6 Content Marketing Tips for Midsize Financial Institutions to Get Attention Money Can’t Buy

Patrick McFadden • October 30, 2013

Do you ever feel like you’re the only marketer who has trouble creating and distributing quality content that get’s people attention and that yields measurable results? If so, you’re not alone.

Given the speed at which Midsize Financial Institutions create, distribute and consume content that references all the tips telling us how to save money and stretch our dollar, it’s no surprise that there’s room for improvement.

Here you will find  6 Content Marketing Tips for Midsize Financial Institutions to Get Attention Money Can’t Buy:

#1. Help Your Customers GROW Their Money.
Right now, most Financial Institutions are likely posting countless “savings” tips and “stretching” tips. Stop doing this and go the opposite way. Instead, give your customers ways to grow their money. Talk about interest rates, talk about CDs and get into the specifics. Instead of saying, “Pay yourself first”. You should say: “CD rates are at a record high. Putting in $200 dollars today will give you $xxx in 3 months.” See what you did there, you promoted a product without promoting a product and you told your audience how to MAKE money. Same concept, different delivery.

#2. Let’s Hear From Your Brand = The Talent.
Your Midsize Financial Institution is full of intellectual capital about money, the economy and investing. If you didn’t know, people like hearing about money. They want to find ways to get more money (see above) but they also want to know what the experts in the field are reading and looking at. Leverage your intellectual capital! Drive your customers to the articles, newsletters and ebooks your experts are reading. This is adding value to prospects and customers and is also a huge brand differentiator.

#3. Care About What Your Customers Care About.
Shared passions can create an increase in engagement and following. This is a not new. But, in doing so, your Midsize Financial Institution must be authentic. So, if your customer LOVES the St.Louis Cardinals and you have content that celebrates their season and accomplishments, Your customers are going to engage because they love the same thing. So, take a good hard look at your sponsorships. And ask; how can your Midsize Financial Institution leverage those relationships to build compelling content for our collective fans and grow your affinity with your shared passion. Posting the score might even be enough!

#4. Help Your Customers Feel Good.
Banks, although sometimes they may seem the same, are very different in terms of brand personality. It is hard to change banks, so people rarely do it. But when your prospect does choose you, remind them occasionally of your values. What is important to you. And if you can show them don’t tell them. Small Business Saturday is a great reason for your customers to feel good about choosing you. Help your customers by sharing content that shows them your values and how you improve the world/community/neighborhood.

#5. Listen to Your Customers.
Your customers have ideas. You should be open to them. Simple!

#6. Be Interesting or Be Invisible
When you have earned the right to talk about yourself, spend those precious words and images being clever and interesting. Overlay some pop culture, use a real-time approach, but if anything else be remarkable. Worth making a remarkable about.

If you consistently tell a true story about your company, product, service, or idea that resonates with the worldview of a group of people, that “world” will eventually beat a path to your door.

Note: In writing this post I looked closely at some of the most successful  Financial Institutions from The Financial Brand Power 100. These content marketing tips are things that are working in terms of growing a following and generating awareness and engagement for both large and small brands.

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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