Helen Mackenzie

Both want to build trust and reduce the risk of a bad purchase. This frame is used to explain stalled deals, dry pipelines, event leads that go nowhere, and why persuasion is the wrong goal.

In a post on stalled deals, the solution is good, the return on investment stacks up and every buyer-side requirement is met, but the deal goes quiet. Mackenzie uses the twins idea to suggest the real obstacle may be human risk rather than the commercials.

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Buyers have learned to ignore generic outreach, mail merges and brief conference chats. The alternative is to build digital trust and be useful online long before asking for a meeting, so an in-person meeting continues a conversation rather than starts a cold pitch.

One post treats a leftover mail-merge token in a message as a signal of low-effort automation rather than personalisation. Another contrasts the excitement of a pile of scanned event badges with the familiar pipeline that follows: unanswered emails and follow-ups.

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They are also asking what happens if they make the wrong choice.

• That makes risk reduction, rather than persuasion, the thing that can move a stalled deal.
• Mackenzie cites an MIT Sloan Management Review article to support the point.

In a post about a deal that stalls for no obvious logical reason, Mackenzie describes a buyer side that seemed happy and a proposal that ticked every box, then asks whether the real obstacle was something more human than the solution or the commercials.

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Mackenzie credits the 70% figure to a study shared by Kerry Cunningham, not to a primary source quoted in the posts. The practical conclusion is that a salesperson does not need to be the deepest expert; they can be a trustworthy guide who connects a buyer's problem to the right solution.

In one post, a salesperson worries that AI-assisted content will make them look more expert than they are. Mackenzie distinguishes the subject-matter expert from the business development representative, describing the salesperson as a guide who knows where to find the water rather than the well itself.

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Instead of treating this only as an SEO or content-volume problem, Mackenzie argues it makes genuine expertise, helpful insight and an understanding of buyer challenges more important.

A post about AI search ends with a photograph of the moon over Eorodale between storms, using that calm moment to ask what people are putting out into the world and what they want to be known for. The post carries a disclosure that it was co-created with an AI tool.

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The posts reference an MIT Sloan Management Review article, a Meltwater analysis of AI citations, and a 70% buyer-preference figure credited to a study shared by Kerry Cunningham. Some posts link to the original article, and several disclose co-creation with Azpertilo.ai.

The 70% figure recurs across several posts, but the posts attribute it to a study shared by Kerry Cunningham rather than quoting a primary source. Where a link is included, readers can follow the original article from the post.

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Start here: the post asks why a deal can stall even when the solution and return on investment look right.

Helen argues that buyers are also weighing the personal risk of making the wrong choice. Her comparison of sales and procurement as “twins” frames both sides as trying to build trust and reduce risk, not simply complete a transaction.

For brands planning a campaign

For a buyer-psychology webinar, this offers a clear starting question: what human concern might be holding up a deal that looks commercially sound? An article could pair that question with examples from both buyer and seller perspectives.

This post addresses a salesperson’s worry that AI-assisted content might make them appear more expert than they are.

Helen distinguishes the subject-matter expert, who has deep knowledge, from the business development representative, who can guide someone to the right expertise. The “guide” and “water” analogy makes that distinction easy to grasp and gives social selling a practical role: help people find a solution rather than pretend to know everything.

For brands planning a campaign

A sales-training collaboration could turn this distinction into a session on responsible content: how representatives can share useful context, identify expertise and make a trustworthy introduction without overstating their own knowledge.

Helen uses that familiar mistake to show how automation can signal low effort instead of personal attention. She contrasts message volume with understanding the person receiving the message, then connects lost trust to the risk of competing on price late in a deal.

For brands planning a campaign

A campaign about digital trust could use the mail-merge example as a simple diagnostic exercise: ask participants to identify what a message communicates beyond its literal pitch, then rewrite it around the buyer’s situation.

This post contrasts the excitement of collecting event leads with the buyer’s experience of receiving a generic follow-up.

The badge scan is a brief contact, not proof of trust. Helen argues that consistent expertise shared before an event can make an in-person meeting a continuation of a conversation rather than the start of a cold pitch.

For brands planning a campaign

For a sales-training article, this supports a before-and-after event framework: build familiarity before the event, make the meeting useful, and follow up in a way that reflects the actual conversation.

The post asks what happens when public sales content becomes part of the information buyers encounter through AI search tools.

Rather than treating AI visibility only as a content-placement problem, Helen emphasizes the substance of what people publish: genuine expertise, useful insight and understanding buyers’ challenges. She links that advice to the possibility that today’s posts may shape what future customers learn from AI.

For brands planning a campaign

A webinar could explore how sales teams can publish material that is useful to people first, while recognizing that it may also inform AI-generated answers. Keep the discussion grounded in content quality rather than promising AI search visibility.

Mackenzie writes from having moved from leading procurement into sales, and uses that double view to explain why deals stall even when the solution, ROI and requirements all look fine. The frame is reused to explain dry pipelines, badge-scan leads that go nowhere, and why persuasion is the wrong goal.

States the twins idea first, then applies it to a concrete situation and closes with a question to the audience.

For brands planning a campaign

Gives a buyer-psychology session a distinctive angle a sales team may not have heard from a pure sales trainer: the same decision described from the procurement side. Works well for a joint sales-and-procurement audience rather than a sales-only one.

Examples: Source 1 · Source 2 · Source 3 · Source 4

Buyers have learned to ignore generic outreach, mail-merge tokens and 90-second conference chats, so the recommended shift is to build digital trust and be seen as a useful advisor long before asking for a meeting. In-person meetings should continue a conversation rather than start a cold pitch.

Opens with the symptom a sales team recognises (quiet pipeline, unanswered emails), reframes it as trust rather than effort, then names the behavioural change.

For brands planning a campaign

A natural spine for a webinar or article on rebuilding outbound around pre-contact credibility. A brand could pair it with a practical diagnostic, such as an audit of a team's existing outreach, to give attendees something to act on.

Examples: Source 1 · Source 2 · Source 3 · Source 4

Citing an MIT Sloan Management Review article, the point is that people facing a proposal are not only weighing features and ROI; they are asking what happens if they choose wrong. Risk reduction, not persuasion, is presented as the thing that moves a stalled deal.

Takes a published article as the starting point, adds a practitioner reading of what it means for a live deal, then invites other people's examples.

For brands planning a campaign

Fits a guest-expert brief on buyer psychology and de-risking decisions. The research is cited secondhand from an article rather than a primary study, so a brand wanting a data-led session should be prepared to supply or verify the underlying source.

Examples: Source 1 · Source 2

Some posts link out to the original article. Several posts also carry a disclosure that they were co-created with an AI tool.

Names the source, states the finding in plain language, then draws the sales implication and asks the audience a question.

The 70% buyer-preference figure recurs across several posts and is attributed to a study shared by Kerry Cunningham, not to a primary source quoted in the posts.

For brands planning a campaign

Useful for a sponsored research piece or a joint report: Mackenzie works from citable material rather than anecdote. The brand should expect to supply or approve the underlying sources, because the posts reference studies rather than presenting original data.

Examples: Source 1 · Source 2 · Source 3 · Source 4 · Source 5

One reports a Meltwater analysis of 9.5 million AI citations and argues that the LinkedIn content sales teams publish today helps shape what AI search tools tell future buyers, so genuine expertise and useful insight matter more than volume. The other answers the fear of posting AI-assisted content and being exposed in a real conversation, distinguishing the subject-matter expert from the salesperson and reframing the salesperson's job as the helpful guide who knows where to find the water.

Reframes the goal from 'being the all-knowing expert' to 'being the most helpful guide', and uses a specific conversation with a salesperson as the opening example.

For brands planning a campaign

A strong hook for a sales-training webinar on AI-assisted content and credibility: the brand can supply the AI-tooling angle while Mackenzie supplies the trust framing. A related article could cover what to publish when the seller is a guide rather than the deepest expert.

Examples: Source 1 · Source 2

One post offers three self-coaching questions for when you feel stuck: what have I tried already, what is getting in the way, and if I already knew the answer what would it be.

• Another covers realistic year-end planning instead of an overloaded to-do list.
• A heavier post on AI closes with a photograph of the moon and weather detail, and the lighter posts use Friday framing.

Short first-person posts that share a small practice or a moment of reflection and invite replies.

For brands planning a campaign

These posts show a relatable, low-production voice suitable for a co-hosted or conversational format. For a substantive expert brief, the trust and AI threads above are the stronger material; the lighter posts are supporting evidence of tone rather than topics to build a campaign on.

Examples: Source 1 · Source 2 · Source 3

The credit is repeated across posts on different subjects, from buyer psychology and stalled deals to event follow-up, sales automation and AI search. The posts do not describe what Azpertilo.ai is, what role it played beyond co-creation, or whether the arrangement was paid, so the commercial nature of the relationship is unstated.

Original disclosure

This post was co-created by me and Azpertilo.ai

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Mackenzie reports that a Meltwater analysis of 9.5 million AI citations found LinkedIn is a significant information source for the AI tools buyers use, and builds an argument about sales teams shaping that knowledge. The study is used as supporting evidence; no commercial relationship is disclosed.

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Mackenzie uses it to explain why deals stall despite good solutions and healthy ROI, and to argue that procurement and sales are driven by the same need to build trust and reduce risk. No commercial relationship is disclosed.

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Zides's Friday pipeline review and founder-led sales ceiling are practical pipeline discussions, close to Mackenzie's posts on dry pipelines and digital trust. Both use short LinkedIn posts that end with a question.

Zides focuses on the seller's operating cadence and founder capacity, using personal failure and simple math. Mackenzie focuses on the buyer's risk and the procurement side of the same decision, using buyer-psychology arguments and the sales-and-procurement twins frame.

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Kulyba's point that CRM has never closed a deal and that relationships track reality overlaps with Mackenzie's argument that pipeline is a trust problem. Both use LinkedIn commentary to challenge conventional sales practice.

Kulyba draws on enterprise telecom software sales and argues for creativity and questioning inherited methods, with examples such as Salesforce. Mackenzie draws on a move from procurement into sales and argues through buyer psychology and the sales-and-procurement twins idea.

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Stopper's value strategy series on mitigating risk and his forecast-review questions ask sales leaders to expose deal risk. Mackenzie's posts argue that buyers stall when they fear choosing wrong, and that trust and risk reduction move a deal.

Stopper writes structured sales-strategy frameworks and executive question lists aimed at improving deal review and pricing. Mackenzie writes narrative posts that explain the buyer's side and the shared sales-procurement view, often anchored in outside articles.

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The two posts reviewed show the mechanics rather than the theory: an hour every Friday for a pipeline review, same time, no exceptions, with every deal asked the same question — what would it take to move this toward close next week — so that by Monday the team knows which deals it is going after.

• Mark Zides frames the habit through playing goalie at Babson: see the whole field, be the last line of defence, and tell everyone where to stand whether they ask or not, except on a schedule instead of on memory.
• The second post supplies capacity arithmetic a trainer can put straight on a slide: 15 hours a week available for selling, one deal eating about 10 of them between calls, proposal and pricing back-and-forth, which lands at roughly 75 deals a year and about $3M at $40K a deal, with more leads only making the queue outside the calendar longer.
• That is a workshop exercise with a number attached, and it speaks to the same audience the brief targets, just from the seller's calendar inward.

The buyer is off-stage.

• These posts are about the seller's forecast hygiene and selling capacity, not about what the person across the table is weighing, so there is no counterpart to the reading of the MIT Sloan Management Review article on stalled deals or to the frame of sales and procurement as twins working the same decision from opposite seats.
• A trainer using this material would have to supply the buyer-psychology half of the webinar themselves.
• The tone is also first-person practitioner storytelling rather than a teachable sequence, and the evidence here is two posts, so the wider range of the work is not established.

Examples: Source 1 · Source 2

One post makes the argument through Salesforce's End of Software campaign — Salesforce did not invent SaaS, but it changed how customers buy and use software and built its positioning around saying so — and lands on the phrase that should worry any sales organisation: we have always done it this way.

• The prompt at the end, why are we selling it this way at all, is a usable discussion starter for a training cohort.
• The second post is the closest match anywhere in the alternatives to the trust and relationship territory in the brief: a CRM reported a deal as nearly done while the VP of Technology had just been replaced, the replacement had a preferred vendor and the budget was under review, all of it learned from a coffee or a five-minute informal call three levels below the decision-maker, none of it captured in a dashboard.
• The closing line — buyers do not buy software, they buy the person who will still answer the phone six months after the contract is signed — is the same claim the brief is built on, told from a 20-year telecom software seat.

There is less to build a co-authored asset around.

• The posts argue a position and give one supporting example; neither offers a named method, framework or exercise a training company can hand to a room, so the teaching structure has to be supplied by the trainer.
• The stated setting is long-cycle telecom software sold to technical buyers with competing stakeholders, a narrower world than a general B2B sales-training audience, and the two posts sit roughly five months apart, which limits what can be said about current themes.
• One of the two draws its evidence from an outside campaign rather than a live deal, so it illustrates the argument rather than proving it.

Examples: Source 1 · Source 2

The forecast-review post hands over five questions an executive should ask before a quarter closes — who can say no, why buy now, what business problem is being solved, is this deal getting stronger, will it close without the sales team forcing it — and reframes the point of asking: the best answer may be good question, I need to go work through that, and that is the review doing its job rather than failing.

• The risk post makes the pricing argument that supports it: price is negotiable, the consequence of business risk is not, and moving a deal from efficiency to risk mitigation changes the physics — urgency arrives on its own, more decision-makers join, and the conversation shifts from product features to business function, which is harder to discount because there is no clean number to push against.
• For a training company that wants an executive-facing module on why deals stall in the forecast, this is ready-made material.

It is deal-review and value-framing content for the executive table, not buyer psychology or digital trust.

• Nothing in the two posts addresses publishing, social selling or how trust is built before a buyer ever engages, which is the centre of the brief, so this alternative covers the commercial-discipline half of a session and leaves the brief's core topics uncovered.
• Both posts are short essay teasers that point readers to longer pieces elsewhere, so a trainer gets the argument and the question list rather than the full method behind them.

Examples: Source 1 · Source 2