15 Insights into Marketing Tactics That Work

Patrick McFadden • February 28, 2014

An old adage reminds us that if you have foresight, you are blessed, and if you have insight, you are twice blessed. Here are fifteen insights to make you quadruple blessed.

When it comes to marketing in the digital age, knowing what works and what doesn’t can be invaluable.

Here are the top 15 insights about modern marketing from Eloqua that you should apply to your own marketing. All these facts are from their  Modern Marketing Insights Charts.

1. Emails sent at the weekend have a better response rate.

Sending well-targeted marketing emails over the weekend results in a click-through rate of more than 25% ‒ higher than at any other time during the week. If you send mail on Saturday, you cut through the noise created by your competitors midweek.

2. Clean customer records are essential.

Outdated contact information offers no potential for revenue creation. Little surprise then that data cleansing activity has increased by 50% in firms using automated marketing techniques.

3. Short forms work best.

Web users are constantly pressed for time, so shorter registration or data collection forms work best. In fact, forms with exactly seven fields are most likely to be completed. Go beyond 10 and the completion rates tail off significantly.

(Source: Eloqua Benchmark Data, 3Q 2011)

4. LinkedIn is a B2B social marketing powerhouse.

LinkedIn accounts for 16% of all B2B social referrals – 16 times greater than in the B2C market. Facebook is also a referral powerhouse for both B2B and B2C interactions, providing 72% and 84% respectively.

(Source: Eloqua Benchmark Data, 2010 Full year)

5. Static content no longer satisfies consumers.

Marketers who serve dynamically generated content to their contacts enjoy a 50% higher conversion rate compared to their competitors who rely on static pages.

6. Automation gets people into your webinars.

Automated reminders to contacts have been shown to boost attendance rates by 32%. Integrating your event platform with marketing automation to follow up no-shows can boost engagement even further.

7. Certified automated marketers generate more leads.

Marketing automation is one thing, but certified marketers can further boost campaign effectiveness. The Eloqua Benchmark Index suggests that qualified marketing automation ‘masters’ can reach 50% of their database – 20% more than their unqualified peers.

8. Email is still king.

Social referrals are on the up (331% increase year on year), but is still significantly outperformed by email. Click-through levels are roughly similar between social and email (around 15,000 per quarter), but email opens top 120,000 in the same period.

(Source: Eloqua Benchmarking Report)

9. Database growth relies on empowered sales people.

An average sales team can increase customer database growth by an average of 4.5% each month. Equip them with content sharing tools, however, and this shoots up to 7.5% every single month.

(Source: Eloqua Benchmarking Report)

10. Automation boosts conversion.

Manual marketing campaigns are tricky to set up and maintain, and are less effective in the long run. Automated campaigns are not only 200% more effective at converting customers, they also remain effective for a lot longer.

11. Be personal for greater success.

Emails with personal email signatures are five times more effective at raising open rates than those from a generic account. They also boost click-throughs by nearly 350%.

(Source: Eloqua Benchmarking Report)

12. Use social sign-ons to keep data clean.

Savvy web users who are keen to avoid unwanted marketing emails, often use fake addresses and details in return for access to your content. However 40% of users now claim to prefer social sign-on methods – allowing you to capture ‘clean’ data and helping them reduce sign-up time. A win-win for you and your customers.

(Source: Consumer Perceptions of Online Registration and Social Login – Blue Research Survey, 2010)

13. No more keyword data from Google . . .

The move to encrypted search by Google means that all search terms and keywords are now hidden from site owners. This, coupled with moves by the search giant to move away from keyword-based indexing, means that marketers are becoming increasingly reliant on paid search to stay top of the search rankings.

14. The rise and rise of video . . .

Text remains important for search engine rankings, but customers are increasingly seeking video content first. Traffic to video sites is up 18% year on year, with approximately 22 million videos streamed over that period.

(Source: Nielsen, October 2009 to December 2011)

15. Constant messaging doesn’t work.

80% of deals are closed within the first two marketing ‘touches’. The effect of any additional messages beyond that point is significantly reduced. Once your marketing team gets beyond the sixth email, any benefits to you or the customer are minimal.

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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