7 Marketing Predictions for Midsize Businesses in 2014
Patrick McFadden • September 11, 2013
Are you wondering what 2014 might look like for marketing?
How will marketing impact midsize businesses in 2014?
What if you had a glimpse into the future?
To give you a glimpse of what I think midsize businesses can expect in the next year. I’ve decided to tap my deep knowledge and expertise.
Here are my 7 marketing predictions for midsize businesses in 2014:
- Customers Trust Customers. This is nothing new, but will be more of a focus. Customers referred products and services to each other before the Internet existed. The most recent study on the topic, showed 70% of consumers trusted consumer ratings and reviews. Are you getting customers to share their experience, rate your product or service or even write a review?
- Exceed Customer Expectations. Provide remarkable service in real life (or however you interact with prospects and customers.) Nothing beats remarkable, amazing, wow service for generating positive word of mouth. Midsize companies must commit to massively exceeding customer expectations. After all, the praise you earn online almost always comes from real actions offline.
- Continued Empowerment of the Consumer. Time to give consumers the key to the car. Empowered consumers reward you with loyalty. I’m a huge advocate of any way we can use generosity and information to build businesses, sell products and support our economy. Becoming a trusted informational provider, makes the purchasing process easier and more fun, and is the reason I see the information-empowered consumer as a huge growth trend in 2014.
- Real-Time Problem Solving. Midsize businesses will move to agile marketing and real-time thinking. With communication being impacted by the internet, disgruntled customers expect answers faster through social media channels. This calls for midsize businesses need to master the art of opportunistic marketing and the art of real-time response. For that, midsize businesses need the right infrastructure and agile processes that will allow them to intuitively and immediately pick up on the marketing opportunities. They also need strategic partnerships that can adapt, react and support them in real-time as well.
- Fewer channels. In 2014, I think midsize businesses will have a nuts-and-bolts focus on getting the most out of the channels that fit their business. They will focus on fewer channels , and they’ll want to go deep in them instead of being diluted across all channels . The adage of “deep not wide” will ring true for the midsize companies that stay focused.
- Customer Engagement . In 2014 engagement strategies will be at the top of the list for midsize businesses. Making marketing activities and interactions worth participating in will be the goal. I foresee the use of different communication channels for celebrating customers by giving them a chance in the spotlight, connecting them with customer service sessions, giveaways and contests, and free product demos.
- Customize Service. Last, but certainly not least, I see customize service being something that’s a huge marketing play in 2014. Having customize service not only deepens the relationship with customers but also means that customers are also investing in the relationship. Plus this creates a lock-in effect.
So, that’s my list of 2014 marketing predictions. Do you Agree? Disagree?
What’s your 2014 marketing predication for midsize businesses?
Everyone is scaling outputs. Almost no one is scaling judgment.
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.
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.
