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Santana Blanchette
AI, influence, brand, and customers: four skills defining marketing leadership in 2026
TL;DR AI makes up 17% of marketing activity today and is heading to 44% within three years. To stay ahead of it, leaders need to understand what AI is actually doing inside their platforms well enough to direct it, not just accept vendor recommendations. Cross-functional influence starts with investing in relationships with finance, product, and sales before you need something from them, and communicating marketing's value in their language, not yours. Brand and performance should share a single view of data and a single measurement framework, even an imperfect one, so budget decisions are made on a consistent basis across the whole portfolio. And customer intelligence needs to be an ongoing habit, not a project. Leaders who stay close to qualitative signals like customer conversations and sales call patterns make better strategic decisions than those who rely on performance dashboards alone.
10 minute readCross-channel storytelling is an organizational problem
TL;DR Cross-channel storytelling means telling one consistent brand story across every platform a customer touches, even though each platform needs its own version of that story. It's fundamentally an organizational problem before it's a media or creative one, because most companies work in silos. You can't control the order customers see your ads in, so consistency matters more than sequencing. Creative fatigue is real, but the fix is variety within a consistent concept, not one-size-fits-all repetition. And while there's no single metric that proves cross-channel storytelling worked, long-term revenue growth and marketing efficiency are the clearest signals. Creative is where all of this actually comes together.
4 minute readMarketing leaders need better CFO relationships and measurement discipline
TL;DR Marketing leaders are under more pressure than ever to justify spend. The ones winning are closing two gaps: the CMO-CFO relationship and measurement discipline. That means learning your CFO's unit economics, building a shared view of marketing's financial contribution, and starting every measurement problem with the business question, not the tool. On attribution, stop chasing the perfect model. Get both teams working from the same imperfect one.
8 minute readThe brand and performance divide is costing you more than you think
TL;DR Performance marketing captures demand. Brand marketing creates it. Most organizations treat them as separate functions with separate budgets, separate teams, and separate goals. That's a mistake. When they don't work together, you get a gap in the middle of the funnel, inconsistent consumer experiences, and budget politics that hurt the business. The fix is simpler than an org overhaul: share media plans early, connect your measurement, and be clear on what each channel is actually supposed to do.
4 minute readCan AI create a (trustworthy) full marketing strategy?
TL;DR AI isn't ready to independently create full marketing strategies yet. While generative AI excels at facilitation (summarization, brainstorming, content polishing, and visualization), it falls short on the nuanced, expertise-driven work that defines strategic planning. The tools lack access to crucial first-party data, can't replicate human taste and judgment, and often produce generic outputs when asked to do too much. Right now, AI works best as a collaborative thought partner, accelerating existing processes rather than replacing human expertise. The key? Use AI for tactical support while keeping humans firmly in the decision-making seat.
5 minute readMost lead scoring sucks (here's how we fixed it)
TL;DR Most B2B companies are doing lead scoring wrong, relying on arbitrary point systems and outdated models that don't reflect actual buyer behavior. Real lead scoring requires clean data infrastructure, empirical validation, and regular updates. More importantly, it should never be prioritized over fundamentals like product-market fit, messaging, and creative. Lead scoring is an optimization layer, not a solution to broken marketing.
4 minute readYour ad data can't tell you everything about your audience
TL;DR Ad platform data gives you demographic snapshots and performance metrics, but it can't tell you the whole story about your audience. Marketing personas with overly specific details aren't practical for media buying, even if they help creative teams remember they're marketing to real humans. The real insight? Stop over-segmenting based on small data samples. Creative does the heavy lifting in audience targeting now, and your best-performing segments might actually be the least incremental. Focus on broader reach, use your first-party data wisely, and break down those silos between departments. Everyone needs to share what they know about your audience.
6 minute readAre marketing best practices helpful or lazy?
TL;DR Best practices in digital marketing aren't one-size-fits-all solutions. While foundational principles like testing and brand consistency matter, blindly following "best practices" can trap you in formulaic thinking. The key is understanding when to apply them, when to break them, and recognizing when someone's just trying to sell you something disguised as a best practice.
3 minute readDeep diving into e-commerce measurement
TL;DR E-commerce success isn't just about ROAS. Smart marketers look beyond surface metrics to understand customer lifetime value, profitability, and the full customer journey. This means balancing short-term acquisition costs with long-term customer value, especially during high-stakes periods like Black Friday. Performance marketers often get tunnel vision on return on ad spend, but the reality is messier. The most successful e-commerce businesses understand that profitable growth trumps vanity metrics every time.
4 minute read