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What An MBA Didn’t Teach You About Sales

The sales profession is challenging. You need to work hard at it to succeed. You need to learn from the best. You need to improve your skills continuously. If you think you can sell since you are a hit at parties and have a lot of friends, you may soon find that you are a failure as a salesperson. Blunt truth:

because the sales profession is so hard, you have to focus on doing everything in sales very well, or you will be considered a failure.

I call this blog, Skinned Knees because I try to relate all of the learning that I have done over the past 4+ decades (while skinning my knees in the learning process).

I hope that you learn from my mistakes so that your business will grow!


Sales Management in the Age of AI: Aligning Marketing, Messaging & Revenue Generation

When it comes to modern B2B revenue generation, the conversation is shifting: it’s no longer just about cycle time or activity metrics, it’s about intent, predictive insights, and sharpening your approach to lead engagement. In this post, we unpack how artificial intelligence (AI) can reinforce your sales management discipline, refine your sales processes, and elevate your team’s business acumen.

Many sales organizations still rely on traditional lead-scoring models: “five points for a white-paper download, ten points for visiting the pricing page.” These rules-based frameworks sit at the heart of countless debates over marketing-qualified lead (MQL) vs. sales-qualified lead (SQL). Yet research shows that such arbitrary scoring systems often perform little better than chance.

By contrast, predictive lead scoring powered by AI changes the game: algorithms ingest data from your CRM, marketing automation, website activity, firmographics and behavior patterns. They then compute each lead’s statistical probability of converting, turning your outreach efforts from scatter-shot to precision-targeted.

In value selling, the objective is to engage high-potential buyers with meaningful differentiation—messaging that resonates with their specific business challenges. When your team is handed leads that reflect a 90 %+ probability of conversion, the conversation changes: it becomes strategic, not just transactional. Your reps spend less time chasing noise and more time facilitating high-impact dialogues.

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Stop Betting on Superstars: How Operating Standards Turn Sellers into Predictable Producers

Many teams grow, but few truly scale revenue beyond individual hero efforts. That difference changes everything for leaders today and in the future. Growth relies on hustle; scaling depends on repeatability across segments and individuals. Your strategy must reflect that hard truth in practice.

Are you relying on one standout to win deals month after month? That looks strong until risk turns visible and costly. One resignation can cripple momentum and expose brittle systems that you had previously ignored.

Scalable sales replaces heroics with defined, teachable operating rhythms that everyone follows. It turns chaos into predictable pipeline progress and results. It clarifies markets, messages, motions, and measurable expectations for every seller on a weekly basis. It builds leverage into onboarding and coaching for consistency. It protects margins while systematically accelerating win rates and velocity across territories.

The foundation begins with a clear picture of your ideal customer, including any disqualifying factors. Having an accurate Ideal Client Profile (ICP) helps minimize waste and reduce uncertainty in your efforts. Take time to define firmographics, pain points, triggers, and buying behaviors using consistent language based on shared evidence. Understand who cares about these issues and why it matters to them now. Also, identify negative personas to sharpen your focus and qualification processes in marketing and sales. A well-defined ICP can significantly boost your conversion rates and shorten the sales cycle.

Next, turn your ICP into straightforward messaging and discovery frameworks tailored for each stage. Consider what unique problems you solve for your customers. What outcomes are most important to them, and who are the key stakeholders by role and priority?

Build talk tracks that lead buyers, not chase buyers with purpose always. Anchor questions to the business metrics and risks they feel. Teach a qualification that tests mutual commitment and outlines next steps with attached dates. Avoid fluffy demos; design relevant proofs using their data. Process specificity turns B players into consistent producers without copying another personality.

I suggest you establish a practical, stage-based operating rhythm that everyone can easily understand and follow. By sharing clear definitions and expectations, managing the pipeline becomes a consistent and smooth process each week. Define each stage with specific exit criteria—avoiding vague intentions or subjective feelings. For example, discovery is considered complete when stakeholders confirm the consequences and impact, and solution fit is achieved when success criteria and ownership are clearly aligned. The commit stage should be backed by a shared plan with clear dates and assigned owners. During weekly reviews, focus on assessing quality rather than just quantity or activity counts. Ask yourself:

  • Does evidence from buyers’ backstage moves have a direct impact on their purchasing decisions?
  • Are the next steps specific, mutually agreed upon, and already scheduled on both calendars?
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The Future of Prospecting: Using Artificial Intelligence to Read Buyer Intent

The modern salesperson faces two extremes: total blindness or total overload. Some still cold call a list of fifty prospects hoping one will answer, while others drown in dashboards flashing with “intent data.” Both approaches fail because neither interprets what the data truly means.

The future of sales management lies in balance — using artificial intelligence to translate buyer behavior into clear, prioritized action. AI can read digital body language, scoring every click, visit, and download to reveal genuine purchase intent. This isn’t about replacing salespeople. It’s about enabling them with sharper business acumen and faster, more precise decision-making.

When sales leaders align technology with disciplined sales processes, they move from guesswork to guidance. Value selling becomes tangible because messaging is timed to the buyer’s journey, not to the rep’s quota. The best teams build standardized playbooks for each stage — from early curiosity to re-engagement — and rely on revenue management data to decide when to act.

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Reclaiming Hours of Selling Time with AI – Lessons from MAICON 2025

You just checked your team’s dashboard. Activity looks fine. But deep down, you know that the numbers don’t tell the whole story.

Every salesperson loses time to the same unseen burden: administrative drag. After each successful discovery call, there’s a 20-minute grind with CRM updates, email summaries, and internal handoffs. This “sales tax” cuts into selling time, hurts momentum, and costs your company thousands weekly in lost productivity.

I just returned from MAICON 2025, and I was so inspired that I wanted to share some of the biggest lessons. At the MAICON 2025 conference in Cleveland, the message was clear: artificial intelligence is changing sales management, not by replacing people, but by empowering them. The winning teams are using AI to eliminate “digital grunt work” through orchestration, not standardization.

Orchestration, Not Standardization

MAICON’s main message was that sales leaders should stop searching for the “one magical platform.” Instead, the most successful organizations coordinate several top-tier tools. Their AI ecosystems are modular, flexible, and collaborative.

It starts with three pieces:

  1. a transcription tool like Fireflies,
  2. an automation hub like Make.com or Zapier,
  3. your existing CRM and communication systems.
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Stop Researching, Start Connecting: An AI-Powered System for Warm Introductions

Most sales teams begin the week by opening a dozen browser tabs and grinding through scattered research, LinkedIn, Google News, company websites, and databases. Hours later, they emerge with a few generic talking points and a cold list that still feels cold. The deeper issue isn’t inefficiency; it’s invisibility. Warm introductions already exist across your company’s network, in email histories, calendars, and executives’ LinkedIn connections, but you can’t see them on Monday morning.

The Relationship-First approach changes that default. Before a single cold call or email, you perform a deliberate “Warm Path Check.” You ask, “Who do we know who knows them?” This question transforms prospecting from random outreach into a repeatable, data-driven process that prioritizes relationships. When you start as a referred conversation rather than an interruption, skepticism drops, credibility rises, and the sales cycle compresses dramatically.

The Hidden Network You’re Not Using

Every organization has an untapped network, a web of past colleagues, vendors, and clients who could open doors to your dream accounts. The problem is that this network is hidden in plain sight. It lives in the collective memory of your company’s communication patterns, but there’s no easy way to access it manually. That’s where KnowledgeNet comes in.

KnowledgeNet serves as your organization’s “relationship intelligence” layer. It analyzes communication data (emails, meetings, messages) to reveal who knows whom, and how strong those connections really are. Instead of guessing, you can instantly see that a colleague in engineering once worked closely with the CFO of a target account. That’s a warm path waiting to be used.

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Automating Sales Workflows: When to Use Automation Over Chat

In sales management, there’s often some confusion about when to use artificial intelligence chat interfaces versus automation workflows. Chat interfaces are ideal for creative problem-solving, learning, and strategic research, while automation excels in repetitive, high-volume, data-driven sales tasks. The trick is to recognize when consistency and scalability are more important than customization.

Automation delivers consistent execution, eliminates human error, and operates 24/7. Sales leaders can rely on it for triggered communications, data synchronization across systems, CRM updates, and compliance tasks that require accuracy and complete audit trails. By moving these routine tasks into automated workflows, sales teams free up valuable time for relationship building, revenue generation, and refining sales strategies.

Real-world examples highlight the impact: a team once spent three hours daily crafting manual follow-up emails. Shifting to automated sequences not only saved time but also improved messaging consistency and pipeline response rates. Similarly, another team utilized automation to synchronize sales data across six systems, thereby eliminating bottlenecks and enabling sellers to focus fully on sales.

Hybrid approaches really take things to the next level! By merging human creativity in chat interactions with the quick and precise power of automation, businesses can craft workflows that beautifully balance personalized service with the ability to grow. This type of teamwork enhances value-driven selling, sharpens business skills, and accelerates revenue management throughout the sales journey.

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Sales Management with AI: Chat Interfaces vs. Automation Workflows

Sales organizations today face a critical decision: should they rely on interactive chat interfaces like ChatGPT, Claude, or Gemini, or should they focus on automation workflows? The answer isn’t either/or. Each approach has unique strengths, and choosing the right one directly impacts sales processes, productivity, and revenue generation.

The problem many sales teams encounter is “random implementation.” They hear about a new AI tool, adopt it quickly, and use it for the wrong purpose. The result? Chat interfaces get bogged down with repetitive work, and automation gets tasked with jobs that require creativity and nuance. Misuse not only reduces efficiency but also frustrates teams and erodes trust in artificial intelligence altogether.

So how do you know when chat is the right fit? The decision comes down to task complexity and uniqueness. Chat excels in situations that require creativity, flexibility, and human judgment. Four categories consistently stand out:

  • Creative and strategic tasks: proposals, executive messaging, strategic planning, and competitive positioning.
  • Complex problem-solving: sales opportunity strategy sessions, unique customer needs, and crisis management.
  • Learning and development: role-playing objection handling, skill coaching, and competitive intelligence training.
  • Research and analysis: prospect research, market analysis, and strategic planning.
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Choosing the Right AI Stack for Your Sales Organization

A VP of Sales recently confided in me: “We have six different AI tools, but our reps are still doing manual work. What went wrong?”

This is the AI tool proliferation problem. Sales leaders often collect tools without a strategy, mistaking a pile of features for a cohesive system. It’s like buying a hammer, screwdriver, saw, and drill without realizing you’re actually trying to build a house. An effective AI stack means integration. When tools work together, they amplify each other’s value. When they don’t, they add complexity, confusion, and wasted money.

Why Strategy Beats Random Adoption

Random tool adoption is rampant across sales organizations. Teams chase shiny new software, often ending up with overlapping features, siloed data, and productivity lost to tool-switching. Instead of solving problems, the stack itself becomes the problem.

But when built strategically, the benefits are profound. Integrated systems reduce manual data entry, accelerate response times, and deliver actionable insights for reps. Three well-chosen, well-connected tools can outperform six isolated ones. Integrated stacks also improve adoption rates by providing consistent interfaces and reducing training overhead.

The Five-Layer AI Stack Framework

To avoid the chaos of random adoption, I use a five-layer framework for structuring sales AI tools:

  1. Data Foundation – Your CRM and data management system, enriched and maintained for accuracy.
  2. Intelligence & Analytics – AI-driven insights, lead scoring, forecasting, and market intelligence.
  3. Automation & Workflow – Sequences, task automation, and cross-platform orchestration.
  4. Content & Communication – AI writing, proposal generation, and customer-facing tools.
  5. Optimization & Learning – Conversation analysis, performance tracking, and continuous improvement.
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From Manual to Automated: A Sales Pro’s Guide to Zapier, Make.com, n8n, and Pipedream

A sales manager recently told me something that stuck: “We went from twenty hours per week of manual work to two hours. Our lead response time dropped from four hours to four minutes.” That dramatic transformation wasn’t magic—it was automation. The reality is that sales teams today have more automation tools available than ever before. But with options like Zapier, Make.com, n8n, and Pipedream, the real challenge isn’t whether you should automate—it’s choosing the right… From Manual to Automated: A Sales Pro’s Guide to Zapier, Make.com, n8n, and Pipedream

Two Tall Guys Talking Sales – Sales Strategies That Outperform AI Tools: ICP, Value Selling, and Revenue Management – Episode 150

In today’s fast-changing sales landscape, everyone is talking about AI, automation, and digital tools, but are these the keys to sales success? In this episode of Two Tall Guys Talking Sales, hosts Kevin Lawson and Sean O’Shaughnessey explore why documenting your sales processes, defining your ideal client profile (ICP), and sharpening your value selling approach must come before chasing shiny new technologies. Whether you’re leading a sales team or building revenue generation strategies as a… Two Tall Guys Talking Sales – Sales Strategies That Outperform AI Tools: ICP, Value Selling, and Revenue Management – Episode 150