Most B2B content strategies fail because they’re built on hope, not data. Recent industry research reveals that nearly 60% of B2B marketers consider their content strategy only “moderately effective” at best. When surveyed about the primary challenges, almost half pointed to a lack of clear goals and measurable objectives.
Your SEO strategy is probably failing. Not because you’re not working hard enough, but because you’re working on the wrong things.
Most companies spend months creating content, optimizing pages, and building links without knowing if any of it actually works. They implement random tactics based on “best practices” from 2018 and hope Google rewards them eventually. This is madness.
Account-based marketing is nearly universal now. But ubiquity hasn’t translated into impact.
90% of B2B organisations have an ABM strategy in place, yet only 39% can prove it’s working. The majority of ABM leaders aren’t fully leveraging account intelligence, the capability most closely tied to strong ROI, leaving them stuck in execution limbo.
That gap explains the contradiction at the heart of modern ABM.
Because when ABM works, it really works.
There’s a difference between creating content and creating value. Most B2B marketing teams are doing the former.
They publish, promote, report on pageviews, and do it all again next quarter. The output looks healthy, but the balance sheets say otherwise.
Your landing page is where curiosity turns into intent—or gets buried in a tab you’ll never see again. Buyers lose interest in seconds. And once that happens, it’s pretty hard to get them back.
You’ve seen the numbers. A prospect clicks your $50 LinkedIn ad, lands on your page, but nothing happens, leaving you with a smaller budget and zero insight into why.
LinkedIn is crowded, and it’s only getting worse.
Over 3 million posts go live daily, many of them AI-polished filler, recycled carousels, or marketing posts trying really hard to go viral.
When growth becomes stagnant or lead quality dips, it’s tempting to turn to paid ads as a quick fix. And for B2B marketers, LinkedIn often tops that list.
Experimentation is changing. Fast.
What was once a human-led process—running A/B tests, tweaking User Interface (UI) elements, and optimizing conversion paths—will increasingly be handed over to AI.
With AI automating tests and variations, humans now have the opportunity to focus on big bets—experiments that don’t just tweak conversions but fundamentally impact business strategy and growth. This shift marks a new era in AI Conversion Rate Optimization (CRO), where automation enables teams to think strategically rather than tactically.
However, it does raise some critical questions: What happens to experimentation teams when AI runs more tests? How does AI-driven testing change the economics of experimentation?
Marketing isn’t magic—it’s a disciplined science of experimentation. It’s easy to think of it as a creative pursuit, full of gut feelings and bold ideas. But at its core, marketing is a series of educated hypotheses put to the test. It’s a process of systematically uncovering what works to move the needle. Or, at least, when it’s done well, it is.
Ever poured thousands into ads targeting the “perfect audience” only to watch your money disappear?
You’re not alone.
Most marketers skip the crucial first step that separates winners from losers: finding your actual crowd before scaling.
I’ve seen companies blow six figures on campaigns targeting audiences they thought would convert. Spoiler alert: most didn’t.
The problem isn’t your product. It’s not even your messaging (yet). It’s that you’re talking to the wrong damn people.
Most B2B marketers aren’t bad at execution. They’re bad at choosing who to execute for.
The default move is to cast wide. Target VP-level and above, hit every industry that could theoretically use your product, and write messaging that offends no one, and therefore compels no one.