Alex Schultz: Why All Marketing Is Performance Marketing

The Brand Versus Performance Debate Is a Fiction

Alex Schultz doesn't believe in the distinction between brand marketing and performance marketing. He thinks it's a false binary that's plagued the industry for decades. "Performance marketing is all marketing," he says flatly. "People make this distinction that you have brand marketing and performance. You have brand and direct response, and all marketing is performance marketing."

This isn't an academic point for Schultz. As CMO and VP of Analytics at Meta, he oversees both the brand strategy and the data infrastructure that powers billions of dollars in marketing spend. The dual role itself is unusual—most companies split brand and analytics into separate fiefdoms. But Schultz sees them as inseparable. "I wouldn't have taken CMO if I thought brand didn't matter," he explains, pushing back against the idea that his analytics background makes him a pure direct-response operator.

Performance marketing is all marketing. So people make this distinction that you have brand marketing and performance. You have brand and direct response, and all marketing is performance marketing.

— Alex Schultz

The implication cuts both ways. Brand marketers who can't measure outcomes are fooling themselves. Performance marketers who ignore brand equity are leaving money on the table. Schultz's view is that every marketing dollar should be accountable to a goal, and every goal should connect to the company's mission. The split between the two disciplines, in his telling, is an artifact of organizational politics, not strategic clarity.

Your North Star Isn't a Metric—It's a Mission

Schultz has spent years refining Meta's approach to North Star metrics, but his most counterintuitive insight is that the North Star itself isn't actually a metric at all. "The North Star is not a metric," he insists. "The North Star is your goal. Your goal is like, what are you trying to achieve? When I joined Meta, it was connect the world online, full stop. And then the metric describes the goal."

This distinction matters because metrics are always imperfect proxies. "A metric never perfectly describes a goal. A metric is always broken," Schultz says. He's seen too many companies optimize themselves into irrelevance by gaming a metric that sounded good in a board meeting but didn't actually capture what mattered. The classic trap: a startup chases monthly active users while ignoring retention, piling up vanity numbers until churn catches up and the whole edifice collapses.

Schultz points to a defining moment in Meta's history as proof that clarity of mission trumps everything else. When Yahoo tried to acquire Facebook in the mid-2000s, most of the executive team wanted to sell. "It felt like the North Star to a lot of the executives was, it's a startup, we need to make it big and exit and become millionaires," Schultz recalls. Mark Zuckerberg disagreed. His North Star was to connect the world, not to cash out. The result: "We turned over the entire executive team. And then out of that fire, which I think really forged the company, we came to much more clarity on what the North Star was."

The North Star is not a metric. The North Star is your goal. Your goal is like, what are you trying to achieve? When I joined Meta, it was connect the world online, full stop. And then the metric describes the goal.

— Alex Schultz

For early-stage founders, Schultz's advice is simple: pick one thing that matters pre-product-market fit, and it's probably retention. "The only metric you care about in consumer and SaaS is retention," he says. "Do you create a product that people keep using?" Everything else is noise.

Growth Teams Should Be Tiny—and Hired Late

One of Schultz's most provocative operating principles is that most companies hire growth teams far too early. At Meta, a company with nearly 100,000 employees, fewer than 1% work on growth. Instagram's growth team? Around 25 people. The central growth team that supports Facebook, Instagram, WhatsApp, and Reality Labs? A few hundred. "I think growth is one of those fields where small talent-dense teams" work best, Schultz says.

But the bigger insight is timing. "If you're in a very small company and you've got like 200, 300 people, I would argue you shouldn't have a growth team at that stage," Schultz argues. "I would argue the entire company should be working on growth." His logic: growth is the CEO's job early on. Delegating it to a specialist team is premature optimization. "Growing your company is probably the single most important job of the CEO," he says. "So many companies try and hire a growth team at like 50 employees and it's just silly."

When growth teams do make sense—at scale—they should focus on platforms and infrastructure, not product features. At Meta, the central growth team handles SEO, ad tech, email infrastructure, and other foundational systems that every product uses. Individual products like Instagram have their own small embedded growth teams that handle product-specific work, but they don't operate in isolation. The model is partnership, not outsourcing.

If you're in a very small company and you've got like 200, 300 people, I would argue you shouldn't have a growth team at that stage. I would argue the entire company should be working on growth.

— Alex Schultz

Schultz also offers a sharp example of why growth teams exist at all: to advocate for marginal users. At Instagram, the entire team consisted of power users who hated notifications. They defaulted notifications off for likes because their own phones were unusable otherwise. But new users uploading their first photo desperately wanted those notifications. "That first like is really meaningful and it's kind of heartwarming and touching," Schultz says. The growth team's job was to remember that not everyone is a power user—and to build accordingly.

One-Person Companies Are Coming (Maybe)

Schultz has a provocative take on AI's trajectory: one-person companies are inevitable. "If we really are going to see advances in intelligence through artificial intelligence that are being suggested by the leaders of the field, then it's going to get very weird indeed, and you're going to see entire companies be one person," he says. He's not being hyperbolic. He compares AI's development curve to semiconductors, where the industry has always known roughly two breakthroughs ahead. "We were talking about agentic behavior 2 years ago. Engineers that were AI engineers, well, that was about a year and a half ago everyone was kind of talking about that."

The mechanics are already visible. Schultz points to startups where founders handle 90% of their legal work using GPT, then ask three precise questions to an outside firm. "They scaled themselves an entire in-house legal department with GPT," he notes. Finance, customer service, even product work—large chunks are getting automated. The question isn't if, it's when. "Do we hit a plateau that means it doesn't happen in our lifetime? Maybe," Schultz concedes. But he's betting against the plateau.

The bottleneck isn't intelligence—it's infrastructure. Schultz describes a global shortage of data center capacity driven by physics, not software. Meta is building a data center the size of Manhattan in Louisiana. Microsoft is bringing Three Mile Island back online. Elon Musk is deploying gas turbines. But the supply chain for generators, fiber optics, switches, and energy itself is lagging. "There was a certain supply chain globally that existed for making data centers," Schultz explains. "And there's also a certain supply chain in terms of energy available." Right now, demand has outstripped supply across the board. "On most of this, it's like an 18-month lag till the system catches up with the demand."

If we really are going to see advances in intelligence through artificial intelligence that are being suggested by the leaders of the field, then it's going to get very weird indeed, and you're going to see entire companies be one person.

— Alex Schultz

The implication for founders: the tools are coming, but the world isn't quite ready. Continental-scale training systems, advances in chip design from NVIDIA, and breakthroughs in energy generation will unlock new waves of capability. But the timeline is constrained by copper wire, steel, and kilowatts—not by algorithms. The future is less a question of what AI can do and more a question of how fast humanity can build the physical substrate to support it.