5 Marketing Lessons Small Businesses Can Learn From The 2013 Political Campaigns

Patrick McFadden • October 31, 2013

November 5 is fast approaching, and every citizen of the U.S. is eagerly waiting to choose the next leader of their city.

Fall in an election year is a time for radio ads, TV ads, banners, stickers, signage, debates, mailings, unsolicited house visits and get-out-the-vote calls. Political campaigning is one of the oldest forms of marketing and advertising and small businesses have a lot to learn from them.

Here are the  5 Marketing Lessons Small Businesses Can Learn From The 2013 Political Campaigns:

Lesson #1. Work closely with local communities and know their world-view

Communities matter and their world view matters even more. This is as true in political campaigns as it is in business. To go big, you must go small. Sure, you can focus on targeting individuals, but tapping into existing community groups and organizations (who by-the-way already have a world view) can spread your message more effectively. During any campaign, traditional advertising target individual consumers, but organizers—people who already believed in their community, who already cared very much—try to create and cultivate long-lasting relationships with neighborhood and community organizations. These groups are full of potential voters, and they turn strangers into friends, friends into voters and then… they do the most important job: turn your voters into campaigners which by the way also can be activated to provide additional support.

Take Away: In your business, this can mean providing sponsorship to local organizations like fundraisers, little league teams, and so on. A customer is great for business, but a customer who actively wants to support your business is even better.

Lesson #2. The message is more effective coming from the people who like you, who respect you, who have a vested interest in your success

Empowering community groups not only makes your job easier, it’s also more effective. That’s because messages, whether about a candidate or a product, are more likely to be considered when coming from a friend or trusted voice. In politics, this means a voter will be more receptive to a phone call or house visit from someone who shares a community affiliation than from an unrelated stranger.

Take Away: In marketing your business, this is why a positive review of a product or service from a friend is so effective. It’s also why a remark from a trusted radio personality is particularly compelling. New media channels are creating ways to be intimate and authentic in communicating with your local community.

Lesson #3.  Leave no local medium unturned

I like to think of marketing as a one-two punch. And I tell business owners all the time, “instead of believing that single marketing weapons such as advertising or a website work, know that only marketing combinations work.” It’s why we at Indispensable Marketing are crazy about cross-platform marketing. In politics, potential voters are sent mailings, called, visited in-person and presented with digital, TV and radio ads. One ad, in a vacuum, is usually not enough to convert a target audiences.

Take Away: Similarly, your small business  or organization should realize that no one medium bests all the others. Platforms don’t compete with each other, they compliment each other.

Lesson #4.  Target your supporters, not your opponents

In most localities, grass-roots campaigns grow by mobilizing supporters. Most political advertising resources are targeted at voters who are already leaning toward a candidate. In other words, a savvy Republican candidate won’t waste time trying to get Democrats to change affiliations. Rather they’ll double down on mobilizing their base to get out the vote. The logic is simple. Not everyone votes, but everyone should. Campaigns are all about making sure that people who support you actually get out and vote on election day. That’s not to say converting undecided voters and chipping off supporters from the opposing party isn’t done. But the “grass-roots” part is all about your own supporters.

Take Away: Similarly, marketers need to effectively target those who are most likely to be receptive to their product. Convincing a consumer who hates your product to buy it is not nearly as cost-effective as encouraging your existing fan base to buy your latest product or attend your latest sale.

Lesson #5. Strategy before tactics

If you’re not the front-runner, empowering your people sometimes isn’t enough. In a political race, it’s often assumed that the front-runner needs to play it safe. Don’t go too heavily on the offensive, focus on empowering your people and avoid a public embarrassment at any cost. But for those trailing in the polls, being daring isn’t an option, it’s a essential. For a candidate trailing in the polls, playing it safe can only mean safely maintaining your current numbers. The point is to increase those numbers.

Take Away: No business should be comfortable with just maintaining the status quo. It’s all about doing something that might not work, learning and growing. Brands that aspire to be the best-in-class in the market need to think big and make audacious decisions in their marketing strategy.

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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