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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!

How to Win When AI-Powered B2B Buyers Already Know Your Product

Imagine walking into a major prospect meeting after two days of preparation. You have reviewed the account, refined your presentation, and rehearsed your opening. Three minutes into your presentation, the vice president of operations interrupts.

“We already know what your product does. We compared you with five competitors using AI.”

She turns her laptop around. On the screen is a spreadsheet with 200 rows of features, prices, reviews, and implementation claims. Some entries are accurate. Others are questionable. Every entry has already influenced how her team thinks about your solution. Your instinct might be to continue the presentation, challenge the inaccuracies, or defend your product feature by feature. All three responses surrender control of the business conversation. The buyer does not need another source of product information. She needs help making a decision.

The Salesperson’s Information Advantage Is Gone

Artificial intelligence has changed what B2B buyers can accomplish before they speak to a salesperson. Generative AI tools can summarize technical documents, compare competing products, model pricing scenarios, identify perceived weaknesses, and develop vendor shortlists in a fraction of the time those activities once required.

According to Gartner’s May 2026 research, 45% of surveyed B2B buyers used generative AI during a recent purchase. Sixty-seven percent said they preferred a sales-rep-free experience. Yet 69% wanted to validate AI-generated insights with a sales representative. Those numbers are not contradictory. Buyers increasingly prefer to gather information independently, then turn to someone who can help them assess its reliability, apply it to their business, and reduce the risk of a bad decision.

This changes the definition of value selling. A salesperson’s value is no longer primarily access to information. It is the ability to translate evidence into business judgment and confidence in decisions.

Your Most Dangerous Competitor Is No Decision

An AI-assisted buying committee may be more informed individually and less aligned collectively. The CFO asks an AI assistant to identify the cheapest alternative. Operations prioritizes reliability and throughput. IT investigates integration and cybersecurity. Procurement scores the vendors against another set of criteria. Each stakeholder arrives with an apparently objective answer. The answers do not necessarily agree. More information creates more debate, more validation requests, and more reasons to defer the decision.

This is how information paralysis becomes a revenue problem. The salesperson who responds with another 40-slide deck adds information without resolving uncertainty. The stronger seller identifies the few factors that determine whether the investment produces a measurable business result.

For a manufacturing automation purchase, those factors might be unplanned downtime, production throughput, and integration costs. The other 197 spreadsheet rows may be informative without being decisive.

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AI Sales Coaching: How to Stop Rescuing Deals and Start Developing Salespeople

There is a dangerous moment in the growth of many B2B companies. It happens when the best salesperson becomes the sales manager.

The promotion seems obvious. This person consistently exceeds quota, understands customers, knows how to close difficult deals, and has earned the team’s respect. Who could be better qualified?

Six months later, that same person is personally rescuing the team’s largest opportunities, handling difficult customer objections, negotiating with executives, and keeping the forecast alive.

The company’s revenue looks healthy. The owner is satisfied. The sales manager appears indispensable.

And that is precisely the problem.

The company hasn’t developed a scalable sales organization. It has become dependent on one talented individual. Artificial intelligence offers an opportunity to change this pattern. But only if we rethink what sales management should accomplish.

The Difference Between Managing Deals and Developing Salespeople

Traditional sales management relies heavily on inspection and intervention. Managers review pipeline reports, examine forecasts, enforce activity requirements, and intervene when opportunities get into trouble. These activities are necessary, but they are not the same as coaching.

Consider a salesperson who confidently announces during a pipeline review that Mary is the Champion for a major opportunity. The manager suspects that Mary is simply a friendly contact who likes the product. An experienced manager might join the next customer meeting, take control of the conversation, and personally secure executive support. The opportunity might close. Unfortunately, the salesperson hasn’t developed the ability to identify and validate a real Champion.

A better manager asks a different question:

“What has Mary actually done that proves she is your Champion?”

Has Mary introduced the salesperson to important stakeholders? Has she explained the customer’s internal decision process? Has she advocated for the solution when the salesperson wasn’t present? Has she taken any personal risk to help the opportunity advance? If the salesperson cannot identify meaningful actions, the relationship remains an untested hypothesis.

The manager’s next responsibility isn’t to take over. It is to help the salesperson determine how to test that relationship. That coaching conversation improves the salesperson’s judgment, potentially affecting every future opportunity.

The objective of sales leadership is not to make the manager better at closing deals. It is to make the entire team better at closing deals.

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The Power Matrix: Mapping Who Really Decides

Every significant B2B purchase is shaped by more people than the salesperson ever meets. Some sign the contract, some recommend, some can quietly veto, and many simply have to live with the result. The Power Matrix puts that network on a single page.

It forces a salesperson to answer three questions about every major opportunity: Who can influence this decision? How much power does each of them really have? How well do we know them? A salesperson who can complete the Power Matrix for every account will be phenomenally successful. One who can’t will find that the empty cells show exactly where the deal is exposed.

This overview explains how the matrix is structured, how to build one, and how a sales leader can use it to judge the real health of the team’s largest opportunities.

An influence chart, not an organizational chart

The Power Matrix maps who influences one specific purchasing decision. It does not map who reports to whom. That single distinction drives everything else about the tool.

Two people on the same row may hold different titles, report to different executives, and work in different parts of the company. They’re on the same row because they carry roughly the same weight in this decision. Likewise, someone placed above another in a column does not need to be that person’s boss. They need to respect each other’s opinions.

Titles are a poor guide to power. A title often reflects tenure rather than influence, and a sharp Director can carry as much weight as a Vice President, especially across departments of very different sizes. Build the matrix by watching how people react to one another, whose opinion others seek, and whose objections stop a conversation.

Two versions, sized to the opportunity

The matrix comes in two sizes. The larger one requires far more research and relationship-building, so the deal must justify the effort.

CharacteristicSmall Power MatrixLarge Power Matrix
Grid3 × 35 × 5
People identified925
Departments35
Influence levels35
Typical deal sizeBelow roughly 5–10% of annual quotaAbove roughly 10% of annual quota
Center cellPrimary CoachPrimary Coach

The quota cutoff is a guideline, not a rule. Adjust it for your product and industry. As a sanity check, a salesperson with a reasonable win rate should rarely need more than about 10 Large Power Matrix analyses in a year. If someone is building 20 or more, the threshold is set too low, and they are spending large-deal effort on small deals.

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AI Prospecting Agents: Build More Pipeline Without Adding More SDRs

One of the more frustrating realities in modern sales is that a company can invest heavily in technology and still leave its best salespeople doing work that should never require their time.

The CRM is open. So is LinkedIn. There is an intent-data platform in another tab, a contact database in another, a sales engagement platform somewhere else, and perhaps a conversation intelligence tool running in the background.

The company has a technology stack. What it may not have is a prospecting system.

That distinction matters.

A collection of tools still depends on someone remembering which accounts matter, noticing when a former champion changes jobs, deciding which buying signals deserve attention, researching the account, moving information between systems, writing the message, and following up. When people are the integration layer connecting all those systems, the company has not really automated prospecting. It has simply given its salespeople more software to operate.

The Prospecting Advantage Has Changed

Traditional outbound sales was built around scarcity. Finding contact information, researching a company, and uncovering a credible reason to approach someone required significant effort. That made volume difficult and valuable.

Artificial intelligence changed those economics.

Today, generating another email is nearly free. Finding another prospect is relatively easy. AI can produce hundreds or thousands of messages faster than a sales team could ever review them. That does not make those messages valuable.

When volume becomes inexpensive, volume stops being a competitive advantage. Relevance becomes the scarce resource.

We need to evolve our systems away from asking, “How can we send more outreach?” Rather, we need to be thinking of, “How can we identify the people who deserve our attention right now and give our salespeople something useful to say when they contact them?”

A modern prospecting system therefore has to answer five questions continuously:

  1. Who should we pursue?
  2. Why should we pursue them now?
  3. What should we say?
  4. Which channel and timing gives us the best chance of engagement?
  5. When should a human salesperson enter the conversation?

The fifth question is particularly important.

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Your Sales Compensation Plan Is Quietly Managing Your Sales Team

A salesperson reaches the final week of the quarter with a major opportunity ready to close. Legal has approved the agreement. The customer is prepared to move forward but asks for a 15 percent discount.

The salesperson understands what the discount does to margin. So does the sales manager. Finance knows as well. Yet the salesperson is measured on revenue, the manager needs the deal to make the quarterly forecast, and neither is directly rewarded for protecting margin.

The discount is approved. The deal closes. The commission increases. Everyone celebrates.

The company may have just paid someone extra to give away its profit.

No one acted dishonestly. The compensation plan worked precisely as designed. That is the problem.

Compensation Is a Management System

Most companies treat sales compensation as an administrative process. Leadership creates a plan, finance calculates payments, and managers resolve disputes when the numbers do not match expectations.

That view misses the strategic role compensation plays.

A compensation plan influences which customers salespeople pursue, how aggressively they discount, whether they favor one-year or multi-year agreements, how they collaborate, and whether they prioritize new business, renewals, margin, or market share.

What the company pays for will eventually outweigh what its leaders say they value.

Many sales leaders inherited plans that accumulated years of exceptions, temporary accelerators, regional variations, product overlays, split-credit rules, and special arrangements. The resulting spreadsheet may be technically functional while being strategically incoherent.

The warning signs are familiar:

Salespeople maintain private spreadsheets because they do not trust their commission statements.

Managers spend time resolving payout disputes instead of coaching pipeline.

Quotas are created by adding a percentage to last year’s number rather than analyzing territory potential.

A handful of top performers benefit from every contest while most of the team decides the competition is irrelevant.

These are not motivation problems. They are design problems that consume selling time, reduce margin, and erode trust.

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How to Build a Sales Organization That Survives a Founder Exit

Navigating the complexities of business transitions can be quite a journey, especially for those in sales and leadership roles. When a founder chooses to pass the baton, whether through selling to someone outside the company, passing it within the family, or setting up an employee stock ownership plan, each option comes with its own unique challenges and chances for growth. For salespeople, sales managers, and CEOs of small companies, understanding these dynamics is really important.

When a business owner considers selling to an external buyer, they often experience a surprising realization: the valuation shock. It’s common for owners to overestimate their company’s worth, only to encounter a reality check during the valuation process. This moment is so important because it influences all future negotiations and strategies. Buyers don’t just look at the numbers; they also carefully examine the business’s sales processes and the owner’s involvement. Here, the owner’s role as the main salesperson can be both a strength and a challenge. If the owner accounts for a large share of sales, such as 30%, it can worry potential buyers. 

The key is to build a business that can thrive even when the owner isn’t around, supported by a solid sales system and a talented team eager to keep everything running smoothly.

For the owner contemplating a sale, preparation is key. 

The question to ponder is: what if you were suddenly unavailable? 

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Build a Repeatable Sales Process Using Buyer Personas

In the world of sales, consistency is a cornerstone for success. Salespeople, sales managers, and CEOs alike strive to find a sustainable way to grow their business, and one effective strategy is to focus on buyer personas. Identifying and understanding these personas can streamline the sales process, making it easier to target the right customers and tailor your approach to meet their specific needs.

Consistency is key. When you consistently sell to profitable companies that see value in your solutions, you can standardize your sales processes and messaging. This consistency allows you to tweak and improve your methods incrementally, rather than making wild changes that may not lead to profitability. Many small companies don’t have the luxury of unlimited cash flow. They need to be mindful of their line of credit and ensure that their accounts receivable don’t get out of hand. By focusing on companies that are easy to sell to and where your product or service fits seamlessly, you can make your clients successful and maintain a steady growth trajectory.

The entrepreneurial operating system (EOS) is a valuable framework that helps businesses achieve consistency. By setting firm foundational corners, such as data, people, and core processes, businesses can create a structured environment where everyone can succeed. For sales departments, this means formalizing not only the messaging but also the reporting structure, job descriptions, core goals, and key behaviors. Consistency in these areas leads to reliable and repeatable results.

A repeatable sales process is crucial. If everything is custom, nothing is standardized, and this can lead to chaos. Sales leaders must set the standard for consistency, and both business owners and salespeople need to align themselves with these consistent behaviors. Standardizing the sales process enables better forecasting and a more predictable customer flow.

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The Buyer’s Clock Starts Before Your Sales Team Notices

A buyer does not become urgent when your CRM creates a record. The buyer became urgent earlier; at that moment, they decided the problem was worth interrupting their day for.

That distinction matters because too many B2B companies design their inbound process around internal workflow rather than buyer momentum. A prospect searches, compares, reads, evaluates, talks to a peer, visits your site, reviews your proof, and finally raises their hand. Then the company they contacted responds as though the buyer has agreed to wait patiently while marketing automation, CRM routing, territory logic, rep availability, and inbox notifications sort themselves out.

That is not a speed problem. It is a revenue system problem.

The real issue is not whether a sales rep should call faster. Of course they should. The deeper question is whether the business can detect, interpret, prioritize, enrich, route, and respond to buyer intent while the buyer still cares. When the answer is no, the company loses revenue without realizing it. The lost buyer does not announce their departure. They simply book with someone else, cool off, or decide the issue can wait.

This is why inbound orchestration deserves executive attention. High-intent inbound activity is not a generic lead flow. A demo request from a target-fit company is not the same as a newsletter signup. A pricing inquiry is not the same as a content download. Treating all of them as “leads” may simplify reporting, but it destroys commercial judgment.

When every lead looks the same, nothing feels urgent.

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Revenue Forecasting Should Be Built on Evidence, Not Hope

Most sales forecasts are not really forecasts. They are seller opinions, manager adjustments, CRM fields, historical averages, and optimism packaged into a number that leadership is expected to trust.

That may have been acceptable when forecasting was mostly an internal sales exercise. It is not acceptable when the board, finance, hiring plans, customer success capacity, and investor expectations are all tied to the revenue number.

The core problem is not that sales leaders are careless. The problem is that many revenue teams are still using an architecture that cannot produce predictability. Spreadsheets, commit calls, and stage rollups organize information, but they do not necessarily reveal the buyer’s truth.

The better question is not, “How confident is the rep?”

The better question is, “What did the buyer actually do?”

That shift changes the entire operating model. Forecasting moves from hope-based to evidence-based. Deals are no longer judged by the confidence in a seller’s voice but by observable buyer behavior: recent engagement, executive involvement, mutual action plans, legal or procurement movement, real next steps, and date-driven urgency.

This is where artificial intelligence and revenue intelligence become useful, but only if the management system is ready for them. AI can identify patterns, detect risk, surface stalled deals, and compare buyer behavior against historical outcomes. But it cannot compensate for weak sales processes, vague stage definitions, poor CRM hygiene, or managers who refuse to inspect the evidence.

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How Bad CRM Data Breaks AI, Sales Processes, and Pipeline Growth

Most sales leaders do not have a prospecting problem. They have a data-confidence problem disguised as a prospecting problem.

The team is working. Reps are calling, emailing, sequencing, researching, and updating the CRM. But when the data is stale, duplicated, incomplete, or legally questionable, every downstream motion becomes weaker. Outreach gets slower. Messaging becomes less precise. Sales processes become harder to manage. Forecasts become less reliable. AI recommendations become faster, but not necessarily smarter.

That is the real issue with B2B sales intelligence today. Too many companies still evaluate data providers with a phonebook mentality. They ask who has the most contacts, the biggest database, the broadest coverage, or the lowest cost per seat. Those questions are easy to compare, but they rarely answer the question that matters: will this data perform against our ICP, in our market, inside our sales stack?

Artificial intelligence raises the standard. AI tools depend on clean, structured, identity-resolved data. If the CRM has three versions of the same person, five versions of the same account, outdated titles, invalid email addresses, disconnected phone numbers, and inconsistent fields, AI will not fix the problem. It will operationalize the problem.

Identity resolution is the missing discipline. It is the ability to recognize that the same person or company appears across multiple systems and create one authoritative record. Without it, lead scoring, personalization, enrichment, intent data, pipeline analysis, and Revenue management all become suspect.

This is why sales management must treat data infrastructure as a strategic operating issue, not a software-administration issue. Bad data burns money in several directions at once. You pay for the data subscription. You pay reps to manually verify what the subscription should have solved. You pay sales operations to clean up the mess. Then you lose revenue because your team is working on bad records while competitors are already in the right relationships.

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