Why CRM Systems Drift Into Disorder

Understanding CRM Data Entropy in Complex Sales & Marketing Systems

“These systems were working fine a few months ago. Why are they going wrong?”

This question is common in any organisation running large, interconnected data systems. At first glance, it seems reasonable: if a platform functioned well before, why not now?

But CRM and marketing systems are not like cars—you can’t simply “service, refuel, and go.” Their behaviour is closer to that of ecosystems than that of machines.

Why Systems Decay

A key distinction with CRM platforms is that they are not purely technical. They are socio-technical systems: a fusion of software, integrations, workflows, incentives, and—most unpredictably—human behaviour.

The Gremlins Metaphor

Engineers in WWII jokingly blamed mysterious aircraft malfunctions on “gremlins.”
It was a way to acknowledge that complex systems fail for reasons that aren’t immediately obvious and often emerge from subtle interactions.

CRM systems behave similarly. It’s rarely “one big issue.” It’s the quiet accumulation of tiny mismatches, workarounds, and human shortcuts.

Was It Ever Truly “Working Fine”?

A system that appears stable may in fact be held together by ad-hoc patches, legacy logic, or assumptions that only worked under lighter data loads.

Like a bridge that seems sturdy—but once traffic increases, stress fractures emerge.

We have this exact same issue around the corner from my house, at Hammersmith Bridge, London - closed to all traffic except pedestrians and cyclists for the last seven years for these very reasons.

Initially, the bridge was strong. But as traffic increased, small structural weaknesses began to show — bolts loosened, joints flexed, stress fractures appeared. 

This bridge in the UK has not functioned for seven years now. My American wife, Catherine, says that in the US, it would have been fixed long ago. I welcome your thoughts in the comments below! 

The Role of Entropy

The second law of thermodynamics states that systems tend toward disorder unless energy is continually applied to maintain structure.

CRM ecosystems follow the same principle. Even if perfectly configured on day one (they never are), entropy creeps in through:

• Human behaviour
• System complexity
• Time

These forces push the system toward disorder unless actively countered.

The Beehive Model: When Systems Work

A healthy beehive functions because:

• Roles are clear
• Communication is consistent
• Inputs are reliable
• Activity flows are coordinated

In CRM terms:

• Leads flow correctly
• Fields are completed consistently
• Deals follow standard paths
• Dashboards reflect reality

Information moves cleanly through the “colony.”

When the Hive Breaks Down

Entropy emerges through small, seemingly harmless actions:

• Required fields skipped
• Inconsistent tracking parameters
• Manual deal creation
• Logic edited without documentation
• Data duplicated
• Attribution overwritten

Individually trivial.
Collectively destabilising.

This mirrors research across socio-technical systems: micro-errors compound in non-linear ways, producing instability that no single actor intended.

Complexity Magnifies Entropy

Modern revenue stacks include:

• CRM platforms
• Marketing automation
• Intent data systems
• BI tools
• Sales engagement platforms

Every integration introduces risk:

• ID mismatches
• Sync failures
• Schema drift
• Conflicting definitions

The more integrated the ecosystem, the faster entropy accelerates.

Time as a Force of Disorder

Even without major changes:

• Definitions evolve
• Teams rotate
• New fields accumulate
• Legacy data lingers
• Integrations layer on top of integrations

The result is gradual “data model drift”—the system you have is no longer the one originally designed.

Below: Dashboard of a Lockheed Martin F-35 Lightning II fighter jet 

Dashboards Are Instruments, Not Reality

A dashboard is to a business what cockpit instruments are to a pilot: essential, but only a representation of reality—not reality itself.

The dashboard provides important signals such as altitude, speed, heading, but it is not the sky, the weather, or the terrain itself. 

Instruments must be monitored, calibrated, questioned, and cross-checked. No pilot assumes the sky looks exactly like the dial.

Dashboards can provide powerful insights, but they should never be treated as the entire picture of what is happening in the business. 

And just as in aviation, the most effective organisations combine instrument readings with context, culture, and human insight to understand what is really happening.

The same principle applies in organisations. Leaders evaluating CRM outputs should adopt a similar mindset.

The Core Insight

CRM systems are not static assets.
They are living organisms that require constant:

• Maintenance
• Alignment
• Definition clarity
• Human behavioural guidance
• Technical calibration

Without active energy input, the system naturally drifts toward disorder—data entropy is not a failure of people or platforms, but an expected property of complex socio-technical systems.

The Reality for Leaders

Managing these systems requires constant vigilance, thought, testing, imagination, planning, and long-term strategy, just as the rest of the business does.

Below: Solving Data Disorder, Managing Organisational Culture

Because left unattended, complex systems drift toward disorder. 

How you manage this complex system will depend a lot on your 'problem-solving culture'. If you look at the matrix above, and according to Jim Collins, author of 'Good to Great', only about 5% of organisations sit in the ideal top right-hand quadrant. 

But essentially, CRM/Marketing Automation/Analytics systems are no exception to the second law of thermodynamics - they drift into disorder, naturally. 

Like any complex system built on human inputs, software integrations, and evolving processes, they naturally accumulate entropy over time.

Which means the question is never whether disorder will appear. That is a given.

The real question is who is paying attention when it does. A Strong culture with psychological safety, populated by teams with diverse cognitive styles, will solve these issues faster and more effectively than others. 

The Real Edge of Private Equity: Active Ownership

I’m a big fan of Scandinavian thrillers, especially the original The Girl with the Dragon Tattoo. So when I walked into the auditorium at the London School of Economics, I had the strange feeling I was looking down at three lead actors from a Nordic noir drama.

The speakers were Ulf Axelson, Professor of Finance and Private Equity at LSE; Per Strömberg, Professor of Finance at Stockholm School of Economics and LSE; and Kurt Björklund, Founder and Executive Chairman of Permira, with roughly $50bn under management.

What followed was one of the clearest, data-driven explanations I’ve heard of why private equity (PE) ownership so often outperforms public equity, and where its limits lie.

Why Private Equity Outperforms: Start with the Data

The first half of the lecture was led by Per Strömberg and focused squarely on the evidence. Rather than starting with anecdotes or ideology, he began with productivity data across countries and firms.

In Germany, for example, fewer than 1% of firms accounted for roughly 65% of positive productivity growth over the period studied. Most firms contribute little. Some actively destroy value.

This matters because private equity does not rely on averages. Its entire model is built around identifying, creating, and scaling outliers.

       

The Mechanism: How PE Actually Creates Value

Strömberg argued that the performance gap between PE-owned and publicly listed companies is not primarily due to regulatory arbitrage or tax advantages, though those exist at the margin.

The core driver is active ownership.

Drawing on both academic literature and operating evidence, PE value creation can be grouped into three broad mechanisms:

1. Governance engineering

PE owners are not distant shareholders. They:

• Sit on boards
• Hire and fire management
• Set incentives tightly linked to value creation
• Intervene early when performance slips

This sharply reduces classic agency problems between owners and executives.

During my MBA at Northeastern, one of my finance professors specialised in corporate governance, and I conducted research on shareholder activism. One theme emerged repeatedly: public-company executives often optimise for personal incentives that diverge from shareholder value.

Below: PE-owned companies are rigorous in selecting customers that add value

PE ownership compresses that gap. In the same way that active shareholders hold senior leadership to account, Private Equity owners can step in to ensure the company is run as efficiently as possible. 

Per explained that the productivity and efficiency gains of Private Equity ownership (according to him, 2-3% higher than Public Equity, according to Kurt, head of a PE firm, it is closer to 6-7% higher), can be divided into three key categories:

Three types of engineering/tools

1. Governance engineering – being an active owner of the company

2 . Financial engineering – reduce cost of capital 

3. Become sector experts – can leverage networks to assist management

Well, that begs the question – why don’t other companies copy the behaviour of PE companies, to improve their performance?

According to Strömberg, this opens a “can of worms”.

First, PE performance may not be indefinitely sustainable. Funds have finite holding periods, typically six to seven years. Active ownership delivers diminishing returns once the biggest inefficiencies are removed.

However, within that limited time frame, PE seems to be doing better than ever. Exit value experienced a rebound in 2025, increasing 41 per cent to $1.3 trillion, the second-highest year on record. 

Second, PE capital is more expensive. While leverage can be cheaper than equity, the cost of financial distress rises sharply as leverage increases.

PE is not a universal solvent. It is a precision tool, effective under specific conditions.

An Operator’s Perspective: Kurt Björklund of Permira

The second half of the session (unrecorded) shifted from data to practice. Kurt Björklund described himself not as a financier, but as a “financial entrepreneur” and "Sector disrupter".

His framing was revealing.

Public equity investors, he argued, suffer from information asymmetry. Even large shareholders rely on periodic disclosures and carefully curated narratives.

PE ownership, by contrast, is built on information abundance:

• Proprietary KPIs
• Weekly operational interaction
• Direct access to management and systems

Björklund was blunt: unlike asset managers such as BlackRock, he cannot afford to be wrong. Every investment must succeed. That forces extraordinary diligence and relentless focus post-acquisition.

He also warned about classic PE pitfalls:

• Buyer’s curse in auction processes
• Cyclicality of capital markets
• The temptation to “take your eye off the ball” during exit processes

“In my business,” he said, “only the paranoid survive.”

Disruption, People, and the Role of AI

One of the most charged parts of the discussion came during the Q&A, where students (from the LSE, Imperial, Oxford, and Berkeley, USA) repeatedly asked about AI and job security. There were also several questions from analysts at various Private Equity firms.

Björklund acknowledged the anxiety, but did little to soothe it.

He described investments in complex B2B businesses where agentic AI, and improved automation have reduced headcount by orders of magnitude, particularly in areas such as KYC and compliance.

In one example, automation reduced a team from 5,000 people to 500, while increasing profitability. Many in the organisation were conducting relatively complex tasks, which could nevertheless be performed more effectively with AI and Automation.

Above - Top Target Universities (non-US) for Goldman Sachs. Source: Krugman Insights

His view was unsentimental: there will always be jobs for the very best, and the traditional path: An elite education, a top investment bank such as Goldman Sachs, and then a good Private Equity firm, remains viable. But the middle is being hollowed out.

Interestingly, he noted that older employees often adopt AI more effectively than younger ones, attributing this to psychological barriers to AI in younger workers. 

Perhaps it's also because you need deep experience in solving the problems, to ask AI the right questions? It's very easy to generate 'AI workslop' that drives no insight, and diminishes your credibility in the organisation. And that is no doubt from whence that fear emanates.

The recording was switched off halfway through the lecture, at which point the atmosphere in the room changed perceptibly. Kurt (The Chairman of Permira) smiled and said he would assume there were no journalists present, which meant he could now speak a little more freely than usual.

The professors, clearly enjoying the moment, joked that in Sweden, Kurt is known as “Superkurt”: the complete package: handsome, physically fit, wildly successful, and extremely wealthy.

Kurt laughed, didn’t deny it, and carried on.

Which confirmed something I’ve learned from working with private equity firms in the past: there is remarkably little self-deprecation in the room, even when the person in question is a typically reserved Swede.

Joking aside, this was one of the best lectures I've seen, unique in that it presented top-level insights from both the academic and 'real-world' perspectives. 

Further Reading

What You all want to Know About Marketing in 2025: Growth Hacks, Customer Psychology, and ROI.

   

Did you know that the average time a LinkedIn ad takes, from first impression to B2B revenue, is 320 days? And 235 from ad engagement. Are you giving your campaigns enough time to work?

- Most companies in my sphere do not have enough, surprise, surprise! - patience. However, I do achieve success with retargeting ads, which, as you might expect, work faster.

But even with retargeting, you have some serious drags on your success – firstly, the economy, which is slowing, flat, or even in reverse, depending on where you are. Secondly, your brand – the biggest brands in the world only have to put out mediocre ads, and they will still get good results. 

But a small startup with an unknown brand, needs to hit it out of the park every time to connect with the customer. Plus, it’s fighting against the adage ‘no one ever got fired for buying IBM’

I guess you’d change that to some variation of Microsoft today. But the point is that it's very hard to convert a lead for a small company with little or no brand awareness.

However, that’s not to mean it’s not impossible! Companies like Zscaler, where I worked, did this – but it was not due to marketing alone. They had an outstanding product, which can make up for a multitude of sins. We also have a dynamite sales and marketing team.

On the contrary, if you are dealing with a poor or not well-established product market fit, it's easy for a company to become sucked into a viciously accelerating churn cycle 'whirlpool': Company loses customers at an alarming rate, so it needs to ramp up sales and marketing efforts (cue unrealistic promises), which speeds up churn, and so on.

How do you avoid such a situation? Make sure that you have virtuous feedback loops from sales and marketing to product and back. And that you have a strong culture of psychological safety. If you have a culture of ‘shoot the messenger’, then no one in senior management will be aware of these problems until it's too late.

How did I get so interested in this topic, I hear you ask? Well, actually, I’ve been very busy on various platforms trying to crack the code of how SEO is changing with AI, in the b2b space.

I feel like I’m getting there! Since my organic blog and web traffic have increased more than tenfold in the last year!

If you look at this chart, you can see what’s driving AI search – I would say for B2B it skews a little heavier towards LinkedIn and Quora. So I’ve been super active on these channels, and I’m getting over 50 b2b questions a day on just Quora, for instance. 

I recently did an entire audit of all my social media engagements across all my key channels (Quora/LinkedIn/Reddit) to see what the trends are

When I fed it all into AI, these were the top topics:

AI-driven GTM & the new search stack
How to win with AI Overviews/AI Max + LinkedIn/Quora/Reddit; practical playbooks, not theory.

Demand gen that actually drives pipeline (esp. in tight markets)
What to cut/defend/double-down on, sequencing experiments, and real metrics (demo-rate, win-rate, payback) — not vanity MQLs.

Sales psychology & decision-enablement content
Buying signals, persuasion without pressure, and case studies that sell (HBS-style narratives over “advertorials”). Quora hits on buying signals, mass outreach, and monetising lists point here.

MarTech/ABM stack & accountability
HubSpot/SFDC + Demandbase/6sense choices, clean ops, SLAs with sales, and agency performance models (pay-for-performance vs. retainers).

Trust engines: community, authenticity & micro-influencers
Turning brand communities and creator voices into a qualified pipeline; founder POVs and no-BS thought leadership resonate with the LinkedIn crowd.

Over the next few months, I will dig into these topics in much more detail with a focus on each one every month. 

It’s great to see that what you are asking me very much aligns with what I am good at, and what I have a strong understanding of – so the algorithms are working!

What are the patterns? – Once again, thanks to my AI agent for compiling this, based on all the research I fed into it from all my channels.

• Uncertainty + urgency → People want growth now, but budgets are tight.
• Confusion about tools & tactics → Which platform, which channel, which metric to trust?
• Fear of wasting time → Nobody wants to spend months on SEO, or money on ads, only to fail.
• Craving clarity & confidence → They want straight answers, practical hacks, and a sense of control in a messy marketing world.

In short, my audience is looking for shortcuts to certainty in an increasingly erratic and noisy world. 

Truth is, there are no true shortcuts—only sharper strategies, faster feedback loops, and the courage to test and adapt quicker than the next marketer. 

And the winners won’t necessarily be the ones with the biggest budgets, but the ones who move sharpest, fastest, and smartest.

AI Max for B2B: Unlock Maximum Growth with AI Search

AI is radically changing the search landscape. For B2B marketers, this shift presents both a significant challenge and a massive opportunity. Historically, B2B search has been a challenging arena, characterised by low keyword volume, high CPCs in competitive verticals such as SaaS, and the constant struggle to generate a steady stream of high-quality, converting leads through non-branded SEO (branded b2b search has typically fared much better, though).

Now, AI has completely altered the playbook. The entire SEO strategies of yesteryear are thrown out the window. It’s platforms like Reddit, and Quora which are driving AI search to a large degree, and even Google search has altered radically.

Where Search is being conducted in 2025 and beyond


The introduction of Google’s AI Max for Search campaigns, for example, a one-click, AI-powered suite of targeting and creative innovations, along with the Search Generative Experience (SGE), means the old keyword-first strategy is quickly becoming obsolete. B2B marketers must adapt to survive and thrive in this transformed environment.

This post will provide a comprehensive framework for founders, CMOs, and demand generation leaders to leverage AI-powered search for maximum growth. We will explore how to integrate tools like AI Max and Performance Max, into your B2B AI marketing strategy to drive demand, enhance personalization, and ultimately, increase conversions.

The New Reality of AI in B2B Search

The way customers find information is undergoing a fundamental transformation. AI search assistants, such as Google AI Overviews, are increasingly delivering summarized insights directly on the results page, often bypassing traditional organic listings. This new reality requires a new approach to both paid and organic search.

Google’s AI Max for Search campaigns, currently in beta, is at the forefront of this change. It enhances standard search campaigns with broad-match expansion, AI-generated headlines and descriptions, and automatic final URL selection.

According to Google, advertisers who activate AI Max typically see a 14% increase in conversions or conversion value at a similar CPA or ROAS. For campaigns that have heavily relied on phrase and exact match keywords, the uplift is even more substantial, up to 27%.

These AI-driven enhancements allow B2B marketers to discover new, relevant queries they might have otherwise missed. Recent updates also provide greater transparency, surfacing metrics for AI-driven expansions, including traffic from AI-generated keyword matches and landing pages. This data gives marketers the insights needed to optimize their campaigns effectively.

The AI Max Framework for B2B Success

To succeed in this new era, B2B leaders need a fully integrated strategy that integrates AI across the entire marketing and sales funnel. This framework breaks down how to apply AI-powered tools, including AI Max, to achieve maximum growth.

Search & Market Visibility

The first step is ensuring your brand is visible where your future customers are searching. This means optimizing for how AI search engines work.

Optimize SEO for AI Search: Your focus must shift from pure keyword targeting to establishing topic authority. Create comprehensive pillar pages and structured content, like FAQ schema, that AI summarizers can easily parse and surface in AI Overviews. Your content needs a clear, brand-aware narrative that positions your company as a thought leader.

Leverage AI Max for Search Campaigns: This is where you can truly amplify your reach. To get the most out of it, you should:

Enable Search Term Matching: This feature uses broad match and keywordless technology to discover new, relevant search queries, expanding your reach to high-intent audiences you weren't accessing before.

Use Text Customization: Allow Google AI to automatically generate compelling ad copy, including headlines and descriptions, based on your landing pages, existing ads, and keywords.

Deploy Final URL Expansion: Let the system send users to the most relevant destination page on your website based on their search context, improving user experience and conversion potential.

Maintain Precision with Controls: AI Max isn't a ‘set it and forget it’ tool. Use the built-in brand and location controls to maintain precision and actively monitor reporting to refine your B2B AI marketing strategy.

AI Demand Generation

Once you have established visibility, the next step is to capture and convert intent into qualified leads. AI accelerates this process.

Use Predictive Platforms: Tools like 6sense, Demandbase, and Apollo leverage AI to identify and target high-intent accounts that are actively researching solutions like yours. This allows you to engage prospects early in their buying journey.

Activate AI-Powered Bidding: Whether on LinkedIn Ads or through AI Max campaigns, AI-driven bidding strategies optimize for cost-per-lead (CPL) efficiency and help you reach your most valuable audiences at scale.

Deploy Conversational AI: Implement chatbots and virtual assistants from providers like Drift or Intercom on your website. These tools can instantly qualify visitors, answer questions, and book meetings, seamlessly aligning with your CRM to ensure no lead falls through the cracks.

Where your prospects and customers are searching with AI

Content & ABM Personalization

In B2B, personalization is paramount. AI enables you to scale your account-based marketing (ABM) efforts and deliver tailored content to every key stakeholder.

Accelerate Content Creation: Use AI writing assistants like Jasper or Writer to create first drafts of blog posts, whitepapers, and ad copy. This frees up your marketing team to focus on strategic editing, ensuring the final content reflects your brand’s unique tone, nuance, and credibility.

Customize Content for ABM: AI allows you to tailor messaging for different personas within the same target account. For example, you can create distinct content variations that speak to the specific pain points of a CIO versus a CMO, increasing relevance and engagement.

Sales & Marketing Alignment

A successful B2B AI marketing strategy requires tight alignment between marketing and sales. AI can bridge the gap and create a seamless feedback loop. But this part also relies heavily on human interaction. You, as a marketer, must talk to your sales team, to your CRO, to the SDRs and SDR manager – to ensure that you explain the new AI-centric approach, and that the entire sales and marketing team are in concert.

Automate Lead Scoring: Ensure that only the most qualified, high-fit marketing qualified leads (MQLs) are passed to your sales team. AI-powered lead scoring analyzes behavioral and firmographic data to prioritize leads accurately.

Leverage Conversation Intelligence: Tools like Gong, Clay, and Chorus analyze sales calls to provide real-time insights. This data is a goldmine for marketers, offering direct feedback on messaging, customer objections, and competitor mentions that can be used to refine your strategy.

Analytics & Growth Operations

Finally, you need to measure what matters. AI enhances your ability to track performance and tie marketing activities directly to revenue.

Apply GA4 Anomaly Detection: Use the built-in AI features in Google Analytics 4 to uncover real-time patterns and performance shifts. This helps you identify opportunities and address issues before they impact your pipeline.

Build AI-Powered Dashboards: Create dashboards that connect ad spend and engagement metrics directly to pipeline generation and revenue outcomes. This provides a clear view of your marketing ROI and helps justify future investments.

Harnessing AI While Maintaining Human Intelligence (empathy + creativity)

As mentioned, adopting AI doesn't mean removing the human element. The most successful organizations will be those that blend AI-driven execution with human-led strategy.

Strategy Comes from Humans, AI Scales Execution: Your team’s expertise is irreplaceable. Use AI to automate tasks and scale your efforts, but let human insight guide the overall direction.

Clean Data is Foundational: AI is only as good as the data it’s fed. Poor CRM hygiene, inconsistent tracking, and inaccurate data will undermine the effectiveness of any AI tool.

Test Before You Expand: AI Max offers built-in experiments that allow you to run a 50/50 split test to validate its impact without duplicating your campaigns. Always test and validate before rolling out changes broadly.

'Social' is the new 'Search'

Blend Organic and Paid Strategies: AI-driven ads and topic-based B2B SEO are not mutually exclusive; they reinforce each other. A strong organic presence builds trust and authority, which can improve the performance of your paid campaigns.

Ideas that take off and go viral organically, are the perfect ones to run, and boost with advertising. As Gary Vaynerchuk explains, 

It’s better to put out one hundred good but not perfect posts, and let the audience decide what they like, than have five ‘Hollywood production level’ ads that could all easily misfire, with near zero ROI 

- as well as providing you with little or no useful optimization data. Once you see which posts have performed well organically, then 'boost' them with paid, or even adapt them in ads, which you can then run.

AI can help you create thousands of new creatives in minutes. This facility was not available to me as a marketer only a few years ago. This is a huge positive change.

Focus on Meaningful KPIs

Track the KPIs that truly matter to your business: pipeline growth, conversion rates, customer acquisition cost, ROAS, CLTV (to avoid churn further down the road) and marketing ROI.



How is AI transforming B2B search?

AI is transforming B2B search by shifting the focus from keywords to user intent. Generative results like AI Overviews provide direct answers, while campaign tools like AI Max for Search use automation to find and convert high-intent users. The modern search journey now centres on deep content authority, intent understanding, and AI-powered optimization.

What makes AI Max for Search campaigns unique for B2B?

AI Max for Search bundles broad-match expansion, dynamic asset generation, and intelligent landing page selection into a single, one-click solution. For B2B marketers, this means discovering new pockets of demand and delivering highly relevant ads, all while retaining control over brand and targeting parameters. Based on Google's data, this can lead to significant boosts in conversions at a similar cost.

Should B2B companies still invest in B2B SEO?

Absolutely. In fact, SEO is more important than ever, but the strategy must evolve. The focus should be on building thought leadership and creating structured, authoritative content that is easily readable by AI. This ensures your brand is surfaced as a credible source in AI-generated answers and maintains a strong foundation of organic traffic.

Your Path to a New Era of B2B Growth

The traditional B2B search playbook is being rewritten in real time. AI Max for Search, AI-powered B2B SEO, and full-funnel automation are no longer optional add-ons; they are essential components of a modern B2B AI marketing strategy.

Founders, CMOs, and demand generation leaders who embrace this change will gain a significant competitive advantage. By anchoring your strategy in human creativity and insight while leveraging AI to scale execution, you can navigate the post-keyword era and unlock unprecedented growth. 

The journey starts with understanding these new tools and integrating them in an empathetic, human way into a cohesive, revenue-focused plan.

The Hardest Challenges Facing B2B SaaS Demand Generation Leaders (and Why They’re Like Building Rockets)

If you’re stepping into a Head of Demand Generation or Revenue Operations leadership role in a B2B SaaS company, chances are you’ve inherited a set of challenges that are far from straightforward. Unlike consumer marketing, where demand can often be manufactured with brand spend and viral reach, true B2B demand generation success is typically a long game that requires precision, alignment, and resilience.

But what happens when the engine that powers your go-to-market machine is either missing, broken, or poorly configured?

In this article, I’ll explore five of the biggest challenges B2B SaaS demand generation leaders face, why they’re so complex, and what lessons you can learn from Elon Musk’s SpaceX rocket program to navigate them successfully.

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Five Core Challenges of B2B SaaS Demand Generation Leadership

1. Rebuilding After Leadership Loss

You’ve lost both your Head of Revenue Operations and Head of Demand Generation. Now you’re starting from scratch, rebuilding the engine room of your growth function.

Unlike replacing parts in a car, you can’t just slot in a new “engine” and expect things to work. Every leader brings their own unique experience, style, and alignment challenges. A misstep here can set your growth trajectory back by months, quarters, or even years.

2. No Demand Generation Engine—Just Outbound Sales

Many SaaS firms rely too heavily on outbound prospecting. SDRs and AEs pound the phones, book demos, and chase the pipeline. But it’s an expensive model. “No-show” rates creep past 25%, CAC balloons, and sales morale plummets. Aggressive and inexperienced 'gun-ho' sales reps can also fatally damage your brand.

Without a demand generation engine, a scalable, predictable inbound system that attracts and nurtures ICP buyers, you’re running uphill against gravity. With outbound sales, you continually start from scratch. With a demand generation engine, you are building, improving and optimising over time, adding momentum to your inbound 'flywheel'

3. Agency Dependency and Declining Returns

You hire an agency. They perform well in year one, but as time passes, performance stagnates while their integration into your processes deepens. Suddenly, you’re stuck with status quo bias, the fear that replacing them will be more painful than persisting with mediocrity.

The truth: agencies rarely innovate on your behalf after the honeymoon phase. A demand generation leader has to know when to pivot and when to insource.

However, to do so requires courage and experience - a demand generation expert who has been tried and tested.

4. Broken Metrics and ICP Confusion

Lead scoring models that don’t predict conversion. A pipeline filled with the wrong personas. Confusion over customer lifetime value (CLV) and churn. A lack of clarity on your ideal customer profile (ICP).

At this stage, it’s not clear whether any single demand generation manager can “fix” the problem without broader executive buy-in and a serious reset. But again, if that person can be found, it must be a demand generation leader with sufficient 'gravitas' to persuade the C suite that he knows what he's doing - and one that can follow through and deliver those promised results. 

5. Organisational Silos and Politics

Sales, marketing, product, and customer success aren’t talking. Worse, they’re competing. Information is withheld, psychological safety is low, and the people who care most about the business (and speak uncomfortable truths) get punished.

You’re left with the consummate politicians while the passionate operators—the very people you need—walk out the door. This is when a company can fall into a death spiral. It takes a skilled expert, to pull out of such a doom loop, and set the demand function on a healthy growth course. 

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Replacing Demand Generation Leaders isn't like swapping out a car engine; it's like rebuilding a rocket

Why Losing Your Growth Engine Is Like Launching a Rocket

When I first thought about losing key revenue roles, I compared it to pulling an engine out of a car. But the more I thought about the analogy, the more I realised that it doesn’t do justice to the reality.

In cars, engines are standardised. You can swap them, and they’ll usually work. In B2B SaaS demand generation, leadership roles are not plug-and-play. Hiring a new Head of Demand Gen or Revenue Ops is closer to building a rocket than fixing a car.

And rockets fail—a lot—before they succeed. Whereas a brand-new car engine is pretty much guaranteed to work if inserted into a new vehicle. 

SpaceX and the “Known Unknowns”

US Secretary of Defence Donald Rumsfeld once spoke about “known knowns, known unknowns, and unknown unknowns.” This framework applies perfectly to building a demand generation engine:

• Known challenges: Your new leaders must learn the organisation, tech stack, and products.

• Known unknowns: How will they perform as individuals? How will they work together? How will sales, SDRs, and product marketing respond?

• Unknown unknowns: What happens if the system breaks down completely? What happens if your new head of demand generation and new head of revenue operations don't get along? What happens if neither works well with sales? The list goes on....

SpaceX’s Falcon 1 and Early Failures

Elon Musk’s SpaceX faced multiple failed launches of the Falcon 1 rocket between 2006–2008. Each failure was costly, public, and demoralising. But on the fourth attempt, Falcon 1 succeeded—and from there, SpaceX iterated its way to reliability.

Falcon 9: Iteration and Reusability

With Falcon 9, SpaceX didn’t just build a bigger rocket—it built one that could be reused. That single innovation changed the economics of space travel. For demand gen leaders, the equivalent is creating repeatable, reusable, scalable campaigns—not one-off wins (like outbound lead gen campaigns).

The Starship Analogy

Today, SpaceX is pushing the boundaries with Starship, a vehicle designed for Mars. It has already exploded multiple times. But each failure accelerates learning.

Similarly, in demand generation, failure is part of the job. Campaigns will flop, SDR alignment will slip, MQL-to-SQL conversions will crater. But with the right mindset, each failure becomes data that makes the system stronger.

However, confidence is built over time, as trust inside a team, and with cross-functional teams, grows. What happens if your new demand generation/revenue operations team has a big setback early on? Will the executive team and wider company support them through that hard time, so they can learn from their mistakes?

Or will the C suite and team abandon them, and lose faith in the strategy, execution, and team? - This is far more likely to happen with completely new Demand Generation and Revenue Operations leaders. 

You need highly skilled, experienced, courageous and tough operators to be successful in such scenarios. 

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The Skills of a World-Class B2B Demand Generation Leader

So, what does it take to thrive in this high-stakes environment? From working across SaaS firms and demand gen programs, I’d distil the role into five core skill areas:

1. Revenue Architecture

The ability to design go-to-market engines that align marketing, sales, and customer success around shared revenue metrics.

2. Data and Analytics Mastery

From lead scoring models to intent data (6sense, Demandbase), a modern demand gen leader must understand the signals that actually predict pipeline and revenue—not vanity metrics.

3. Full-Stack Channel Expertise

Paid media (LinkedIn Ads, Google Performance Max), SEO, content marketing, email nurture, ABM, webinars, and partnerships—demand gen leaders need range, not silos.

4. Cross-Functional Leadership

The ability to break silos, foster psychological safety, and align diverse teams behind a single growth vision.

5. Resilience and Iteration

Like SpaceX, the best demand generation leaders fail fast, learn faster, and iterate continuously. 

That takes more than tactics — it requires C-suite backing, trust in your leaders, and the grit to ride out the inevitable highs and lows of your strategy.

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From Engines to Rockets: The Opportunity Ahead

Yes, the challenges in B2B SaaS demand generation leadership are immense: broken engines, siloed teams, political infighting, ICP confusion, agency inertia.

But the opportunity is equally vast. Just as SpaceX transformed the economics of space travel through persistence and iteration, the right leaders can transform SaaS demand generation into a predictable, scalable growth engine.

How founders can take their B2B Marketing strategy from Good to Great

Build a scalable B2B demand generation engine. Learn how to align sales, track vital metrics, and drive revenue with smart marketing strategies.

Most B2B marketing strategies stay trapped in the realm of "good." They hit vanity metrics, deliver leads, and provide a sense of activity, but they often fail to drive tangible revenue growth or establish true scalability.

But what if your marketing efforts could transcend the “good” and achieve true greatness? Inspired by Jim Collins’ business classic Good to Great, this post will explore how to elevate your B2B demand generation strategy to unlock revenue, align teams, and deliver real impact.

Over the years, I've read countless books on management. 'Good to Great' captures what outstanding business practices look like by far the best; No other thought leader has ideas and values I can get behind as wholeheartedly as Jim Collins.

Here’s how to turn your B2B marketing engine into a high-performance, revenue-driving machine, by applying his incredible high-performance business philosophy.

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The Hedgehog Concept for B2B Marketing

Collins explains that great companies find the sweet spot between what they excel at, what drives their economic engine, and what they are deeply passionate about.

For B2B demand generation, this concept translates into identifying the strategic intersection where performance marketing becomes transformational, not just tactical.

Your Hedgehog for B2B Marketing

• Best At: Are you leveraging your competitive edge? Whether that’s account-based marketing (ABM), intent-based targeting, outstanding sales marketing alignment, or impactful brand-building events, concentrate your efforts on where your team’s strengths shine and deliver results.
• Economic Engine: Focus on metrics that matter. Don’t just track leads; measure downstream KPIs, such as marketing-qualified lead (MQL) to sales-qualified lead (SQL) conversions, pipeline attribution, and campaign ROI.
• Passion: Align your efforts with where you deliver the most value. For example, if your most significant wins come from ABM campaigns for senior job titles in enterprise companies in the Financial Sector, double down on refining that approach.

This clarity enables you to scale efficiently while remaining true to your core capabilities.

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Humble Yet Gritty Leadership in B2B

According to Collins, “Level 5” leaders combine personal humility with a relentless focus on results. This principle applies perfectly to B2B marketing leadership, where siloed teams and ego-driven decisions often block progress.

What does this look like in practice?

1. Unify Sales and Marketing Teams: Stop the blame game and dismantle silos. Get everyone aligned on shared revenue goals, clear ICPs (ideal customer profiles), and the same KPIs to track success.
2. Prioritise Collaboration Over Decentralisation: Marketing isn’t just about generating leads; it’s about revenue acceleration in partnership with sales. That’s when the entire funnel is built cohesively.

"You can accomplish anything in life, provided that you do not mind who gets the credit."

Jim Collins, Good to Great

3. Be Data-Driven, Not Ego-Driven: Use analytics tools like HubSpot or Salesforce to track performance objectively. Hold campaigns accountable—but also celebrate what’s actually working.

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Confront the Brutal Facts in Your Funnel

B2B demand generation often stagnates because teams avoid confronting inefficiencies. Are you willing to dig deep into your marketing and sales funnel to uncover what’s slowing you down?

Common Pain Points:

• Misaligned ICPs: A vague or unrealistic ICP can result in wasted spend and irrelevant leads.
• Poor Hand-off Processes: If MQL to SQL conversion rates are low, the problem likely lies in inconsistent or unclear handoff processes.
• Leaky Funnels: Leads are coming in but disappearing before they can be nurtured toward conversion. Is it a bad fit, poor nurture flows, or retargeting campaigns?

How to Respond:

• Conduct a funnel audit to assess breakdowns. Tools like HubSpot analytics, Demandbase, Terminus, 6sense, or Lead Forensics ABM platforms, SEMrush, or Google Data Studio are excellent for visualizing problem areas.
• Employ a rigorous yet constructive approach to revamping underperforming campaigns and strategies. Remember to refine rather than reinvent the wheel.

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Build the Right Cross-Functional Team

A B2B demand engine is only as strong as the people running it. Outstanding marketing execution requires diverse skills—from imaginative content creation to data analysis and technical optimization.

Embrace cognitive diversity - this is the diversity arguably most likely to power success according to the latest research.

Who You Need on the Bus:

• Data Analysts & Strategists: These are the people who ensure campaigns are built on insights instead of generalizations.
• Sales Champions: They act as the bridge, ensuring the pipeline results in realistic, winnable opportunities.
• Creative Experts: Content creators who can craft killer messaging that resonates across every channel. Designers who can interrogate the brief and capture in image form, not necessarily what you ask for, but absolutely what you want. AI will never replace the imagination, skills, and experience of a brilliant designer.

Getting the right team aligned will supercharge your system, turning disjointed outputs into a cohesive strategy.

The Flywheel Effect in B2B Marketing

Building momentum is critical—but great marketing efforts don’t happen overnight. Sustained growth comes from creating a “flywheel” effect where one success amplifies the next.

How to Create a Marketing Flywheel:

1. Align Technology, Channels, and People: Ensure your data flows seamlessly between tools like HubSpot, Demandbase, or 6sense. Consistent messaging and metrics should unify your campaigns.
2. Focus on Multi-Channel Impact: Combine paid media, ABM, SEO, email, and events into an integrated strategy. Each channel should reinforce the others.
3. Nurture, Nurture, Nurture: Automate lifecycle marketing that adapts to each touchpoint (e.g., post-click emails, blog engagement, social retargeting). Smaller, targeted email campaigns triggered by actions or behavior typically trump high-volume, untargeted, unpersonalized email 'blasts'.

Peak-performing B2B funnels don’t rely on individual lightning strikes. They’re built for compounding returns over time.

Don't seek out silver bullets - build solid incremental gains over time.

That's not to say you should ignore tremendous opportunities you spot - if you find a silver bullet, fire away!

But realistically, most of your success will come from the slow, sustainable processes you put in place—testing, optimising, feedback loops, and grinding forward with passion.

Just get your marketing fundamentals right and hire good (or even great!), highly competent professionals. Then, you will be well on your way to B2B Marketing success.

The superhero narrative is incredibly glamorous, and appealing. I get it.

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Measure What Matters

The key to long-term growth is tracking the B2B metrics that truly drive pipeline and revenue.

Critical Metrics to Monitor:

• Lead-to-Opportunity Conversion Rates: Are your leads progressing through the funnel efficiently?
• Cost Per SQL: Keep tabs on how much you spend to create sales-qualified leads.
• Cost Per Sale: In the long run, also keep a steady eye on your ROAS. Ideally, it should be over 4X - though, the exact number will depend on your overall strategy
• Account Engagement: Measure how your target accounts are interacting with ABM campaigns.
• Intent Scoring Accuracy: Make use of intent-based targeting tools to prioritize high-fit leads.
• Revenue Attribution Models: Identify which campaigns or touchpoints contribute most to net-new revenue.

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Technology as an Accelerator, Not a Crutch

Your MarTech stack isn’t what makes your campaigns great. This is the message that CMOs, and Demand generation leaders in mid-size SaaS cybersecurity, fintech, and martech companies told Damien & I loud and clear in our recent B2B Account-Based Marketing Roundtable.

The most expensive up-to-date buyer intent tools will not fix your conversion problems if your team is not working well together.

As Jim Collins noted in his book, high-performing 'good to great companies' didn't even rank technology among their top ten most essential contributions to success.

Technology will not fix a broken system.

Instead, tech should amplify smart strategies and simplify execution.

How to Control the Stack:

• For demand generation, focus only on tools that unify data and simplify decision-making, such as HubSpot, Salesforce, or 6sense.
• Prioritize platforms that integrate seamlessly to create a holistic view of performance.
• Avoid overcomplicating with unnecessary tools that fragment your system.

The right technology won’t just manage your marketing workflow; it will power intelligent, data-driven growth.

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Elevate Your B2B Marketing Today

Taking your B2B marketing strategy from good to great isn’t just an achievement; it’s the only path to sustained growth in today’s competitive market.

By focusing on core principles such as data-driven decision-making, sales and marketing alignment, and leveraging the right MarTech tools, you can build a scalable demand generation engine that drives measurable revenue growth.

If you’re ready to accelerate your growth and turn leads into customers faster than ever, start building or optimizing your demand generation strategy today.

“Great companies respond with thoughtfulness and creativity, driven by a compulsion to turn unrealized potential into results; mediocre companies react and lurch about, motivated by fear of being left behind.” (page 162)