10 Questions to Ask Before You Create a Marketing Strategy

Patrick McFadden • June 28, 2017

So you’re ready to take a more process approach in your marketing efforts, but you’re not sure where to start…

You’ve come to the right place. Marketing strategy must come before tactics and these 10 questions will help guide you through the process.

From overall characteristics about ideal clients to logistics about measurement and offers, these questions walk you through the steps you should take prior to hitting “go.”

For example, it may help to know that your clients real problem is cash flow and the value they get from your solution is getting paid faster.

Bottom line: the goal of a marketing strategy is to increase business and grow awareness of your organization.

Here are the 10 questions to ask before creating your marketing strategy.

#1. Who is your ideal customer?

This question helps you focus in on your sweet spot. Ideal can mean many things — who can you deliver the greatest value to, who do you enjoy working with, who needs what you do most. Give some thought to how you might reach them and appeal to them. Use your most successful accounts to date to help you think about what makes them ideal for you. (Hint: they are profitable and talk about you.)

#2. What core problem do you solve for ideal customers?

Think about what your customers core problem is. This question lets you discover the real value about you, your services/products and your company. Write a description of the problems you solve for ideal clients.

#3. Who are your primary competitors?

If you’re going to war, you must know your enemy. Smart marketers employ some form of competitive research in an effort to better understand what products and services, pricing models and value propositions they are up against.

#4. What is your primary competitive advantage?

Trying to figure out how to be better than the competition — better product, better service, better features, and better price is worthless. In my opinion focusing on building a better process or better relationships is the surest and maybe simplest way to create a true competitive advantage that someone might care about.

#5. What is your lead offer to first time customers?

Today’s shift in buying now demands a very tangible way prospects can experience your offer. Buyers want an understanding of what they’re potentially buying, and they want it right away — essentially a buyer wants the opportunity to see and experience a service/product in action very early on. The answer is offering prospects a way to sample your expertise, product or service. This can be in the form of free consultations, money-back guarantees, demos, seminars, proof of concept, audits, trail offers, assessments, etc.

#6. What is your maximum cost to acquire a new customer?

I think the cost of acquiring a new customer is one of those data points that is critical to understand in any business. Once you understand the lifetime value of a customer, you can determine how much you’re willing to pay in new customer acquisition costs. For example, if the lifetime value of your average customer is $1,000, anything you spend under that in new customer acquisition costs will be profit — or the marginal net worth of your average customer.

#7. How many new customers you can handle per month?

The customer experience is everything today. You must make sure your organization is equipped to handle incoming request and on-boarding new clients. Ruin this in a social driven world and you’re doomed.

#8. How do you ensure prompt follow-up on sales inquiries?

Lack of a process approach to selling is the biggest weakness for most small businesses. Installing a sales process, one that everyone involved in selling in the organization operates, is the fastest way to improve overall results. I’ve seen lead conversion rates go from 3% to over 50% when all of the parts of a marketing and sales process work together.

#9. What target keywords do you want to rank in Google?

Keyword research has long been the primary tool for search engine optimization plans. The idea was that you found out what people in your industry were searching for and you optimized your site and pages to try to show up on page one — pretty simple. Today, I believe that content is the primary tool for optimizing your effectiveness is just about every channel your clients use — it’s the key to SEO, social media sharing, referrals, email marketing and even online and offline advertising.

#10. How do you measure marketing investments?

Management consultant extraordinaire Peter Drucker famously said, “What gets measured, gets managed.” Now, while terms like measurement and management might seem like big company jargon, the fact is you can’t successfully grow a business unless you track what works and what doesn’t work.

We suggest using Google analytics or vendor specific analytic tools to measure your marketing. It gives real-time reporting on social media, inbound links, seo, keywords and Pay per click marketing campaigns.

Conclusion

When asked to come into a business and evaluate marketing activities for growth or make marketing recommendations — this is where I start because this is where all the answers reside.

The Missing Layer in AI: Why Judgment, Not Just Data, Will Define the Next Era of Intelligence

By Patrick McFadden • May 2, 2025
Everyone is scaling outputs. Almost no one is scaling judgment.

Everyone Talks About AI Judgment. We Built It.

By Patrick McFadden • May 2, 2025
Ask anyone in tech where AI is headed, and they’ll tell you: “The next leap is reasoning.” “AI needs judgment.” “We need assistants that think, not just answer.” They’re right. But while everyone’s talking about it, almost no one is actually shipping it. So we did. We built Thinking OS™ —a system that doesn’t just help AI answer questions… It helps AI think like a strategist. It helps AI decide like an operator. It helps teams and platforms scale judgment, n ot just generate output. The Theory Isn’t New. The Implementation Is. The idea of layering strategic thinking and judgment into AI isn’t new in theory. The problem is, no one’s been able to implement it effectively at scale. Let’s look at the current landscape. 1. Big Tech Has the Muscle—But Not the Mind OpenAI / ChatGPT ✅ Strength: Best-in-class language generation ❌ Limitation: No built-in judgment or reasoning. You must provide the structure. Otherwise, it follows instructions, not strategy. Google DeepMind / Gemini ✅ Known for advanced decision-making (e.g., AlphaGo) ❌ But only in structured environments like games—not messy, real-world business scenarios. Anthropic (Claude), Meta (LLaMA), Microsoft Copilot ✅ Great at answering questions and following commands ❌ But they’re assistants, not advisors. They won’t reprioritize. They won’t challenge your assumptions. They don’t ask: “Is this the right move?” These tools are powerful—but they don’t think for outcomes the way a strategist or operator would. 2. Who’s Actually Building the Thinking Layer™? This is where it gets interesting—and thin. Startups and Indie Builders Some small teams are quietly: Creating custom GPTs that mimic how experts reason Layering in business context, priorities, and tradeoffs Embedding decision logic so AI can guide, not just execute But these efforts are: Highly manual Difficult to scale Fragmented and experimental Enterprise Experiments A few companies (Salesforce, HubSpot, and others) are exploring more “judgment-aware” AI copilots. These systems can: Flag inconsistencies Recommend next actions Occasionally surface priorities based on internal logic But most of it is still: In early R&D Custom-coded Unproven beyond narrow use cases That’s Why Thinking OS™ Is Different Instead of waiting for a lab to crack it, we built a modular thinking system that installs like infrastructure. Thinking OS™: Captures how real experts reason Embeds judgment into layers AI can use Deploys into tools like ChatGPT or enterprise systems Helps teams think together, consistently, at scale It’s not another assistant. It’s the missing layer that turns outputs into outcomes. So… Is This a New Innovation? Yes—in practice. Everyone says AI needs judgment. But judgment isn’t an idea. It’s a system. It requires: Persistent memory Contextual awareness Tradeoff evaluation Value-based decisions Strategy that evolves with goals Thinking OS™ delivers that. And unlike the R&D experiments in Big Tech, it’s built for: Operators Consultants Platform founders Growth-stage teams that need to scale decision quality, not just content creation If Someone Told You They’ve Built a Thinking + Judgment Layer™… They’ve built something only a handful of people in the world are even attempting. Because this isn’t just AI that speaks fluently. It’s AI that reasons, reflects , and chooses. And in a world that’s drowning in tools, judgment becomes the differentiator. That’s the OS We Built Thinking OS™ is not a prompt pack. It’s not a dashboard. It’s not a glorified chatbot. It’s a decision architecture you can license, embed, or deploy— To help your team, your platform, or your clients think better at scale. We’ve moved past content. We’re building cognition. Let’s talk.

We Found the Missing Layer AI Has Been Waiting For

By Patrick McFadden • May 2, 2025
In every era of innovation, there’s a silent bottleneck—something obvious in hindsight, but elusive until the moment it clicks. In today’s AI-driven world, that bottleneck is clear: AI has speed. It has scale. But it doesn’t have judgment . It doesn’t really think . What’s Actually Missing From AI? When experts talk about the “thinking and judgment layer” as the next leap for AI, they’re calling out a hard truth: Modern AI systems are powerful pattern machines. But they’re missing the human layer—the one that reasons, weighs tradeoffs, and makes strategic decisions in context. Let’s break that down: 1. The Thinking Layer = Reasoning with Purpose This layer doesn’t just process inputs— it structures logic. It’s the ability to: Ask the right questions before acting Break down complexity into solvable parts Adjust direction mid-course when reality changes Think beyond “what was asked” to uncover “what really matters” Today’s AI responds. But it rarely reflects. Unless told exactly what to do, it won’t work through problems the way a strategist or operator would. 2. The Judgment Layer = Decision-Making in the Gray Judgment is the ability to: Prioritize what matters most Choose between imperfect options Make decisions when there’s no clear answer Apply values, experience, and vision—not just data It’s why a founder might not pursue a lucrative deal. Why a marketer might ignore the click-through rate. Why a strategist knows when the timing isn’t right. AI doesn’t do this well. Not yet. Because judgment requires more than data—it requires discernment . Why This Is the Bottleneck Holding Back AI AI can write. It can summarize. It can automate. But it still can’t: Diagnose the real problem behind the question Evaluate tradeoffs like a founder or operator would Recommend a path based on context, constraints, and conviction AI today is still reactive. It follows instructions. But it doesn’t lead. It doesn’t guide. It doesn’t own the outcome. And for those building serious systems—whether you’re running a company, launching a platform, or leading a team—this is the wall you eventually hit. That’s Why We Built Thinking OS™ We stopped waiting for AI to learn judgment on its own. Instead, we created a system that embeds it—by design. Thinking OS™ is an installable decision layer that captures how top founders, strategists, and operators think… …and makes that thinking repeatable , scalable , and usable inside teams, tools, and platforms. It’s not a framework. It’s not a chatbot. It’s not another playbook. It’s the layer that knows how to: Think through complex decisions Apply judgment when rules don’t help Guide others —human or AI—toward strategic outcomes This Is the Missing Infrastructure Thinking OS™ isn’t just about better answers. It’s about better thinking—made operational. And that’s what’s been missing in AI, consulting, leadership development, and platform design. If you’re trying to scale expertise, install judgment, or move from tactical to strategic… You don’t need a faster AI. You need a thinking layer that knows what to do—and why. We built it. Let’s talk.
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