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Minco de Boer
Sales Leader
about
Minco de Boer
Minco de Boer is an experienced sales and GTM leader with extensive expertise in managing complex B2G, B2B and B2B2C sales environments in companies like Google and Deliveroo. He has a strong track record in driving growth through cross-functional collaboration, combining innovative technologies with strategic insights to optimise sales and marketing results. Passionate about leveraging AI and data-driven strategies, Minco consistently pushes the boundaries of what’s possible in today’s fast-evolving market landscape.
How would you describe the ideal revenue generation model? Is it more sales-led or marketing-led?
Ideally it is customer led, which requires a carefully balanced approach in any organisational setting, to ensure solid collaboration across the go-to-market funnel and any function touching it. Whether it's strategic planning or day-to-day execution, you will want to maintain open communication, and double down on aligning OKR’s and KPI’s. Rather than one function or role leading over the other, it’s really about each team contributing where their strengths lie. For example, marketing supports sales by generating leads, building the brand and gathering insights, while sales focuses on nurturing relationships and closing deals. Vice versa, sales feeds marketing (and product) with first hand customer insights with a structured and well documented cadence.
This ideal balance is particularly valuable because it leverages the unique contributions across the teams, enabling a truly holistic approach to revenue generation. By integrating insights from marketing into the sales strategy, you can ensure that both functions are moving in the same direction, focused on shared goals. The ability to combine resources and collaborate cross-functionally will make the process more adaptable and efficient, which is ultimately a function of the quality of the teamwork at play
In the evolving B2B and B2G landscape, how do you see marketing and sales evolve?
It’s probably mostly about efficiency and effectiveness driven by new technologies. In budget constrained conditions, the key focus is to reach more of the right customers faster while maintaining or reducing the level of resource and expenditure. Marketing and sales need to support each other here, and that starts with shared goals and strategies. One of the more exciting developments is the use of generative AI, which can help marketing, pre-sales and post-sales activities. For example, AI can support SDRs by automating repetitive tasks, freeing them up to focus on more strategic activities, like persona development. Similarly, it can improve and scale lead nurturing across the journey by providing tailored content and solutions at speed with higher volumes. Another good example is the process preceding bid / no-bid recommendations for large tenders which can be made more efficient with the support of generative AI.
Generative AI also enhances the ability to analyse large datasets and act on insights faster. The technology allows teams to personalise outreach based on buyer persona’s and very specific persona behaviours and interests, making it easier to engage the right prospects at the right time. It’s an exciting evolution that offers the potential to increase productivity and effectiveness across the board. By adopting the right AI tools, GTM can become more data-driven, which if done the right way will ultimately benefit the top and bottom line of the organisation.
In B2G specifically, where buying groups are more complex than in B2B, marketing plays a crucial role in ICP definition and persona research. This includes identifying who the decision-makers are and understanding their motives, enabling the sales teams to craft more effective engagement strategies. In a way, marketing’s role is evolving and expanding from building the brand and generating leads to providing actionable insights that help sales teams engage earlier and more strategically, as well as driving budget efficiency through automation and incorporation of generative A.I. in the commercial workflows.
How does the complexity of buying groups in B2G markets impact the role of marketing?
In B2G, which shares similarities with B2B but is more complex, you often deal with multiple stakeholders spread across different governmental and nonprofit entities. Understanding the broad spectrum of personas involved is crucial because their motivations and timings differ significantly. Marketing’s contribution in defining these personas and determining when and how they are likely to engage in the buying process is indispensable.
One of the biggest challenges B2G sales people face is identifying the key decision-makers or influencers within these ‘’multi-entity’’ buying groups. This is where marketing can provide intelligence on the personas before they formally enter the procurement process. With more complex buying groups, it’s not just about the individual—it’s about understanding the entire network of influencers involved in the decision-making process.
Lead generation in particular depends heavily on the commercial team’s ability to map out these personas accurately. The mapping output informs targeted strategies to engage the right people at the right time, which is critical for influencing the buying decision. The insights that are provided by marketing and sales combined are an invaluable and foundational part of the ability to influence the procurement process effectively.
How do you view Marketing Qualified Leads (MQLs), and what improvements could be made to ensure they are sales-ready?
The value of leads depends on how thoughtful and detailed you define the qualification criteria. It’s usually not about tracking one single action, like a website visit, but combining multiple signals over time to assess a pattern of intent. A single action might most certainly evidence some interest, but the more viable MQLs are couched in a pattern of behaviours, like repeated engagement from multiple stakeholders within an organisation. It is also important to distinguish behaviours that increase a leadscore, for example content downloads, and behaviours that decrease a leadscore, for example an unsubscribe from a newsletter. The challenge is to find the right threshold score that triggers subsequent investment in engagement.
In short, an MQL’s intrinsic value can be expected to be higher when it shows sustained interest across multiple touchpoints expressed as a leadscore—whether it’s multiple people from the same account interacting with our content or different signals indicating buying intent. These more developed leads are the ones are the ones a sales team will want to prioritise
Ideally, a good amount of effort will be put into refining lead-scoring mechanisms to reflect a more nuanced and even deeper understanding of buyer intent. By integrating various data sources and tracking behaviours across all engagement platforms, more sales-ready leads will flow into the sales funnel. This approach can ensure that sales teams are investing their time and resources in high-potential opportunities rather than chasing less valuable leads.
How do you personalise outreach at scale, and what insights from marketing could enhance this process?
Personalisation at scale is one of the biggest challenges commercial teams face, and it relies heavily on both research and smart use and diligent configuration of the available technology. In most companies, the marketing functions usually provide the contours of the buying personas—who they are, where they are in the buying cycle, and what their specific needs are. The sales people who interact with the market in-person and on a daily basis are usually well positioned to provide the finesse and the ever so important nuance.
With generative AI, you can automate this account research, and personalise messages efficiently by generating content tailored to the specific attributes of each persona. It is crucial, however that the team really thinks through the array of personas and use cases and makes very careful and deliberate decisions as to which combination of personas and uses cases to pursue at scale: you don’t want to ‘out automate’ the capacity of the team that is ultimately tasked with engaging with the leads on a personal basis.
That is why I would always recommend introducing AI step by step, ensuring the AI is supervised by sales people, and that automated escalation features are used. For example, have AI create initial drafts of outreach messages based on past successful interactions. These drafts are then reviewed by sales teams to ensure they are relevant before being sent out.
Automating this process allows teams to be more responsive and targeted in their communications. The result is a more efficient way to engage prospects without losing the personal touch that resonates with customers and simultaneously trains the AI. Again, it is teamwork that does the trick!
About 6sense
6sense is on a mission to revolutionise the way B2B organisations create revenue by predicting customers most likely to buy and recommending the best course of action to engage anonymous buying teams. 6sense Revenue AI is the only sales and marketing platform to unlock the ability to create, manage and convert high-quality pipeline to revenue. Customers report 2X increases in average contract value, 4X increases in win rate and 20-40% reduction in time to close deals. Know everything, do anything, with 6sense.