The Midsize Business Formula for Social Media Success

Patrick McFadden • November 20, 2013

Admit it. It sucks to work hard on your social media and have no real results to show for it. Let’s discuss …

If you’re trying to sell products and services, gain visibility, become part of the conversation and build brand awareness, all online, you’re probably looking for that one magic formula to make your midsize business social media work.

Many seek the simple factors for social media success.

So here it is:  The Midsize Business Formula for Social Media Success 

Social Media Success Ingredient #1: Transparency

It turns out that transparency increases profitability. Are transparent as an organization. When consumers get used to transparency, they’re also more interested in the quality of what you sell, and are more likely to willingly pay extra.

Social Media Success Ingredient #2: Assortment

Become familiar with cross-platform marketing and employ an assortment of social media tools (blogs, mobile apps, online video channels). One social media ad, in a vacuum, is usually not enough to convert a target audiences.

Social Media Success Ingredient #3: Investment

Social media is not an expense, but an investment. And it’s certainly isn’t a free strategy. Social media requires investment to yield measurable results, even if it’s in the form of employee time. Social media spending includes staff, technology, marketing agency fees, consulting services and other costs.

Social Media Success Ingredient #4: Centralization

You should be centralizing your social media function at the corporate level. You should have a small core social media team focused on social media strategy, best practices and metrics that they leverage across the organization. Social media staff matters!

Social Media Success Ingredient #5: Involvement

This describes the relationship between you and your employees — and it is a relationship. You prove your involvement by asking for their input; they prove theirs by being focused on what’s being said on social media. For an effective social media strategy, you need at a minimum, the 3 front line functions, namely, marketing, customer service and sales.

Social Media Success Ingredient #6: Control

Marketing controls social media. Marketing is everything you do or say. And you’re saying a lot on social media platforms. Simple!

Social Media Success Ingredient #7: Measurement

“What gets measured gets managed. ~ Peter Drucker” You can actually double or triple your profits by measuring the results of your social media marketing. Some marketing tactics hit your target right in the middle. Others miss it completely. Unless you measure, you won’t know which are which. You must track your marketing to ensure that it yields sales and profits.

These are important ingredients to follow when running a successful social media campaign. However, I believe these ingredients aren’t the only ones and could be improved or substituted.

Question: What do you think? Do you have some ingredients of your own? What successes have you had with social media? Please share some of your own ingredients.  

About the Author:  Patrick McFadden is a marketing consultant/coach for small businesses and midsize organizations. He’s also an  American Express OpenForum Advisor. He develops highly tailored marketing plans and strategies that increase your customers and maximize profits.

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