The AI Sales Process Map: The Ten-Stage Sales Process Framework

The AI Sales Process Map: The Ten-Stage Sales Process Framework

By Sean O'Shaughnessey

Sales leaders today often fall into the trap of using artificial intelligence tools randomly rather than systematically. This sporadic usage is like owning a Swiss Army knife but only using the bottle opener; you miss out on ninety percent of the available value. AI’s real power comes not from isolated tools but from integrating capabilities across every stage of your sales processes. When mapped correctly, AI accelerates every interaction, shortens sales cycles, and makes revenue generation more predictable.

Random AI adoption leads to inconsistent results. Some reps use it effectively, while others revert to manual methods under pressure, resulting in uneven performance. Systematic AI integration, however, compounds improvements across the entire sales cycle. Data captured at one stage strengthens the next, creating a virtuous cycle of sales success that is scalable, measurable, and sustainable. The outcome is not just faster deals, but stronger business acumen and more consistent revenue management.

The ten-stage AI sales process framework provides a structured way to apply AI:

  1. Prospecting,
  2. Outreach,
  3. Qualification,
  4. Scoping,
  5. Presentation,
  6. Economic Buyer meetings,
  7. Validation Events,
  8. Proposals,
  9. Closing,
  10. Onboarding/expansion.

Each stage leverages AI differently, from intent data analysis in prospecting to AI-driven customer success monitoring post-close. Integration ensures that research informs outreach, discovery guides scoping, and validation improves proposals. By connecting the entire workflow, sales teams gain predictable processes and continuous optimization opportunities.

Process-based implementation builds competitive advantage. Competitors can replicate isolated AI tools, but systematic integration across sales strategies and sales management creates a differentiated approach that scales with growth. Consistency across the team reduces dependency on individual skill differences, enhances messaging, and strengthens value selling.

The measurement framework behind this approach ensures continuous improvement. Stage-specific conversion rates, velocity metrics, and data quality indicators guide refinements. Weekly reviews, monthly AI effectiveness assessments, and quarterly adjustments keep teams aligned while maximizing ROI from AI investments. Over time, these optimizations compound, creating a performance engine that drives long-term revenue generation.

The future of B2B sales isn’t choosing between humans and AI. It’s humans amplified by AI. Let’s build that future together.

If you’d like to explore this topic in more depth, there’s a podcast episode that covers all of this information and more. You can find the link to the episode here and consider subscribing to the podcast AI Tools for Sales Pros on your favorite podcast player.

Hiring for Growth: How to Build a Sales Team That Drives Long-Term Success

Hiring for Growth: How to Build a Sales Team That Drives Long-Term Success

By Sean O'Shaughnessey

Building a successful sales team requires more than just filling open seats with available candidates. Company leadership must strategically align its hiring process with business objectives, market needs, and long-term goals. 

Whether you’re a solopreneur transitioning to a team-based approach or a CEO managing a growing sales force, the principles of intentional recruitment and onboarding remain the same. Hiring the right people is an investment in the future of your business.

One of the most common pitfalls in sales hiring is a lack of intentionality. Too often, small businesses hire out of convenience, choosing candidates from their immediate network or taking the first person who seems interested. While this approach may solve an immediate need, it rarely leads to long-term success. 

Hiring a salesperson means selecting someone who can actively drive growth and represent your brand with competence and integrity. The stakes are even higher when you’re working with a lean team; every hire matters, and mediocrity is not an option.

To avoid these missteps, it’s essential to approach hiring with the same rigor you apply to your sales process. Think of recruiting as a parallel to securing a high-value client. Just as you wouldn’t sell your product without qualifying leads or understanding their needs, you shouldn’t hire without a structured process to evaluate candidates. 

Begin by defining what success looks like for the role. What skills and attributes are non-negotiable? What specific outcomes do you expect this person to achieve within their first 90 days? A clear job description and measurable KPIs set the foundation for finding the right fit.

Cultural alignment is another critical factor. Your salespeople are the face of your business to prospects and customers. Their ability to embody your company’s values and mission can make or break the customer experience. A candidate might have a stellar track record, but if their approach clashes with your team’s culture, the partnership is unlikely to succeed. At the same time, skills and experience must align with the specific demands of the role. For instance, if your goal is aggressive market penetration, you need a hunter mentality, someone skilled in building relationships from scratch and closing deals in uncharted territory.

Read the rest of the article…
Choosing the Right AI Stack for Your Sales Organization

Choosing the Right AI Stack for Your Sales Organization

By Sean O'Shaughnessey

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.

These layers aren’t just categories; they’re connected through data flows and integration principles. Each layer enhances the next, creating a system that scales intelligently with your team.

Your foundation layer usually consumes about half of your AI stack budget, but it’s worth it. Clean, structured data is the lifeblood of every other tool. From there, intelligence and automation layers drive the bulk of ROI by improving deal velocity, conversion rates, and rep efficiency.

Content tools and optimization layers build on that foundation, ensuring customer-facing communication remains sharp while performance is continually refined. When done right, this phased approach allows organizations to see value in months, not years.

Too many organizations make predictable mistakes: choosing tools for features rather than integration, underestimating training and adoption costs, or layering new tools on top of dirty data. Others rush implementation without testing, or ignore governance and compliance until it’s too late. The result? Expensive tools with low adoption and little measurable impact.

The lesson is simple: treat your AI stack like architecture. Every decision influences the system’s stability and scalability for years to come.

Real-World Configurations

  • Small teams may thrive with Pipedrive, Make.com, and ChatGPT handling CRM, workflows, and content.
  • Mid-market firms often layer Salesforce, Gong, Outreach, and PandaDoc for stronger intelligence and automation.
  • Enterprises combine Salesforce, advanced data platforms, SalesLoft, Gong, and dedicated optimization teams for scale.

These examples prove the point: success isn’t about tool count, it’s about fit, flow, and integration.

The Competitive Advantage of Integration

Companies with strategic AI stacks create barriers that their competitors can’t easily replicate. Data integration, consistent workflows, and continuous optimization compound value over time. The earlier you get your architecture right, the stronger your long-term advantage becomes.

And remember: the future of sales isn’t about humans versus AI. It’s about humans amplified by AI.

Immediate Action Items

  1. Inventory your current AI tools and map them to the five-layer framework.
  2. Identify missing layers and integration opportunities.
  3. Calculate the ROI of your current stack by measuring time saved, deals accelerated, and revenue uplift.
  4. Create a phased implementation plan using a 12-month roadmap.
  5. Establish data governance processes to protect the foundation of your stack.
  6. Pilot integrations before rolling them out team-wide.

If you want to go deeper into this topic, listen to Episode 7 of AI Tools for Sales Pros: Choosing the Right AI Stack for Your Sales Organization. You’ll find it on your favorite podcast player. Be sure to subscribe so you don’t miss the next episode: The AI Sales Process Map.

AI Isn’t Replacing Salespeople, It’s Giving Them a Competitive Edge

AI Isn’t Replacing Salespeople, It’s Giving Them a Competitive Edge

By Sean O'Shaughnessey

AI isn’t replacing salespeople, it’s making them more effective. The real risk isn’t losing your job to AI; it’s losing to a competitor who uses AI better than you do. Sales professionals who integrate AI into their workflow will outperform those who don’t. 

It’s not about technology taking over but about using technology to gain an edge. The market is becoming increasingly competitive, and the most efficient salespeople will emerge victorious.

Time is a salesperson’s most valuable asset. 

Every minute spent on administrative tasks is a minute not spent selling. AI helps reclaim those lost hours. Tools that automate writing, scheduling, and research allow salespeople to focus on what matters: building relationships and closing deals. If you’re not leveraging AI to increase productivity, you’re leaving opportunities on the table.

Sales emails need to be clear and professional. AI-powered writing assistants ensure your messages are polished and effective. A poorly written email can cost you a deal. AI tools catch grammatical mistakes, improve clarity, and even suggest more effective phrasing. This isn’t just about looking professional; it’s about being understood. 

If your message isn’t clear, it won’t convert.

Presentations are another time-consuming task. AI can generate professional decks in minutes. Instead of spending hours designing slides, salespeople can focus on developing effective strategies. AI-powered tools create branded, structured presentations based on simple inputs. This ensures consistency while saving time. Sales professionals who utilize AI for presentations can focus on delivering insights rather than formatting slides.

CRM systems are the backbone of sales operations. AI enhances CRM by automating data entry, tracking customer interactions, and suggesting next steps. Salespeople often struggle with keeping CRM data updated. AI reduces this friction by automatically capturing and organizing information. A well-maintained CRM leads to better forecasting and stronger customer relationships. 

If your CRM doesn’t have AI capabilities, it’s time to upgrade.

AI-driven insights enable sales managers to make more informed decisions, rather than relying on instinct. Managers can use AI to analyze performance trends, identify coaching opportunities, and predict revenue outcomes. AI doesn’t replace leadership; it enhances it. 

Sales managers who adopt AI can build stronger teams and achieve better results. Ignoring AI in sales management is a strategic mistake.

Lead generation is another area where AI adds value. AI-powered tools can analyze vast amounts of data to identify high-potential prospects. Instead of spending hours researching leads, salespeople can receive AI-generated recommendations. This allows for more targeted outreach and higher conversion rates. AI doesn’t just find leads, it finds the right leads.

Sales follow-up is often inconsistent. AI ensures follow-ups happen at the right time with the right message. Automated reminders and AI-generated responses keep deals moving forward. 

A well-timed follow-up can be the difference between closing a deal and losing it. AI helps salespeople stay on top of their pipeline without relying on memory.

Read the rest of the article…
Transforming Quota-Setting: Strategies for Sales Leaders to Optimize Performance and Revenue

Transforming Quota-Setting: Strategies for Sales Leaders to Optimize Performance and Revenue

By Sean O'Shaughnessey

Quota-setting is one of the most misunderstood elements of sales leadership. Too often, it’s treated as a spreadsheet exercise or a top-down directive, rather than a strategic lever that drives behavior, performance, and growth.

Whether you’re leading a team of 20 or you’re the founder managing three reps, how you define quotas has a direct impact on your revenue trajectory and your team’s motivation.

So, where do you start?

With timing. If you’re not delivering quotas to your team until February or March, you’re already behind. Salespeople need clarity by December. That gives them runway to plan, prioritize, and hit the ground running in January. Delayed quotas create confusion and stall momentum. To achieve a strong Q1, you need to equip your team early.

Quota-setting varies depending on the size of your company. Larger teams offer more flexibility. With 10 or more reps, you can spread risk, balance performance, and model averages. You’ll have top performers who consistently overdeliver, alongside newer reps who are still ramping up. The law of averages works in your favor. You can afford some variance. Smaller teams don’t have that luxury.

When you’re running a small team, maybe two or three reps or founder-led sales, every individual matters. One person missing quota can tank your number.

You can’t rely on averages. You need precision.

That means tying quotas to actual relationships, known opportunities, and real probability. It’s not about slicing up a target evenly. It’s about assigning numbers based on what’s realistically achievable in each territory or account list.

Territory design plays a big role here. Whether it’s geographic, vertical, or named accounts, quota must reflect the market potential. You can’t expect equal performance from unequal opportunity. If Rep A has 500 viable accounts and Rep B has 50, their quotas shouldn’t look the same unless you have data that says Rep B’s accounts are closer to your Ideal Client Profile. Use available market data to inform the number. Don’t assign quotas in a vacuum. 

In larger organizations, quotas often originate from the top down, typically from finance. The CEO and CFO commit a growth number to the board, investors, or in public filings to the SEC. They have no choice but to pass it down. It’s not uncommon for the sales team to receive the number without context. That’s a problem. If you’re in a leadership role, you need to pressure test that number. Can your team realistically hit it? If not, what additional resources are required?

  • More headcount?
  • Better enablement?
  • Marketing support?

In large organizations where the quota is driven by investor expectations, the VP of Sales must establish an organization well before the new year that achieves this year’s goal, while also meeting the expectation of growth for the next year. Planning ahead, sometimes years in advance, is part of the job.

Read the rest of the article…
ChatGPT vs. Claude vs. Gemini vs. Copilot: Which AI Wins in Sales?

ChatGPT vs. Claude vs. Gemini vs. Copilot: Which AI Wins in Sales?

By Sean O'Shaughnessey

A few days ago, a sales manager asked me which AI platform to use for writing cold emails. I told him it depends on what kind of emails he’s writing, and he looked confused. That confusion is common and costly. ChatGPT, Claude, Gemini, and Copilot all look similar at first glance, but in reality, they serve very different purposes depending on your sales workflow.

Choosing the right platform matters because the wrong choice drains time, creates change fatigue, and erodes ROI. Companies that align platform strengths to sales use cases are seeing dramatic results: 40% higher email response rates, 60% faster proposal generation, and triple the efficiency in call preparation. The stakes are high, and the decision deserves more than guesswork.

ChatGPT: The Versatile Performer
ChatGPT shines when creativity and personality are critical. It’s excellent for cold emails with humor, social selling posts, objection-handling scripts, and meeting prep. The downside? It can be verbose and sometimes casual for executive communication. If your team thrives on creativity and prospecting with personality, ChatGPT is a strong choice.

Claude: The Professional Communicator
Claude specializes in polished, business-appropriate communication. It’s strong for executive proposals, deal analysis, contract prep, and professional email sequences. While less creative than ChatGPT, it’s ideal for enterprise and strategic sales where tone, nuance, and professionalism are paramount.

Gemini: The Integrated Researcher
Google’s Gemini offers real-time research, market intelligence, and smooth integration with Google Workspace. It’s especially powerful for sales teams who rely heavily on spreadsheets, Gmail, and real-time prospect research. However, it may produce generic copy and come with potential data privacy concerns.

Copilot: The Enterprise Integrator
Microsoft Copilot excels in environments already standardized on Microsoft tools. Its strength lies in Outlook automation, PowerPoint proposals, Teams prep, and CRM integrations. While it can feel corporate and less creative, it’s perfect for organizations that value compliance, governance, and seamless integration across Microsoft 365.

Making the Right Choice
The best AI platform isn’t the one with the flashiest marketing; it’s the one your team will consistently use. Start by mapping your use cases: creative outreach, professional communication, research, or enterprise integration. Then run pilot programs, measure results, and refine your approach. Many sales teams find value in using more than one platform, each aligned to a different stage of the sales cycle.

The future of B2B sales isn’t about choosing between humans and AI. It’s about humans amplified by AI. Let’s build that future together.

If you’d like to explore this topic in more depth, there’s a podcast episode that covers all of this information and more. You can find the link below and consider subscribing to the podcast AI Tool for Sales Pros on your favorite podcast player.

Cut Through the AI Hype: Practical Definitions for Sales Professionals

Cut Through the AI Hype: Practical Definitions for Sales Professionals

By Sean O'Shaughnessey

Artificial intelligence is transforming sales, but too many leaders are investing in tools they don’t fully understand. The result? Costly mistakes, poor adoption, and missed opportunities. This episode of AI Tools for Sales Pros breaks down the three core technologies behind AI:

  1. Machine Learning (ML),
  2. Natural Language Processing (NLP),
  3. Large Language Models (LLMs)

and explains them in plain language that every sales professional can use.

The episode compares the current AI confusion to the database revolution of the 1990s. Just as sales leaders once needed to grasp relational databases or virtualization to sell effectively, today’s leaders must understand AI fundamentals to buy, implement, and coach effectively. Without this knowledge, vendor meetings become traps where features outshine true solutions.

Why Sales Leaders Need to Understand AI

  • Vendors are selling “AI-powered” tools that are often just automation with marketing polish.
  • ROI depends on knowing what you’re really buying.
  • Sales reps look to leadership for clarity and coaching on new technologies.
  • Competitive advantage comes from strategic implementation, not just adoption.

The Three Core AI Technologies

Machine Learning (ML): The pattern recognition engine. It predicts outcomes by analyzing historical sales data. Use cases: lead scoring, deal risk analysis, forecasting.

Natural Language Processing (NLP): The communication translator. It helps machines understand and analyze human conversations. Use cases: call transcription, sentiment analysis, chatbots, and objection detection.

Large Language Models (LLMs): The content creation powerhouse. They generate human-like content at scale. Use cases: personalized emails, proposals, meeting prep, follow-ups.

When the Technologies Work Together

The magic happens when ML, NLP, and LLMs integrate. Imagine: ML identifies the best prospects, NLP uncovers their communication style, and LLMs create personalized outreach. Companies are seeing 30%+ response rates with this integrated approach.

Misconceptions and Realities

  • Myth: AI replaces humans. Reality: It augments judgment.
  • Myth: More AI equals better results. Reality: Focused use beats scattered adoption.
  • Myth: AI requires massive data. Reality: Many sales AI tools work with modest data sets.

Action Steps for Sales Leaders

  1. Audit your current tools—identify which technologies you’re already using.
  2. Apply the vendor evaluation framework before making new purchases.
  3. Share these simplified definitions with your team.
  4. Connect with peers in the B2B Sales Lab community to learn from real implementations.

AI competency isn’t about programming—it’s about making better buying decisions and leading your sales team strategically. The future of B2B sales is not humans vs. AI—it’s humans amplified by AI.

👉 Register for your free 90-day membership at b2b-sales-lab.com and join the conversation.

AI in B2B Sales Isn’t Optional Anymore

AI in B2B Sales Isn’t Optional Anymore

By Sean O'Shaughnessey

Several months ago, I was serving as a fractional VP of Sales for a $50 million manufacturing company. Their top salesperson was a 15-year veteran who knew the industry inside and out. Yet he was consistently being outsold by a competitor’s much newer hire. At first, it didn’t make sense until we discovered the reason.

The competitor’s rep wasn’t just more energetic or aggressive. They were AI-enabled. While my client’s rep was manually scrolling LinkedIn and drafting emails from scratch, the competitor’s rep was using AI tools to research prospects, craft personalized outreach, and prepare for meetings. In other words, the competitor had a partner working 24/7—freeing them to focus on what humans do best: building trust and closing deals.

That was the turning point. I realized we weren’t just competing against other salespeople anymore. We were competing against AI-enhanced sales teams.

The Most Urgent Technology Wave in Sales

Throughout my career, I’ve watched new technology waves disrupt the sales profession. Robotics transformed manufacturing in the 1980s. Solid modeling replaced drafting tables in the 1990s. Cloud computing reshaped IT in the 2000s.

Each time, early adopters gained the edge while laggards struggled to catch up. The AI wave is different for two reasons:

  1. It’s broader: touching every aspect of sales, from prospecting to forecasting.
  2. It’s faster: companies have months, not years, to adapt before the competitive gap becomes overwhelming.

AI in sales isn’t coming. It’s already here.

The Four Pillars of AI Sales Transformation

To make sense of AI’s role in sales, I use a framework I call the Four Pillars of AI Sales Transformation.

1. Efficiency Amplification

Salespeople lose hours each week on research, data entry, and administrative tasks. AI automates these repetitive activities, turning wasted time into revenue-generating capacity. If a rep with a $2 million quota spends 40% of their time on admin work, reclaiming even half of that time can translate into hundreds of thousands of dollars in additional revenue potential.

2. Personalization at Scale

Buyers expect relevance. AI enables sales teams to tailor outreach at a scale that was previously impossible. One client of mine went from producing 10 personalized emails per day to 500, each one referencing company news, industry pain points, or competitive dynamics. The result: higher engagement and faster response times.

3. Predictive Intelligence

AI spots patterns humans miss. It identifies which deals are at risk, when prospects are most likely to respond, and which leads are worth pursuing first. For one client, simply shifting demos to Tuesday afternoons increased conversion rates by 40%. When your competitors are guessing, AI gives you confidence.

4. Continuous Learning & Optimization

Unlike static playbooks, AI evolves. It analyzes win/loss data, tests messaging, and provides real-time coaching insights. One client discovered that pricing discussions were their biggest choke point. AI flagged the pattern, we built automated battlecards, and close rates improved by 18%.

Real-World Results

These aren’t theoretical benefits. In my own client work:

  • An AI-powered prospecting rollout increased appointment-setting rates from 8% to 23% in just six weeks.
  • A lost-deal analysis uncovered patterns that helped recover $2 million in the pipeline.

The reality is clear: companies already experimenting with AI are pulling ahead. Those who delay are watching the gap widen daily.

Three Things You Can Do This Month

If you’re ready to start, here are three immediate steps:

  1. Audit your workflow. Identify one repetitive task you can automate—prospect research, meeting prep, or follow-up emails.
  2. Pilot an AI tool. Start small with an affordable, no-code platform. Many cost less than $200/month.
  3. Learn with others. Don’t navigate this change alone. Surround yourself with peers who are experimenting, learning, and winning with AI.

Join the B2B Sales Lab

The best way to accelerate your adoption is to connect with others on the same journey. That’s why we built the B2B Sales Lab, a private, member-led community for sales professionals who want actionable insights, not theory. It’s where strategy meets execution.

In the Lab, you can:

  • Ask real questions about sales challenges.
  • Share proven best practices.
  • Learn from other sales professionals and veteran leaders.

Your first 90 days are free. Join us today at b2b-sales-lab.com.

The future of B2B sales isn’t about choosing between humans and AI. It’s about humans amplified by AI. Those who adapt now will thrive. Those who wait may not get the chance to catch up.

To learn more, listen to this podcast on the subject.

B2B Sales in the Age of AI: Why Top Salespeople Will Thrive While the Repetitive Roles Disappear

B2B Sales in the Age of AI: Why Top Salespeople Will Thrive While the Repetitive Roles Disappear

By Sean O'Shaughnessey

The buzz surrounding artificial intelligence has left many professionals wondering about the future of their careers. For B2B sales professionals, the rise of AI presents a fundamental question: Will AI replace salespeople?

The short answer is no, but it will replace some of their work. More accurately, AI will redefine the B2B sales landscape by eliminating lower-value activities, consolidating support roles, and enhancing the capabilities of top performers. In doing so, it will widen the gap between average and great salespeople.

Several years ago, I wrote a similar explanation about the fear that “the internet” would replace salespeople. That didn’t happen. You can find that article on the blog that supports my first sales book. Are salespeople necessary in the Internet age?

This blog post explores how B2B sales is positioned relative to AI disruption, referencing key insights from Benjamin Todd’s article, “How Not to Lose Your Job to AI” (80,000 Hours, 2025). Todd’s framework on skill types that increase in value in the age of AI helps us understand how high-functioning sales teams should evolve and how sales professionals can future-proof their careers.

Understanding AI’s True Impact: Augmentation, Not Replacement

A common misconception about AI is that it simply replaces humans. This isn’t true. AI devalues tasks it can perform while increasing the importance of the skills it cannot. Todd explains this dynamic through examples like the ATM: while the ATM reduced the need for transactional teller tasks, it actually increased demand for bank branch workers by allowing banks to open more branches. AI follows a similar pattern.

In B2B sales, AI will handle the most automatable tasks, such as data entry, follow-ups, list-building, and basic prospecting emails. However, this doesn’t eliminate the sales role; it sharpens its focus.

Instead of dialing hundreds of prospects daily, sales professionals will focus more on strategic engagement, account planning, and using AI-generated insights to elevate conversations. The result? Sales has become a more thoughtful, human, and strategic discipline for those who can keep up.

Four Categories of Skills That AI Will Make More Valuable

In Todd’s excellent article, he identifies four skill types that increase in value in an AI-enhanced workplace:

  1. Hard-to-automate skills
  2. Deployment-related skills
  3. Scarce, high-utility skills
  4. Skills hard for others to learn or replicate

Each of these aligns tightly with the demands of modern B2B sales.

Read the rest of the article…
Two Tall Guys Talking Sales – Fixing the Funnel – Building a Sales Pipeline That Actually Works – E130

Two Tall Guys Talking Sales – Fixing the Funnel – Building a Sales Pipeline That Actually Works – E130

By Sean O'Shaughnessey

Welcome back to Two Tall Guys Talking Sales with hosts Kevin Lawson and Sean O’Shaughnessey. In this episode, the tall guys dive deep into one of the most critical yet commonly broken elements in any sales organization: the sales funnel. Whether you’re stuck with a clunky three-stage process that tells you nothing or overwhelmed with 35 micro-stages that only confuse your reps, Sean and Kevin offer a practical guide to rethinking and rebuilding your pipeline strategy. Packed with metaphors (yes, even superhero ones) and sharp analysis, this episode will leave you inspired to take a hard look at your funnel—and finally fix it.


Key Topics Discussed

  • Why Most Sales Funnels Are Broken (00:00:45)
    Sean unpacks the common pitfalls in how companies define and manage their sales stages, including oversimplified or overly complex CRM setups.
  • Defining Sales Stages Based on the Buyer Journey (00:04:30)
    Kevin emphasizes the need to align your sales stages with how buyers actually buy—not how your company wants to sell.
  • How Many Sales Stages Are Too Many? (00:05:00)
    The guys explore the delicate balance between not enough insight and too much complexity in stage design.
  • The Case for Multiple Pipelines (00:08:00)
    When does it make sense to separate budgetary planning pipelines from active sales discussions? Kevin and Sean explain.
  • What a Healthy Funnel Actually Looks Like (00:10:45)
    Sean introduces a visual and mathematical approach to evaluating whether your funnel is properly shaped—and what to do if it’s not.


Key Quotes

“The Avengers became a team, not just Iron Man. You need to have a team. Even superhero salespeople like to have support.”
— Sean O’Shaughnessey (00:02:50)

“Fixing the funnel starts visually. Does it fit well on one sheet of paper? If not, you’ve already lost the battle for clarity.”
— Kevin Lawson (00:04:45)

“Stages should be built to qualify someone into the next step—not just to log an activity. Every transition should represent progress, not busyness.”
— Kevin Lawson (00:06:15)

“If your pipeline doesn’t look like a funnel, then you’re either wasting time or losing deals. Probably both.”
— Sean O’Shaughnessey (00:12:20)

Additional Resources Referenced

A Significant Actionable Item from this Podcast

Audit Your Sales Funnel for Shape and Stage Effectiveness
Pull a report from your CRM and visualize your current pipeline by number of deals and total revenue per stage. Does it actually look like a funnel? If it doesn’t, dig deeper. Are your stages aligned with your buyer’s journey? Are reps stuck in certain stages too long? This snapshot identifies gaps and opportunities for stage redefinition or activity refinement.

Summary

Whether managing a sales team or closing deals yourself, this episode of Two Tall Guys Talking Sales gives you the blueprint to diagnose and repair a misaligned funnel. Sean and Kevin combine humor, hard truths, and highly actionable insights to help you bring structure and sanity back to your sales process. If you’re ready to create a pipeline that reflects how buyers buy—and helps your team win more deals—this episode is a must-listen.

🎧 Listen now and take the first step in fixing your funnel for good.