#MidsizeWednesday: 6 Steps For Midsize Businesses to Master Social Customer Acquisition

Patrick McFadden • September 25, 2013

At Indispensable Marketing we think a lot about how we can help midsize companies address marketing and the realities of the new marketplace. We continually listen and keep up-to-date with sources that connect with midmarket business leaders about their needs and preferences. Every Wednesday we publish a post called  #midsizewednesday  to help midsize businesses take advantage of these changes to evolve and ultimately grow.

How do you turn social media into a real customer acquisition channel? In this post I’m trying to answer that question, in six steps for midsize businesses.

Converting potential prospects into customers via social media takes labor. Furthermore, a midsize businesses (or any business for that matter) customer engagement doesn’t end with the close of the sale, but that’s where it begins.

With that mindset in place the focus, then of midsize businesses should be on lifetime value. This means a very strategic approach to getting that customer to buy more from you again and talk about your products to their peers and friends because this is where the major impact of social media is— word-of-mouth. As a result, social media conversion is a constant process that requires continual refinement.

To convert prospects into customers via social media here are 6 Steps For Midsize Businesses to Master Social Customer Acquisition:

#1. You can’t hit a target you cannot see, and you cannot see a target you do not have.  Know who your prospects and potential customers are. Think as if you’re selling to a network of people. Consider outside influences, decision makers, the end-user, LinkedIn connections, Twitter Followers, FB Likes and the public. This helps your team better know your target market and craft effective content that works as marketing.

#2. Deliver independent value with content before you attempt to make the sale . Offer useful, relevant content prospects and customers search, want and need. Make this content they seek in plain English, and easy-to-understand. Specifically, give them useful service or product information, answers to their product/service-related questions, demonstrate how your product or service solves their problem, and infuse customer ratings and reviews into this process.

#3. Pricing only matters when customers and prospects can’t tell the difference between your products and services and a competitor’s.  Showcase the differences/benefits of your offering. Use the appropriate social media channel that works with the use photographs and videos. Customers need this information both pre-purchase and post-purchase because if your product doesn’t get used, customers won’t buy from you again.

#4. There’s a huge difference between action and awareness. Include contextually relevant call-to-actions to motivate prospects to act. Don’t assume potential prospects know what to do. Also, they may need to view your content several times. Content marketing works best through repetition. Repetition establishes contact and starts a relationship with the prospect.

#5. You want to know where you are going. Measure the results against your overall business goals. This means determining your metrics so that they’re aligned with your goals. You’re only allowed to decide what you want to happen before not after the marketing. Also, reviewing your analytics can capture useful information at each step of the process.

#6. Improve results through testing. Test using either A/B or test different ways of presenting your product or service for every aspect of your conversion process to determine where you can improve results. (A/B testing most commonly fails because the test itself has unclear goals, so you’ve got to know what you’re testing.)

Conversion via social media is an ongoing, work in progress where you gather incremental learning from each marketing campaign. You must continue to rinse and repeat the process to improve your results since social platforms, contexts and effectiveness change.

Question: What has been most effective in your conversion process? What challenges have you found?

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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