇️

How to Stop Getting Lost in the Numbers

Your job as a business owner isn’t to memorize every marketing metric and acronym. It’s to stay focused on the right metrics for your business goals—and know how and when to use them.

Need leads? Track CPL. Trying to raise your prices? Improve AOV. Running ads? Check ROAS—but also watch CVR and CAC.

But here’s the real secret: while you should always be tracking everything, you can only optimize one thing at a time.

For example, here’s how I would recommend you analyze a new digital marketing campaign:

• If you're running ads on social media and you're seeing strong reach but low engagement (CTR), it’s a messaging problem. Test new headlines, hooks, or formats.

• If you have strong engagement, but people aren’t converting (CVR is low), check what they’re landing on. Is the offer clear? Is the next step obvious?

• If you’re seeing good CVR but a high CAC, then it’s time to look at your audience targeting, pricing, or spend efficiency.

Campaigns rarely succeed or fail at one step. The magic is in seeing where people are dropping off—and optimizing that single moment before moving on.

The Bottom Line: Building a brand takes intention—and iteration. Making marketing decisions based solely on sales velocity is like flying blind. The metrics we’ve covered aren’t just industry jargon—they’re strategic clues. They show you what’s working, what’s not, and where to focus next so you can lead with insight instead of guesswork.

💁🏻‍♀️Pro tip: Get in the habit of tracking your metrics weekly. Why? Because that’s the only way to know if the tactics—and tweaks—you’re making are actually working. Over time, these numbers become more than reports. They become your radar. You’ll start to spot patterns, catch shifts early, and course-correct before a campaign stalls, sales dip, or inventory runs dry. Metrics don’t just show you what happened—they help you anticipate what’s coming.

Want to go deeper?

This article covers the must-know metrics for growing your business—but if you're ready to nerd out (just a little), I've got you covered with my Marketing Metrics Cheat Sheet. It’s your go-to dashboard for making data-driven decisions without drowning in analysis paralysis. Perfect for founders, marketers, and anyone who wants to track smarter (not harder).

→ Grab the Marketing Metrics Cheat Sheet — a Google Sheets file that includes

• All the key metrics (+ the Investor stats I mentioned earlier) in A–Z order

• A sortable list by use case (think: awareness, sales, efficiency, retention)

• A breakdown by business stage (Start, Grow, Scale, Fund)

Think of it (and me) as your CMO in spreadsheet form—minus the salary. 👩🏻‍💻

Wrapping It All Up

Understanding marketing metrics doesn’t have to be overwhelming. With the right context, a solid strategy, and a commitment to focusing on one area of improvement at a time, you can turn data into direction. Whether you’re just getting started or preparing to scale, what matters most is using metrics as tools, not rules. Your numbers are here to guide you—not stress you out.

So take a breath, pick one place to start, and begin measuring what matters most for your brand.

Your Turn: Which of these metrics are you tracking—or finally starting to understand—in a new way? Drop a comment, hit reply, or DM me and let me know what’s clicking (or what still feels confusing).

AI-supported, human-led. All ideas and insights are my own. Curious how I use AI and where I draw the line? See my AI Disclosure Policy →

Editor's Note: This is an old blog post I did about StrengthsFinder back in 2021. I’ve added it to Marketing Jam because I referenced the story in a recent post and I want people to have access to the information. I've left it exactly as written even though it pains me to see how I was hiding behind the collective 'we' as the author. As I read it now, I am reminded of Smeagol from Lord of the Rings -- and not in a good way. 🤦🏻‍♀️

This week we want to talk about a management philosophy we stumbled upon around a decade (or two?) ago called StrengthsFinder that we see Gallup has re-branded as CliftonStrengths. At it’s core, StrengthsFinder, or SF as we’ll call it from here on out, is an assessment tool for identifying a person’s innate strengths, i.e., the things they naturally do well. Additionally, the bigger idea behind the assessment tool is that people should focus on leaning into their strengths versus trying to shore up their weaknesses.

The reason we like SF so much — aside from the obvious point above — is that once someone is aware of their strengths, they are able to simultaneously focus on doing the things they are good at and stop wasting time on the things they are not. Of course, we aren’t advocating (and neither is SF) that success will come to those who ignore everything they are bad at, but, rather, that people stop trying to overcome their intrinsic weaknesses and focus instead on finding other ways to fill the gaps. More specifically, the theory tells us that creating teams of people with opposite, or perhaps more accurately, complementary skills will create an environment where everyone can be more successful. Whoa — opposites really do attract — minds blown!

We know this makes our blog post 100% self-serving, but that last point is honestly what gets us up in the morning. It’s our mission to help businesses of all shapes and sizes succeed, so we absolutely love the idea of bringing other people’s ideas to life by serving as the marketing yin to their entrepreneurial yang. Additionally, we’d like to suggest that if you don’t yet know what you are most brilliant at, you should take the SF quiz and figure it out pronto!