The Biggest Marketing Challenge Small Businesses Face

Patrick McFadden • May 4, 2017

Every business owner faces different challenges, wears many hats and makes many decisions each day. Although we typically share similar goals, some businesses are stuck on hiring the right people, increasing sales, making payroll, filing taxes and providing remarkable customer service.

Whatever the case may be, there’s always at least one area that you can stand to improve.

According to a survey conducted by Alignable the biggest marketing challenge for small businesses is that they don’t have enough leads, and getting more leads is also their number one goal.

These results aren’t at all surprising to me as I hear this all the time. For business owners of small companies the two biggest concerns in lead generation are cost (as free cash is comparatively limited) and return on investment (as ineffective strategies waste significant time and resources). That’s why I’ve come up with this list of three effective, and proven lead generation strategies any small business owner can use to increase leads.

1) Strategic Networking

I know everyone tells you that you must be networking today, but simply attending any event on a Thursday and fumbling through your first impression is what leads to ineffective networking. You must network, but you must do it strategically.

The truth about networking that no one wants to admit is that it’s hard work. While the barrier to connect today is low, the barrier to trust and attention is high.

To succeed at networking you must consistently engage with 3 defined groups:

  1. Prospects – These are the people who connect with you personally first, and then in some way raise their hand or show interest in your firm, product or service. This may be in the form of asking for your business card, setting up a time to connect outside the networking event and/or asking specific product/service related questions.
  2. Strategic Partners – These are companies you don’t compete with but both target and call on the same type of ideal client. If you’re a merchant services firm targeting medical practices, then your strategic partners might be medical office cleaning companies, printing supply companies, HR companies, group benefits companies, marketing companies, payroll companies, etc.
  3. Existing Clients –  These should be happy clients that are willing to go out of their way to make strategic introductions for you. Also, engaging existing clients at networking events should be viewed as another customer touchpoint that can build trust (or erode it) and help reaffirm the smart choice they made by hiring your solution.

Identify five people who you know you can help and would appreciate your help, then reach out and offer to do something very specific to help them . Super success comes from engaging these groups in a way that provides and contributes value, relevancy and meaning. The bonus would be to achieve this without adding costs to the others.

2) Answer Prospect and Client Questions

The reality is that prospects are becoming more self-educated and complex, requiring more educational points of contact and information as they move from a “suspect,” a member of your target market you suspect needs what you offer, into a prospect – one you know needs and wants what you have to offer.

To make answering questions pay as a lead generation source you must first understand that when a prospect needs to solve a problem today, they search online proactively gathering information and you must show up there; leading the competition in the search results – just waiting to be clicked so you can deliver your offer to a prospect.

Here’s the easiest way to go about doing that. Search your requests and emails, then make a list of the top 10 questions you get asked from prospective and current customers. For an example, here’s the top questions I get on Quora:

Now, go about planning the resources needed to turn each of those questions into a piece of content – blog post, workshop, seminar, FAQs document, marketing material, or newsletter topic.

3) Teach and Educate

For many service based business owners, the most effective lead generation strategy  involves workshops, seminars and webinars. Teaching and educating requires that your organization give and in doing so build the trust needed for your target market to take a step or action that essentially signals you have permission to sell to them.

During this time, you need to tell stories, share examples of other people’s success and start to paint a picture of how you can solve your customer’s problem. Teaching and educating is a great way for prospects to relate to you as someone who delivers value, without the exchange of money.

When you develop a reputation for being someone who can  teach people , then you get invited to places where you have the opportunity to sell.

P.S. Good blogging is a form of teaching.

The real point here is that you’ve got to execute a variety of different lead generation strategies , working together, in order to create a lead generation snowball effect.

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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