David Brock writes and advises on B2B sales execution, helping sellers and sales leaders understand customers, improve buying conversations, and build the judgment to sell effectively.
David Brock writes about B2B sales execution: how sellers can help customers make decisions instead of relying on pitches, outreach volume, and playbooks.
His recurring challenge is simple: could a salesperson have a useful first conversation without talking about the product?
Brock argues that understanding a customer’s business and problems helps sellers ask better questions, build trust, and move stalled decisions forward.
Follow his work for practical ideas on customer conversations, sales leadership, and using AI to strengthen rather than replace judgment.
Brock connects sales performance to the way customers experience the buying process.
In his argument for improving win rates, he reframes the deals a team loses as a cost of its strategy, often tied to customer inaction rather than a competitor.
He makes the alternative concrete in a story about a stalled deal: instead of pitching, he asked a grocery retailer’s CFO about the cost of products discarded behind its stores.
The CFO challenged the estimate, worked through the numbers, and asked how Brock could help.
That focus on judgment also shapes Brock’s view of technology and productivity.
In a post about AI and sales time, he argues that automating work is not the first question; leaders should first identify work worth stopping, then use AI to sharpen sellers’ thinking.
Across these examples, Brock’s distinctive contribution is to turn abstract calls for better selling into practical questions about what customers need, what teams measure, and what they should change.
David Brock writes about why B2B selling underperforms even when teams hit their activity numbers, and what to do instead.
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Three arguments run through the material: sellers should understand the customer's business well enough to hold a conversation without mentioning the product; most losses come from customers deciding to do nothing, not from competitors; and success itself makes it hard to change a playbook that still looks like it is working.
Brock is skeptical that saving sellers time with AI improves results, and argues for stopping low-value work before automating it and for using AI to sharpen a seller's thinking rather than replace it.
The ideas are illustrated with specific stories — a stalled grocery-retail deal, a workshop where teams found roughly a third of their time could be cut, and inbox statistics from Brock's own prospecting experience.
Success makes change feel like losing your identity
Brock argues that doing well removes the reasons to change.
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When a company is a startup or things are going badly, it experiments and shifts direction.
Success replaces that with playbooks, processes, supporting metrics and rewards for compliance — and over time those stop being how the team works and become who it is.
When the market shifts, change no longer feels merely risky; it feels like losing an identity.
Sunk cost then pushes teams to double down on what produced the success.
Brock's proposed responses are to ask what should be stopped, to ask what the team would do if it could not use its current approaches, to look for ideas far from competitors because competitors are looking at the same things, and to reward people who experiment even when the experiment fails.
His sharper test is whether anyone can remember the last time the team changed something that was still working.
Brock contrasts the usual scoreboard — hitting numbers, outperforming peers, winning the Presidents Club trophy, holding the top-right corner of an analyst's chart — with a friend, Tobia La Marca, who chooses to measure himself against people who have studied the craft for decades rather than the colleague who closes more deals. La Marca reads history, strategy and research far outside sales; Brock presents that as the alternative to measuring yourself against the same scoreboard as everyone else.
Brock credits the framing to La Marca's essay on what he calls the mastery trap, and says he learns from every conversation with La Marca. The idea recurs across several of Brock's posts rather than appearing once.
Following the playbook is safe, and it is a ceiling
Brock separates the immediate cost of judgment from the immediate comfort of compliance.
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Judgment costs arrive right away: being wrong sometimes in front of everyone, having to explain why you did something the playbook did not call for, and going slower in a world that measures velocity.
Brock describes that as simply what learning feels like.
Following the playbook feels safer — hit the activity metrics, do what you were told, and if you lose, it was the playbook's fault.
Brock argues that is not safety but a ceiling: what you can do in five years is what you can do now.
The hard part is that nobody can tell when they have hit it.
He says he struggled to write the piece because it kept turning into an ROI analysis without numbers, until he reframed the cost of judgment as finding out what you are capable of and whether you can handle a future nobody can see.
Brock points to SaaS companies whose growth was slowing and whose win rates were sliding for years, with the data saying something was wrong, before AI arrived and the position crumbled — no one had seen a ceiling.
He uses Kodak as the famous version: the company invented the digital camera and chose to protect the film business, which he says was the rational call every single quarter.
Individually, he describes people who hit their numbers and look fine until a promotion, a global account or a team-leadership role reveals they have been fine for years without getting better.
This is the personal-cost companion to his argument about success at the organizational level, and it names La Marca's practice of "finding novelty every day" as the counter-habit.
Brock argues that treating time as the scarce resource is the mistake behind most AI-in-sales investment.
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The tools pitched to save sellers time have not improved performance in his account: win rates are declining, cycles are lengthening, fewer people make their numbers and customers are more disengaged.
His explanation is that much of the saved time was time that should never have been invested — outreach broadening when it should be narrowing to organizations that need to act now, and effort spent on deals that may be real but will never be real for that seller.
Automating research and call preparation, he argues, removes the work where judgment is built: the seller can follow a script, but when a customer says "tell me more" or "that's not important to us," there is nothing behind it.
His sequence is to ask what to stop first, then who should do what remains and what is falling through the cracks, and only then to automate low-judgment work or turn AI into something that challenges the seller's thinking instead of replacing it.
Brock describes running a workshop called "Sh*t we have to stop," in which teams sort through every activity, meeting and report that fills their time and ask why they are doing it and what would happen if they stopped.
In one session, the things people could stop immediately took roughly 30% of their time.
Only after that sorting does he raise AI, and then as a challenger — asking the seller what is really happening in the account, what evidence they have, and what they do not understand.
Sellers should understand the customer's business before the product
Brock gives clients a rule for first meetings: no talking about products, even if the customer asks.
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He splits the missing capability into customer acumen (understanding a customer's world, markets, metrics, workflows and language), problem acumen (understanding problems the way the customer sees them, including that in complex B2B the customer may never have faced the problem before) and financial acumen (how the customer makes money, funds decisions and what the problem actually costs).
Knowing the customer's business is the input, he says; acumen is what you do with it.
He also argues the capability is buildable rather than innate, and that it improves with every conversation about the customer's business.
A client's deal with a large grocery retailer had stalled, with everyone approving except the CFO.
Brock opened a meeting with the CFO by asking whether he realized the company was paying suppliers $15B a year to put their products in the green dumpsters behind its stores.
The CFO challenged the number, worked it out at the whiteboard and concluded his own estimate was over $20B a year, then asked how Brock could help.
The product was never discussed, and a deal stalled for months moved in 45 minutes.
Brock adds four years of work with Dr.
Howard Dover at The University of Texas at Dallas, where students interview at least ten executives in a single role; acumen scores start very low and are very high by the seventh to ninth conversation.
Brock cites figures that more than 65% of buying decisions end in No Decision Made and that over 70% of those who do decide have regret, which links this argument to his writing on loss rates.
Brock separates three kinds of customer conversation.
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Pitching and presenting is talking at customers.
Walking through a discovery checklist is talking to them — customers answer the seller's questions in a familiar ask-and-answer pattern, and neither party learns much.
Talking with customers is different: the agenda is set together, customers ask questions back, both sides leave having learned something, views change and trust develops.
Brock says the missing ingredient is customer and problem acumen — understanding what people are responsible for, how problems emerge, how customers recognize them and what happens if nothing is done.
On AI he is direct: it can supply the first question, but when the customer says "tell me more" or "that's not an issue for us," a seller without acumen is stuck.
His closing test is a measurement gap: teams measure calls, meetings, talk time and playbook compliance, but never test whether a seller can hold a 30-minute conversation with a customer without mentioning the product.
The 30-minute, no-product conversation is Brock's proposed test, framed as the question he puts to leaders: can your people actually talk with your customers? He sets it against the metrics organizations already collect, which he says never ask that question.
Brock turns a win rate into a strategy statement: subtract the win rate from 100 and you have the outcome your business strategy produces, whether that is 85%, 80% or 75% of qualified deals lost.
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It is not what gets reported to boards, which hear that the numbers will be hit.
His account of how it deteriorates is specific — under pressure sellers lower the quality of deals in their pipelines, win rates slip, sellers cannot manage the rising volume, more people are hired, costs rise, and the result is labelled scaling.
Losing is not free either: Brock cites research that losing a deal takes up to twice as long as winning one, counting SDR, sales engineering and management time along with proposals, pricing and legal approvals.
Most losses, he writes, are not to competitors, who are doing as badly, but to "No Decision Made" — which he reads as a failure to help customers buy rather than being outsold.
He also points to a human cost: sellers who lose eight or nine of every ten deals start giving up, and morale, burnout and turnover follow at every level.
Brock walks through the arithmetic: a slide from a 15% win rate to 12% means losing 88% of deals, and going from 15% to 30% doubles revenue without increased spending, because the time and resources are already being invested. He describes the 15% norm as an excuse, and argues the differentiator is being able to say the team wins 30% while competitors are stuck at 15%.
Prospecting should raise something the recipient wants to talk about
Brock writes from the receiving end.
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About 45% of his inbox each morning is prospecting, and roughly one message in 200 provokes his interest.
He describes the pattern: senders open by asserting they know what he needs without having researched him or his business, even though AI makes that easy; sequences continue after a "this is my last outreach" message, so the recipient knows more are coming.
He notes that many of the senders are highly visible on LinkedIn sharing advice on high-impact prospecting, and that at least half work for well-known companies.
The messages that worked, he says, were not heavily personalized and did not mention his posts — they raised issues his clients face and asked what he thought, which made him curious enough to look at their websites and profiles.
When he followed up, he found those senders had read his articles carefully; research was simply how they worked, not something they had to prove.
That leads to his reframing: prospecting is finding something the recipient wants to talk about, not finding people willing to listen to what you have to say.
He adds that underneath the pushback about not having time is a real fear — most sellers know products, scripts and playbooks, not their customers' businesses, because the systems, training and metrics never asked them to.
Brock counts the extremes rather than describing them generally: one well-known company has sent him 274 outreaches since January 2024 with no conversation, one seller had sent 16 touches since starting on August 11, and a prospecting "guru" changes his email address every few messages to get past spam filters, which Brock says has been going on for two years. In a shorter post he reduces the same complaint to a line: "Can we explore a mutual opportunity?" is the new "Buy my product!"
AI exposes a leadership problem rather than creating one
Reading a Wall Street Journal article about a family firm that never had a layoff in 75 years, Brock argues that AI is not creating a new problem but exposing a decades-old confusion between management and leadership.
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Managing to the numbers, working the dashboard and treating people as resources to deploy is, he writes, a philosophy that AI makes organizations tremendously effective at executing.
Much of the discussion of AI's effect on employment is about efficiency — how much more work can be done and how many fewer people are needed — and the phrase "human in the middle" rarely prompts the question of why the human is there.
Brock lists what he says cannot be automated: deciding what matters, establishing purpose, making the commitments purpose requires, and being accountable for the consequences of choices.
He closes with questions for leaders, among them whether they are using AI to avoid rethinking the work rather than automating it, and finally: are you using AI to avoid leading?
Brock contrasts The Gund Company, which he says has grown an average of 18% a year for the past decade and has not had a layoff in 75 years, with Microsoft's announcement of 60,000 voluntary reductions. He describes Gund's approach as measuring itself on taking care of each other, the customer and the business, with leaders going to where the work happens, listening and acting on what they hear, and holding high standards as part of caring rather than opposed to it.
Answers the question the whole AI-in-sales debate skips past: what should be stopped before anything is automated?
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Start here if you want David Brock's clearest statement of that sequence.
David Brock argues that treating time as the scarce resource is the mistake.
The AI tools pitched to save sellers time, he writes, have not improved performance: win rates are declining, cycles are lengthening, and customers are more disengaged.
His explanation is that much of the time being saved was time that should never have been invested — outreach broadening when it should narrow, and sellers spending up to twice as long losing a deal as winning one.
Automating research and call prep, in his account, removes the work where judgment is built: the seller can follow a script but has no answer when a customer says "tell me more" or "that's not important to us."
He describes running a workshop called "Sh*t we have to stop," in which teams sorting through their activities found roughly 30% of their time could be stopped immediately, followed by asking who should do what remains and what is falling through the cracks.
Only after that, he writes, does the automation question make sense.
For brands planning a campaign
The stop-then-automate sequence is a ready-made structure for a co-authored article or webinar: open with the workshop exercise, then apply AI to the low-judgment work that survives it.
Explains the economics argument behind everything else David Brock writes: the loss rate is not bad luck, it is what a strategy produces.
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A newcomer should read this to understand what he means by helping customers buy.
David Brock turns a win rate into a strategy statement: subtract the win rate from 100 and you have the outcome your business strategy produces, whether that is 85%, 80% or 75% of qualified deals lost.
His account of how it gets worse is specific — under pressure sellers reduce deal quality, win rates slip from 15% to 12%, volume rises, more people are hired, and costs are labelled scaling.
He cites research that losing a deal takes up to twice as long as winning one, counting SDR, sales engineering and management time along with proposals, pricing and legal approvals.
The losses, he writes, are mostly not to competitors, who are doing as badly, but to "No Decision Made."
He argues that going from 15% to 30% doubles revenue without increased spending, and points to a human cost as well: sellers who lose eight or nine of every ten deals give up, and morale, burnout and turnover follow.
For brands planning a campaign
The 15%-to-30% framing and the "No Decision Made" finding are quotable anchors for a co-authored piece. The post also promotes a live web conference with Gerhard Gschwandtner and Andy Paul, so check whether an equivalent event is current before referencing it.
If you only read one piece to see how he thinks about customer conversations, read the one with the grocery retailer and the CFO.
David Brock gives clients a rule for first meetings: no talking about products, even if the customer asks.
He breaks the missing skill into customer acumen, problem acumen and financial acumen, and illustrates it with a stalled deal at a large grocery retailer where everyone had approved except the CFO.
Brock opened the meeting by asking whether the CFO realised the company was paying suppliers $15B a year to put their products in the green dumpsters behind its stores.
The CFO challenged the number, worked it out at the whiteboard, and replied that his own estimate was over $20B a year, then asked how Brock could help.
The product was never discussed, and a deal stalled for months moved in 45 minutes.
Brock adds four years of work with Dr.
Howard Dover at The University of Texas at Dallas, where students interview at least ten executives in a single role: acumen scores start very low and are very high by the seventh to ninth conversation.
He also cites figures that more than 65% of buying decisions end in No Decision Made and over 70% of those who do decide have regret.
For brands planning a campaign
The dumpster story is the strongest single concrete example in the set and works as the opening anecdote for a session on stopping low-value work, because the deal moved without any product discussion.
Answers a question most sales leaders assume they have already settled.
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It separates three kinds of customer conversation and shows which one is being measured and which one matters.
David Brock distinguishes talking at customers, which is pitching and presenting; talking to them, which is walking through a discovery checklist where customers answer the seller's questions in a familiar ask-and-answer pattern; and talking with them, where the agenda is set together, customers ask questions back, both sides leave having learned something, and trust develops.
He argues the missing ingredient is customer and problem acumen — knowing what people are responsible for and how problems emerge, are recognised, and what happens if nothing is done.
On AI he is direct: it can supply the first question, but when the customer says "tell me more" or "that's not an issue for us," a seller without acumen is stumped.
His closing test is a measurement gap: teams measure calls, meetings, talk time and playbook compliance, but never test whether a seller can hold a 30-minute conversation with a customer without mentioning the product.
For brands planning a campaign
The 30-minute no-product test is a measurable, repeatable exercise a partner can run live in a webinar, which suits a co-authored format better than a purely argumentative piece.
Answers the leadership question underneath the automation question: whether AI is being used to avoid leading.
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Start here for the version of his AI argument aimed at executives rather than sellers.
David Brock responds to a Wall Street Journal article about The Gund Company, which he says has not had a layoff in 75 years and has grown an average of 18% a year for a decade, and contrasts it with Microsoft's announcement of 60,000 voluntary reductions.
His argument is that AI is not creating the problem but exposing a decades-old confusion of management with leadership: managing to the numbers, working the dashboard, and treating people as resources to deploy.
Most discussion of AI's effect on employment, he writes, is about efficiency, and the phrase "human in the middle" rarely prompts the question of why the human is there.
He lists what he says cannot be automated — deciding what matters, establishing purpose, making the commitments purpose requires, and being accountable for the consequences.
He closes with four questions for leaders, including whether they are using AI to avoid rethinking the work rather than automating it, and finally, "Are you using AI to avoid leading?"
For brands planning a campaign
This is the executive-level counterpart to the stop-then-automate argument and is well suited to a leadership audience. It leans on a named WSJ article and specific company figures, so re-check both before reuse in a partner's material.
Answers why capable people and companies keep doing what already works.
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It is his clearest explanation of the ceiling that playbook compliance creates.
David Brock writes that he struggled with this piece because it kept turning into an ROI analysis without numbers, until he saw the cost of judgment as finding out what you are capable of.
The costs arrive immediately, he says: being wrong sometimes in front of everyone, explaining why you did something the playbook didn't call for, and going slower in a world that measures velocity — which he describes as what learning feels like.
Following the playbook feels safe but is a ceiling, because what you can do in five years is what you can do right now, and the difficulty is that you don't know when you hit it.
He uses two examples: SaaS companies whose growth was slowing and win rates sliding for years before AI arrived, and Kodak, which he says invented the digital camera and chose to protect the film business because that was the rational call every single quarter.
He also names a friend, Tobia La Marca, whose practice is "finding novelty every day," and who questions himself in every meeting about how the work actually helps the customer.
For brands planning a campaign
Pairs naturally with the automation argument as the case for building judgment rather than replacing it, and the Kodak and SaaS examples give a partner concrete historical anchors.
Answers what wasted outreach actually looks like from the receiving end.
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It is the most concrete evidence in the set for the argument that volume is not the problem to solve with more volume.
David Brock writes that about 45% of his inbox each morning is prospecting and that roughly one message in 200 provokes his interest.
He counts the extremes rather than describing them in general terms: one well-known company has sent him 274 outreaches since January 2024, one seller had sent 16 touches since starting on August 11, and a prospecting "guru" changes his email address every few messages to get past spam filters.
He notes that many of the senders are highly visible on LinkedIn sharing advice on high-impact prospecting, and that at least half work for well-known companies.
The messages that work, he says, were not heavily personalised and did not mention his posts; they raised issues his clients face and asked what he thought.
When he followed up, he found those senders had read his articles carefully — research was simply how they worked, not something they had to prove.
For brands planning a campaign
The 1-in-200 and 274-outreach figures are memorable, verifiable-from-the-post details for a session on stopping low-value outreach before scaling it with AI.
Execution depends on conditions, not effort alone1
Customer understanding before product pitching
Brock argues that sellers should understand a customer’s business, problems, and financial pressures before presenting a product.
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He illustrates the point with a stalled retail deal that moved forward after a conversation about supplier payments and wasted inventory.
He distinguishes customer, problem, and financial acumen, and says sellers build it through repeated customer conversations.
For brands planning a campaign
A webinar or article could demonstrate how to prepare for a business-focused first meeting, using questions and a concrete customer scenario rather than a product pitch.
Brock frames low win rates as a consequence of sales strategy, not just an individual seller’s performance.
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He argues that teams spend substantial time and resources on deals that end in no decision, and that improving qualification, coaching, and understanding of how customers buy can be more valuable than adding pipeline.
For brands planning a campaign
Suitable for a leadership discussion about measuring deal quality and reducing avoidable losses before increasing outreach or headcount.
Brock contrasts high-volume, generic outreach with messages that raise an issue relevant to the recipient and invite their perspective.
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In his account, the messages that interested him did not announce that the sender understood his needs; they prompted curiosity, while the sender’s research showed in the quality of the conversation.
For brands planning a campaign
A practical campaign could compare a product-led outreach sequence with a customer-issue-led opening and ask sales teams to rewrite one message.
Brock questions whether saving sellers time through AI improves results.
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He argues that broad outreach and low-value work can consume reclaimed time, while research and preparation can help sellers develop judgment. His proposed sequence is to identify work to stop, decide what remains, and then automate low-judgment tasks or use AI to challenge a seller’s account thinking.
He describes a workshop exercise in which teams question the purpose of activities, meetings, and reports, then decide what to stop and who should do remaining work.
For brands planning a campaign
Strong fit for the proposed article or webinar: focus on stopping low-value work before automating it, and show how AI can prompt better reasoning rather than replace it.
Brock says success can make established playbooks and processes feel like part of an organization’s identity, making change harder even as markets shift.
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He recommends looking beyond competitors for ideas, rewarding experimentation, and asking what a team would change while its current approach still works.
For brands planning a campaign
Useful for a leadership or enablement conversation about continuous improvement, experimentation, and the risks of treating past success as proof that a sales process is still best.
Brock argues that automating work does not answer what work matters or what capabilities people need to build.
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In a post discussing the Gund Company, he contrasts managing to numbers with leadership that listens to employees, serves customers, and remains accountable for choices.
For brands planning a campaign
A campaign about AI and sales execution can connect workflow decisions to leadership responsibilities and employee development, rather than presenting efficiency as the only outcome.
In a post recommending Sheevaun Thatcher’s book, Brock highlights the idea that execution depends on the right elements coming together for the right people at the right time.
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This adds an organizational-systems angle to his other emphasis on seller capability and customer conversations.
For brands planning a campaign
Could support a discussion of how sales leaders design conditions for consistent execution, while avoiding a claim that this post provides a detailed framework.
The posts reviewed document no sponsorship, affiliate, investment, or ownership relationship.
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The one organization David Brock names as continuing work is The University of Texas at Dallas, where he says he has spent four years with Dr.
Howard Dover's program having students interview executives to build customer acumen; the posts do not state what that arrangement is commercially.
Other companies that appear—Microsoft, The Gund Company, Amazon—are examples or sources Brock cites in an argument, not brands he works for, advertises, or sells for.
The University of Texas at Dallas
Disclosed partnership
Brock writes that he has worked for four years with Dr.
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Howard Dover at The University of Texas at Dallas, where students interview at least ten executives in a single role and their acumen scores rise sharply by the seventh to ninth conversation.
He uses the program as evidence that customer and problem acumen can be taught and coached.
Brock describes the collaboration but not its terms, so the commercial nature of the relationship is unstated in the reviewed material.
Brock's posts are a running argument about why B2B selling underperforms and what to do about it.
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A reader new to the work can start with the pieces on holding a customer conversation without pitching a product, then move to the analysis of win rates and how many deals end in no decision, and from there to the writing on AI, time and judgment.
The thread connecting them is judgment: what sellers should understand about a customer's business, what leaders should stop measuring, and where automation helps versus where it removes the work that builds capability.
The posts are short and written for sales leaders and enablement teams, and most link to longer articles for the full argument.
Expect opinions stated as direct questions — "are you using AI to avoid leading?" — carried by concrete stories rather than frameworks.
Wright makes the same core move as Brock: separate what an AI tool does from what a seller should decide.
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Wright contrasts a chat window that speeds up research with a connected workflow that runs research, scoring and routing end to end while humans keep the decisions about who to pursue and when to hand off.
Brock argues the same way about judgment, saying automation should take the low-judgment work and leave the seller's thinking intact.
Both write short LinkedIn posts aimed at sales leaders about how the sales floor should actually operate.
Wright frames the argument around process and system integration inside a go-to-market motion, and posts as a vendor of that workflow.
Brock comes at it from the strategy and leadership side, asking teams to stop low-value work before automating anything and warning that automating research and call preparation removes the work where judgment develops.
A reader who wants the operational build-out should follow Wright; a reader who wants the argument about whether to automate at all should follow Brock.
Howerton's recurring point is that AI should carry the administrative load — follow-ups, data entry, reporting — so sellers can spend their attention on curiosity, deep listening and empathy with customers.
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That lands on the same ground as Brock's insistence that sellers should understand a customer's business before talking about a product, and Howerton also notes how much seller interaction never reaches the CRM, echoing Brock's concern that what teams measure is not what matters.
Howerton writes close to the product, describing field-sales mechanics such as a voice note that updates the CRM and drafts a follow-up, and often speaks directly to sellers about tools.
Brock writes to leaders about strategy, win rates and the cost of losing deals, and questions whether saving sellers time improves results at all.
Howerton is the more practical, tool-level read; Brock is the more skeptical, leadership-level read.
Seshan writes about the same shift Brock keeps returning to: moving sellers away from constantly reporting into systems so they can spend time understanding customers, building relationships and navigating complex decisions.
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Seshan describes agents that research accounts, prioritise prospects and prepare reps, with the stated aim of freeing human attention for the parts of selling that matter — the same division of labour Brock draws between low-judgment automation and seller judgment.
Seshan writes from inside the product side, explaining a platform roadmap and new agents, and treats adoption of the technology as the direction of travel.
Brock writes independent critique, names what he thinks is wrong with efficiency-led AI spending, and asks leaders whether they are using AI to avoid rethinking the work or to avoid leading.
Follow Seshan for the platform vision; follow Brock for the challenge to it.
David Brock’s posts are aimed at B2B sales leaders and sales teams working on customer conversations, sales execution, and AI.
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They may suit a campaign for that professional audience, especially one about improving sales judgment rather than simply increasing activity.
The posts show themes and intended appeal, not who follows or sees them.
Before booking, ask for recent LinkedIn audience demographics and, if the brief requires particular job roles or seniority, documented survey results or another source for those professional attributes.
The posts reviewed do not describe a sponsorship program, media kit, or brand-partnership offer.
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What they show is David Brock promoting his own advisory work and events: help developing sales acumen and the tools his team uses for it, a workshop called "Sh*t we have to stop" about cutting low-value sales activity, and a November web conference on improving win rates that he is hosting with Gerhard Gschwandtner and Andy Paul, where readers are asked to comment "Win More!" for information.
The contact route he gives readers is direct — "reach out to me," "contact me," or a link to a longer explanation — rather than a partnership page.
A brand that wants to work with him should treat this as an approach to discuss scope, fees, and deliverables directly, not as a package to select from a published menu.
Nothing reviewed states whether he takes sponsorships outside this material, so that remains open rather than answered.
A B2B sales enablement company wants to feature a thought leader on AI and sales execution, and proposes a co-authored article or webinar on stopping low-value sales work before automating it.
Reasons
The proposed topic is David Brock's own argument, not an angle imposed on him. He writes that most AI sales tools on the market promise saved time, yet win rates are declining, cycles are lengthening, and customers are more disengaged. His explanation is that much of the time being saved was never worth investing, and his recommended order is to stop the work first, then decide what remains, then automate only the low-judgment parts.
He brings a worked exercise, not just an opinion. He describes a workshop called "Sh*t we have to stop," in which teams question the purpose of each activity, meeting, and report, and reports that one session found roughly 30% of participants' time could be stopped immediately. That is a usable spine for a co-hosted session: run the exercise live, then apply AI to what survives.
He is comfortable arguing against the grain of his own audience. He says the work sales teams are most eager to automate — account research and call prep — is where judgment is formed, and that a seller handed the research cannot answer when a customer says "tell me more." A webinar built on that position gives the sponsoring company a position to react to rather than another generic AI-in-sales panel.
The claim is backed by concrete scenes a partner can reuse: the grocery retailer whose CFO recalculated the cost of dumping suppliers' products at the whiteboard, moving a deal stalled for months in 45 minutes without any product discussion, and the four years of interviews with Dr. Howard Dover at The University of Texas at Dallas, where acumen scores are reported as very low at the start and very high by the seventh to ninth conversation.
He already produces the surrounding work. He promotes a workshop by name, hosts a November web conference with Gerhard Gschwandtner and Andy Paul on improving win rates, and points readers to longer articles. A co-authored piece fits an existing habit of public teaching rather than requiring him to start one.
The commercial route is a direct conversation. The reviewed material shows no sponsorship program, media kit, or format list — the routes he gives readers are "reach out to me," "contact me," or a link to a longer explanation. For an enablement company this is ordinary: negotiate scope, fee, and deliverables directly instead of selecting from a published menu.
Watch outs
Nothing reviewed states whether he accepts paid partnerships or what terms he works on, so budget and exclusivity have to be settled before any co-marketing commitment.
Several posts link outward to longer articles and to other people's work. Those linked pages were not read here, so any claim about their contents must come from what he says about them, or from reading them separately before publication.
His posts carry few visible dates, so references to "recent" arguments should be time-checked against his current output at the moment of the campaign.
When to choose a specialist
Poor fit for David Brock as the fronted expert.
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Brief
A conversational-AI vendor launching a self-serve outreach product asks for a named sales expert to front a launch webinar promising more meetings per rep within a quarter, with messaging that volume and personalization at scale are the fix for missed pipeline targets.
Reasons
The core promise contradicts his published position. He argues that broadening outreach is the mistake and that effort should narrow to the accounts ready to act; he writes that sellers already spend up to twice as long losing a deal as winning one, and that adding pipeline, outreach, and headcount while win rates slip is how costs rise under the label of scaling. A launch built on "more meetings from the same headcount" asks him to endorse the mechanism he says causes the loss.
His evidence points the other way. He reports that about 45% of his morning inbox is prospecting, roughly one message in 200 provokes his interest, one company has sent him 274 outreaches since January 2024 without a conversation, and a prospecting figure changes email addresses every few messages to get past spam filters. Asking him to speak for high-volume outreach invites him to repeat exactly those examples on the vendor's own stage.
Automation of research and call prep is his stated counter-example, not his recommendation. He says that when AI hands a seller the research and the call prep, the seller never develops a perspective and has no answer when the customer pushes back, and that automating low-judgment work is the smaller opportunity compared with using the tools to sharpen thinking.
A quarter-long meeting-volume target would need measured outcome data the reviewed material does not contain. His figures are described in prose — win-rate ranges, the relative time cost of losing versus winning, the reported shift in acumen scores — and there is no post-level performance or audience-measurement data in the set to support a hard numeric promise.
The audience alignment is also thin for this brief. The reviewed posts address B2B sales leaders and teams working on customer conversations, execution, and AI, and they carry no follower or engagement data. A launch aimed at self-serve tool buyers may not be the room his material speaks to.
The fallback of buying a brief mention would sit badly beside the argument. His criticism of prospecting is partly aimed at people who are highly visible on LinkedIn sharing advice on high-impact prospecting while sending unreplied sequences. A paid endorsement from him in that category would undercut the credibility the material rests on.
What would change the decision
A brief reframed around stopping low-value work before automating it, with the product positioned for the work that survives that filter, would move into the strong-fit case.
A leadership-level session on whether AI is being used to avoid rethinking the work, rather than to replace reps, would suit his material on management versus leadership and his closing question, "Are you using AI to avoid leading?"
A worked campaign example
Assets
A one-page worksheet reproducing the stop-list exercise: columns for the activity, why it is done, what would happen if it stopped, and who should own what remains.
A scripted 30-minute no-product conversation prompt set for a manager to run with one rep, with a simple pass or fail recording line.
The co-authored article following the same five-part structure, with the worksheet embedded and downloadable on its own so it works outside the session.
Audience
Sales leaders and enablement or sales-operations leads at B2B companies who are currently buying or piloting AI tools for their sales teams.
Format
One 60-minute co-hosted webinar plus one co-authored article adapted from the same script, with a short written worksheet carrying the stop-list exercise.
Measurement
Track worksheet downloads and completed no-product conversation tests reported back after the session, alongside the usual registration and attendance counts. Those two signals show whether the audience used the sequence or only watched it. Registration and attendance alone will not show that.
Opening angle
Run the arithmetic live. Ask attendees to subtract their win rate from 100 and read the result back to themselves as a strategy statement. The point of the exercise is the claim that starts the argument: the loss rate is not bad luck, it is the outcome the current strategy produces, and most of it shows up as no decision rather than a competitive loss.
Outline
Minutes 0-10: The arithmetic. Win rate subtracted from 100, stated as a strategy outcome. Introduce the sequence the session will follow: stop, then decide who does what remains, then automate.
Minutes 10-25: The stop exercise. Walk the audience through the workshop question applied to a single activity, meeting, or report they own: why are we doing this, and what would happen if we stopped? Share the reported result that one workshop session found roughly 30% of participants' time could be stopped immediately, with the caveat that this is his reported experience in a session rather than a benchmark.
Minutes 25-40: The judgment case. Why automating research and call prep removes the place where perspective is built. Use the scenario where the customer replies "that's not important to us" and a scripted seller has no answer. Then contrast the two uses of AI: producing a briefing document, or prompting the seller to explain what is really happening in the account and what evidence supports it.
Minutes 40-52: The customer conversation standard. The rule for first meetings that the seller cannot discuss the product even if asked, and the measurement gap he identifies: teams track calls, meetings, talk time, and playbook compliance, but never test whether a seller can hold a 30-minute customer conversation without mentioning the product. Offer that test as the session's takeaway experiment.
Minutes 52-60: The leadership question. Close on whether the team is using AI to rethink the work or to avoid rethinking it, and hand the audience the worksheet plus one next step.
What to settle before booking
Whether David Brock will co-present, and on what fee and exclusivity terms. No published partnership format, media kit, or fee information exists in the reviewed material, so the arrangement has to be negotiated directly.
Whether the sponsor will accept a session whose central claim is that more outreach and more pipeline are the wrong first move. If the campaign cannot accommodate that position, this is the wrong pairing.
Which figures the sponsor will put in marketing copy. The win-rate ranges, the relative time cost of losing versus winning, and the reported acumen-score shift come from his written accounts; where a figure will be quoted publicly, re-check it with him and cite the source he names.
Why it works
The session does not ask David Brock to argue a sponsoring company's case. It hands the audience a decision sequence his published work already sets out — stop low-value work, assign what remains, automate only the low-judgment parts — and the sponsor's tool enters the conversation at the point in that sequence the sponsor can honestly occupy. The worksheet and the 30-minute test are the parts attendees can use on Monday, and they are the parts that carry the sponsor's name into a team meeting rather than a single slide.
Choose Zach Wright when the sponsoring company wants the session aimed at SDR leaders and front-line sales managers rather than senior sales leadership, and wants the argument framed as an agentic workflow problem rather than a customer-conversation problem.
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Wright's version of the same brief is that most AI-for-sales pilots buy a chat window, not a workflow: the seller still reads the answer, checks CRM, pastes into Slack or a sequencer, and updates fields by hand.
The proposed fix is to dissect the SDR process end to end — inbound qualification, outbound targeting, account-executive handoff — and automate the places where a seller digs through CRM, rebuilds research, or rewrites cold emails and call notes, while humans keep the decisions about who to pursue, who to pass, and when to hand off.
For a sponsor whose product sells to that audience and lives inside the workflow rather than beside it, this is a more operationally specific pitch than the stop-list exercise, and it names the exact steps the tool replaces.
Wright's posts are tied to Syft AI and read as a product position — the agentic side is identified with a named tool — so the sponsor shares the stage with a competitor-adjacent product instead of a neutral teaching voice.
The reviewed material is also thin: two posts from late September 2026.
And the order of the argument shifts.
Wright compresses the stop step into removing manual bottlenecks and moves quickly to automating the process end to end, so an audience expecting the win-rate arithmetic, the judgment-built-by-research case, and the 30-minute no-product conversation test will not get them.
Choosing Wright trades the diagnostic half of the brief for a workflow-automation half.
Choose David Howerton when the sponsor wants a field-sales and CRM-capture angle and a relational frame — elevate the relational, automate the transactional.
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Howerton brings audience-ready numbers and a live product story that fit a conversation-capture brief: 44% of seller interactions never make it into CRM systems, and top performers using AI spend twice as much time with customers because they waste fewer minutes.
The product account is concrete — a seller says what happened in about thirty seconds right after the conversation, and CRM entry, a drafted follow-up, and later task execution happen without them, with one tap to confirm before anything goes live.
If the sponsoring company sells in that capture-and-follow-up space, Howerton can demo the mechanism the sponsor is actually selling.
Howerton's posts are largely product promotion, several closing with a direct invitation to make contact, and one is a comment on another person's post rather than a standalone argument.
The sequence is also reversed from Brock's.
Howerton starts by automating the administrative work and freeing the seller for the relational part; that is close to the automation-first order Brock argues against, and it does not carry the stop-first filter or the loss-rate framing.
Choosing Howerton means trading the diagnostic thesis of the brief for an automate-the-transactional thesis, and the reviewed evidence is two posts, one from May 2025 and one from August 2026.
Choose Arvind Seshan when the sponsor wants platform-scale reach and the vendor-roadmap view of agentic selling.
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Seshan's posts are Sales Cloud announcements from the Dreamforce keynote: Momentum turns conversations into context, Hunter is a new outbound sales agent that researches accounts, prioritizes prospects, drafts outreach, learns from calls, emails, and CRM history, multithreads accounts, and prepares reps for calls, and Salesforce in Claude puts sales skills into a third-party assistant. The frame — from AI assistant to AI teammate — suits a sponsor launching an agentic product and wanting a named platform executive to describe where the category is heading.
Seshan is a platform executive, so the material is company announcement rather than an independent teaching position, and the entire direction is that agents take on the research, preparation, and repetitive execution.
That is the automation-first order the brief is built to question, so a sponsor using Seshan gives up the stop-the-low-value-work-first thesis and the judgment case about sellers who cannot answer when a customer pushes back.
It is a stronger fit for a launch or roadmap session than for a co-authored argument, and the reviewed evidence is two posts from September 2026.
Based on 11 posts from David Brock's LinkedIn account, all read in full, covering customer conversations, customer and problem acumen, win rates and lost deals, prospecting and outreach, AI and sales time, judgment, leadership, and organizational change.
The posts carry no publication dates in the material reviewed, so no timeline is claimed and no post is described as recent.
Several posts link outward to longer articles, an essay by Tobia La Marca, and a book by Sheevaun Thatcher; those linked pages were not reviewed, so anything said about them here stays within what Brock writes.
The material also contains no audience demographics, post-performance data, published sponsorship formats, or fee information, and does not state whether Brock takes paid partnerships.
Recent engagement
Across their last 9 LinkedIn posts, the median post got 19 reactions and 9 comments. Checked 2026-11-02.
