Paul Hassels Mönning

The remedy is deliberately small: choose one important conversation, spend 15 extra minutes preparing, and answer three questions — what is really happening for this customer, which crucial question did you miss last time, and what do you want to learn beyond SPIN-selling, MEDDIC or your own method? Paul also suggests bringing a Marketing, Product or Customer Success colleague, since two people can catch nonverbal signals that AI transcription tools such as Fireflies, Jamie or Gong miss.

Paul turns the argument into a one-conversation exercise, citing Pieter Winsemius's book 'Speel nooit een uitwedstrijd' and the French phrase 'reculer pour mieux sauter' to make the case for slowing down before speeding up.

Read original

Transcribing calls is a useful first step; stopping there leaves the CRM as a management-control tool rather than a learning tool. Their alternative is a team that learns from transcribed and summarized conversations in HubSpot, Microsoft Dynamics or Salesforce, with continuous AI-supported practice — naming Reppic — plus occasional specialist trainers, since hiring one every day is unrealistic.

Paul points to companies that log calls and fill CRM fields, then asks what would change if the team studied those conversations together. In a separate post, they note that transcription tools miss nonverbal signals, so human observation still matters.

Across the posts, the emphasis shifts from 'transcribe first' to 'learn from transcripts with people in the room'.

Read original · Original 2

They also argue for ending relationships that drain money or energy. Fit affects the quality of the work and the relationship, not just revenue.

A machine builder from the German border, quoted by Paul, says demanding behaviour one moment and open discussion of necessary improvements the next go together with going into the Kneipe for a large Krombacher or Warsteiner. The example shows fit as chemistry and candour, not just firmographics.

Read original

The foundation of the commercial process and 'house' has to be in order first, and small and medium B2B teams need use cases within reach.

• They put this to the test: generating a graduation image with NanoBanana2, hitting a Gemini refusal and building a prototype learning-and-development environment for B2B marketing, sales and customer success teams with Lovable.
• Paul says the certification did not make them an AI guru; it sharpened their understanding of the conditions for adoption.

The concrete test is a prototype, not a strategy slide: Paul tries tools, hits friction and uses the exercise to judge what a commercial team can realistically adopt.

Paul describes a love-hate relationship with AI and selective use because of energy and water consumption, then completes the Certified AI Business Professional programme and teaches in Beeckestijn's B2B Marketing & Sales programme. The direction is more hands-on, not less cautious.

Read original · Original 2

Buyers and algorithms both reward visible proof, they argue, so sellers should show real expertise and experience instead of relying on a smooth pitch. A solution pitch can be part of the mix, but it should not be pushy.

Paul describes a webinar with real expertise, real customers speaking unscripted, genuine entertainment and a solution pitch that was present but elegant and not pushy. They point to a PDF checklist for four sales-process steps plus a bonus step.

Read original

In one post, they explain that Google lets people mark preferred sources and suggest setting dutchmarq as a preferred source for topics they write about — sales enablement, B2B marketing, business-development training, content marketing, HubSpot.

• They link to the book Brainbound Marketing and other articles, then suggest readers share the tip with clients, relations and partners in a newsletter or at an event.
• The idea is practical: help people find useful explanations faster and give businesses a simple tactic to pass on.
• The post promotes their own book and brand.

The preferred-source setup is the tactic: readers can choose which source appears more clearly in search results for topics Paul has written about.

Read original

Start here for practical advice and a clear picture of the human cost of an overloaded sales calendar.

Paul opens with “Meer doen ≠ meer bereiken” and describes a familiar failure: as calendars fill, preparation drops.

• People rely on experience and autopilot, ask fewer questions, listen less sharply and jump to solutions before understanding the customer’s needs.
• The post offers a concrete exercise: choose one important conversation and spend 15 minutes longer preparing.
• Answer three questions: What is really going on?
• Which crucial question did you miss last time?
• What do you want to learn beyond standard SPIN-selling, MEDDIC or your own method?
• Paul also recommends bringing a colleague from Marketing, Product or Customer Success: two people can catch nonverbal signals that AI transcription tools such as Fireflies, Jamie or Gong miss.
• Pieter Winsemius’s book “Speel nooit een uitwedstrijd” and the French phrase “reculer pour mieux sauter” reinforce the case for slowing down.

For brands planning a campaign

A sales-enablement or training company can build a webinar or guide around meeting preparation, question quality and cross-functional attendance rather than “more calls” targets. The 15-minute exercise and named tools give mid-market sales leaders a practical hook.

Start here for the argument that transcribed calls are useful only when teams learn from them.

Paul cites the claim that in 70% of the buying journey the prospect is not waiting for your account manager.

• Even so, in long B2B sales cycles the human still makes the difference.
• Paul describes a common half-step: companies transcribe sales calls, log them, fill the CRM, and let the sales manager check.
• That makes CRM mainly a management control tool rather than a team learning tool.
• Paul points to a different use: learning as a team from transcribed and summarized conversations in HubSpot, Microsoft Dynamics or Salesforce, with an AI-supported platform such as Reppic for continuous attention and occasional specialist experts for targeted training.
• The post ends by asking readers which AI learning-and-development tools they have used and what they like or distrust.

For brands planning a campaign

For a sales-training provider, this supports a collaboration on AI-supported coaching that pairs continuous conversation review with expert intervention. Paul’s position is clear: AI is not the trainer; it makes coaching continuous and evidence-based.

Start here for concrete fit criteria and a rare discussion of ending poor-fit customer relationships.

Paul illustrates the point with a machine builder from the border region who does a lot of business with German customers.

• The owner says demanding behaviour one moment and openly discussing necessary improvements the next goes hand in hand with going into the Kneipe for a large Krombacher or Warsteiner.
• Paul turns that into a personal ICP checklist: high-value solutions, international reach or ambition, attention to marketing, sales and service/customer success, a culture of openness, innovation, team spirit and fun, a team that goes the extra mile, good customer value over a longer relationship, and an intrinsic drive to make customers, the industry and the world better, healthier, smarter and more sustainable.
• Paul also says saying goodbye to loss-making customers belongs to this, not only in financial terms but in energy and mutual fit.
• The post compares the business question with politics, mentioning Macron and Starmer at the White House, while noting the comparison is imperfect.

For brands planning a campaign

A campaign on ICP-focused selling can use this checklist to prompt discussion among sales leaders at manufacturers. It also raises a less common topic: account selection and when to leave poor-fit customers, not just lead generation.

Start here for the link between Paul's own study, Paul's teaching role and Paul's scepticism about AI hype.

Paul lists the ways Paul has kept skills sharp as an entrepreneur: webinars, e-learning at HubSpot Academy, conferences, events, and time with clients and prospects in B2B.

• Paul describes a love-hate relationship with AI, noting being an early adopter compared with many peers, and says Paul prefers to think independently and use generative AI selectively because of energy and water consumption.
• Paul still concludes that AI is here to stay and can help human communication and creativity.
• The concrete step: Paul started the Certified AI Business Professional programme at Beeckestijn Business School, a practical Post-HBO programme, with a kickoff from Bart Meerdink and Silke van der Werf.
• Paul connects the study to a use case and hackathon in B2B marketing and sales and to Paul's role as a core lecturer in Beeckestijn's B2B Marketing & Sales programme.

For brands planning a campaign

A training provider can position Paul as a practitioner who both studies and teaches AI in B2B marketing and sales. The honest scepticism and the specific programme details make a stronger webinar or course collaboration than generic 'AI expert' positioning.

Start here for a concrete account of an AI certification project, including tools, a failed image prompt and a realistic caveat.

Paul describes returning to school in autumn 2025 for the Certified AI Business Professional programme and becoming a certified AI Business Professional.

• The post is specific about the work: Paul tried to generate a graduation image with NanoBanana2 and found it was not simple; Gemini replied that it could not help with that image; Paul made a prototype of an L&D environment for B2B marketing, sales and customer success teams with Lovable and found that almost easier.
• Paul includes a practical caveat: the programme did not make Paul an AI guru, but it sharpened Paul's view of the conditions a commercial process and 'house' need in order, and the use cases within reach for small and medium-sized B2B companies that only have Copilot, ChatGPT or Gemini switched on for employees.
• Paul's line is that adoption is not the same as having the licence in house.

For brands planning a campaign

This gives a training provider direct evidence for a practitioner-led session on AI adoption in mid-market B2B. The failed image prompt and the distinction between having a licence and achieving adoption offer a realistic, non-hyped angle.

Start here for a short, concrete standard a training provider can adopt.

Paul describes coming out of a webinar where the energy was high: real expertise was shared, real customers spoke without a script, and the session was genuinely entertaining.

• A solution was pitched, but elegantly and without pressure.
• Paul connects that experience to Google's E-E-A-T criteria — expertise, experience, authoritativeness and trustworthiness — and argues that the same four qualities make the difference in B2B sales in the AI era.
• The post points readers to a PDF for checking how they handle the four steps in the sales process and adds a bonus step after that.

For brands planning a campaign

A sales-enablement company can use this to plan a webinar featuring unscripted customer voices, demonstrated expertise, light entertainment and a soft pitch. It also gives Paul a ready-made argument for why human proof still matters in AI-assisted sales.

When calendars fill up, preparation drops.

• Sellers lean on experience, ask fewer questions, listen less sharply and jump to solutions before understanding the real need.
• The practical approach is to slow down one important conversation, spend 15 extra minutes preparing, and answer three questions: What is really happening for this customer?
• Which crucial question was missed last time?
• What should be learned today beyond standard SPIN or MEDDIC prompts?
• Paul also suggests bringing a Marketing, Product or Customer Success colleague, because two people can catch nonverbal signals that AI transcription tools such as Fireflies, Jamie or Gong can miss.

A one-conversation exercise with three preparation questions and an optional cross-functional partner.

The post cites a book and names transcription tools as examples, but does not evaluate them.

For brands planning a campaign

A sales enablement or training company can build a webinar or workshop around preparation routines and listening discipline.

• The hook is a measurable experiment: prepare one conversation differently, with a cross-functional observer.
• It also supports a balanced message: AI call tools capture words but do not replace human attention.

Examples: Source 1

A machine builder from the German border illustrates the fit: demanding at one moment, open to necessary improvements the next, and willing to continue the conversation over a drink. Paul also argues for actively parting with customers that drain money or energy.

A personal ICP checklist paired with an account-review question: who gets the red carpet, who gets a functional relationship, and who should be let go?

The criteria are Paul's own, not a validated framework.

For brands planning a campaign

A sales enablement firm can build an ICP-focused selling session around account selection and de-selection.

• The machine-builder example offers a direct entry point for mid-market manufacturers.
• The practical output: a shared ICP checklist and a review of which accounts deserve more or less effort.

Examples: Source 1

AI changes the buying journey, but in long B2B sales cycles the human still makes the difference, making effective sales conversations more important.

• Transcription is a good first step, yet many teams stop at logging calls and filling the CRM.
• The result: a management control tool rather than a learning tool.
• Paul asks what would happen if a team learned from transcribed and summarized conversations in HubSpot, Dynamics or Salesforce.
• They favour a mix of continuous AI-supported learning, naming Reppic as an example, and occasional guidance from a specialist expert; hiring a trainer every day is unrealistic.

A blended model: continuous AI-supported practice plus periodic specialist training.

Reppic is named as an example; the post does not establish a commercial relationship.

For brands planning a campaign

This is the closest fit for a campaign about turning CRM and transcript data into continuous coaching.

• A training company can propose a webinar or content collaboration on the subject, with expert-led sessions for moments that need a human trainer.
• The angle should be blended learning, not an AI-only promise.

Examples: Source 1

They say the program did not make them an AI guru, but sharpened their view of the conditions a commercial process and its foundations need before use cases can work. The post points to SMB B2B teams with Copilot, ChatGPT or Gemini licences that have not turned access into adoption.

Hands-on tool tests and a prototype build.

The prototype and images are described, not shown in the corpus.

For brands planning a campaign

AI vendors and training providers can use this practitioner angle for SMB-focused content: show a small prototype, name the friction, and focus on adoption conditions rather than licence counts. A co-created demo or webinar suits a brand seeking practical credibility without guru claims.

Examples: Source 1

The solution pitch was present but elegant and non-pushy.

• They apply the marketing idea of E-E-A-T—expertise, experience, authoritativeness and trustworthiness—to B2B sales in the AI era, arguing that the same qualities distinguish effective sellers.
• The post offers a PDF on four sales-process steps and a bonus step.

An E-E-A-T checklist applied across the sales process.

The referenced PDF checklist is not in the corpus, so its exact steps are unverified.

For brands planning a campaign

A sales training brand could co-host a webinar built on real customer voices, expert demonstration and a non-pushy pitch. The content angle: trust in AI-era selling—what buyers can verify, what sellers must show, and how to make expertise visible without overselling.

Examples: Source 1

They describe themselves as an early adopter relative to peers but remain selective about generative AI because of its energy and water use; they prefer to think for themselves.

• They still see AI as useful for enhancing human communication and creativity.
• They started the Certified AI Business Professional program at Beeckestijn Business School and also teach in its B2B Marketing & Sales program, linking their learning journey to a use case and hackathon.

A formal post-HBO program combined with ongoing practice and teaching.

Ask for learning outcomes and results; the post gives only a broad outline of the program.

For brands planning a campaign

Education and training providers can position Paul as a practitioner-educator for AI adoption content aimed at commercial leaders.

• A webinar or curriculum collaboration could pair hands-on use cases with a candid discussion of selective AI use, energy costs and human skills.
• The fit is strongest when the brand wants reflection as well as tool demos.

Examples: Source 1

They point to their book Brainbound Marketing and to articles, whitepapers and blogs, then suggest sharing the tip with clients, relations and partners in a newsletter or at an event.

A step-by-step preferred-source setup.

Because the post promotes Paul's own brand and book, ask for independent evidence before relying on its claims about search-ranking effects.

For brands planning a campaign

A search, content or marketing-tools brand could collaborate on a short explainer about preferred sources and discoverability in AI-mediated search.

• The format suits a newsletter, event segment or co-branded practical guide.
• Frame it as a useful tactic, not a ranking guarantee.

Examples: Source 1

They name the school as the provider of the Certified AI Business Professional programme, completed in autumn 2025.

View example

The post does not state ownership, employment or payment.

View example

Like Paul, they start with the commercial system a team already has and ask what needs to be in place before AI can help.

Gabriel's work covers agency-side HubSpot implementation and AEO for clients, including CRM onboarding and answer-engine visibility. Paul's focuses on sales-conversation coaching, customer fit and training commercial teams.

Read original · Original 2

That build-and-test approach echoes Paul's work on prototyping and the conditions for adoption.

Erik focuses on ecommerce data infrastructure and AI-agent commerce; Paul on B2B sales conversations, sales learning and ICP fit.

Read original · Original 2

In a post about HubSpot and AI agents, Gabriel connects CRM structure, customer history and sales conversations to better-informed agents, while keeping human oversight in the picture. That gives a HubSpot-focused campaign a clear systems-and-context angle.

The available examples focus on CRM adoption, AI agents and company visibility—not sales coaching routines or ICP-focused account selection.

• Paul’s posts are the closer match when the campaign needs practical conversation preparation, team learning from call summaries and customer-fit decisions.
• Ask for audience data before targeting mid-market manufacturing sales leaders.

Examples: Source 1 · Source 2