Case Study: Local Handyman Company Exceeds Revenue Goal by 300%

Patrick McFadden • July 6, 2016

Indispensable Marketing helped one of the fastest growing handyman companies in Richmond, VA bring order to disorganized marketing activities, free up the owner to work on the business and create a lead generation system that gets prospects to systematically call them.  Read the case study below to see how we did it.

Background

Handyman Matters of Richmond is one of the fastest growing handyman companies in Richmond, VA.  The owner, Michele Deane, has run the business for 3 years and is well-respected in the area.  Her company provides home repair, home improvement, home remodels services to residential clients and handyman services to commercial and property management clients.

The Problem

Before she started working with Indispensable Marketing, Michele Deane had spent over $40,000 working with four different tactical marketing professionals–a web designer, SEO specialist, pay-per-click specialist, and direct mail specialist. All of them promising to grow her business fast, make the phone ring and generate all the leads her organization could handle. Well you know the story, in order to be effective, all of these areas need to be closely coordinated, but in Michele’s case these specialists were not communicating with each other, pulling her marketing in totally different directions and in some cases were barely even generating results for her. Michele thought about a conversation we had 2 years prior about developing a solid marketing foundation, and made the call for us to help turn this chaos into clarity and generate real results.  

The Solution

Upon being hired we immediately recognized two of the marketing specialists working with Michele was not a good situation, their services were not generating results and basically stealing our clients hard earn money.  We proposed that Michele fired these two marketing specialist, and have everyone involved in working on Handyman Matter’s marketing report to Indispensable Marketing, who would then report to Michele.  That way, everyone would be on the same page for the results we were seeking, marketing efforts would be coordinated, and Michele would only have to deal with one company instead of four.

Michele agreed to this plan, and allowed Indispensable Marketing to take over supervision of Handyman Matter’s marketing.  One of the first things we did was interview Michele about her vision and research information about her best customers to see what they had to say about the business.  We also met with the various marketing providers and starting developing a lead generation system that runs without the owners efforts.

Next, we identified the unique difference, wrote core positioning messages and developed website content for Handyman Matters of Richmond. This content was packaged up in a marketing plan that could be used by Handyman Matter’s employees and service providers.  It is also being used to create an “offer” that could be used in lead generation campaigns.

Once the new website and marketing plan was finished, Indispensable Marketing began improving Handyman Matters marketing activities and adding some as well, including:

  • Development of Call Intake Form – Systemized the process to hire additional dispatcher
  • Improving Lead Conversion – with new leads coming in we went to work on converting more of them
  • Brand Identity  – Ensuring all marketing efforts are branded with our core message
  • Commercial Accounts were mined from 2 national property management firms
  • PPC Pay-Per-Click – Advertising generates 50-60 leads a month 
  • Real Estate Referral Program – Program generates 10-20 high quality leads a month
  • Profitability of projects went from 12% to 20% over 3 months
  • Revenue goal was met or exceeded for 3 consecutive months. Update: 300% over 2016

Results

Thanks to Indispensable Marketing’s supervision, these new initiatives were integrated seamlessly into the existing marketing plan so that they complemented what was already being done and built upon past successes.  Michele now has time to create strategic partnerships, spend weekends with her family, develop employees and run the business without worrying that the money she invests in marketing is going to waste due to lack of incompetence or uncoordinated efforts.

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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