George Bonaci: Why Most Growth Teams Are Placing Bets Too Slowly

The False Precision of Waiting for Perfect Data

George Bonaci once faced a crisis at a previous company: their number one acquisition channel was dying. Conversion rates on a critical web page had been declining for months. The team had two options: run a series of controlled A/B tests to isolate which variables mattered, or throw everything at the wall at once and hope something stuck. They chose chaos.

They 3x'd the conversion rate in weeks. They also had no idea what actually worked. Months later, when they finally ran proper tests, they had to undo half the changes. This tension—between velocity and rigor, between hitting the number this quarter and understanding the underlying mechanics—defines Bonaci's approach to growth at Ramp, where he leads efforts for one of the fastest-growing fintech companies in the market.

Growth is mostly just science. You kind of have to come in with a blank slate, form a hypothesis, and then run a bunch of experiments. You'll be surprised about what works, you'll be surprised at what doesn't work.

— George Bonaci

Before Ramp, Bonaci was VP of Growth at Gong and helped scale Samsara from $100 million to $650 million ARR through its IPO. His background is chemistry, not marketing—a detail that explains his allergy to the copy-paste playbook mentality that dominates most growth teams. He believes the vast majority of marketers are bad at science, and that's why they fail.

Saturation Should Happen in Weeks, Not Years

When a channel starts working, most startups tiptoe toward scale. They go from $10K to $15K, then maybe $20K, watching the metrics, being prudent. Bonaci thinks this is a catastrophic mistake. If something works, he wants to spend $200K immediately and find the asymptote—the point where returns start decaying—as fast as possible.

The logic is ruthless: every day you spend gradually ramping is a day competitors could discover the same channel, a day the market could shift, a day you're leaving growth on the table. Yes, the $200K won't be as efficient as the initial $10K. But mapping the entire response curve in weeks instead of quarters gives you information capital that compounds.

Most companies get to that asymptote too slowly. They should really be scaling much, much faster if they find something that works. Most things saturate probably more slowly than people expect.

— George Bonaci

This philosophy extends to how he thinks about customer acquisition costs. The textbook answer is that CACs always increase as you saturate your core market. But Bonaci has rarely seen this play out in reality at Samsara, Gong, or Ramp. Why? Because before true saturation hits, teams discover new products to sell, new geographies, new channel combinations that create halo effects. The macro pressure of rising CACs is real in theory, but it takes far longer to materialize than founders fear.

Hire Junior, Fire the Playbook

Bonaci would rather hire for potential than experience, especially early in a company's life. Senior marketers bring pattern recognition, which sounds valuable until you realize that patterns from one company rarely transfer cleanly to another. They arrive with a playbook—say, the Gong content strategy or the Samsara paid acquisition stack—and try to transplant it wholesale. It almost never works.

The tendency of a lot of marketers is to think in terms of, what do I know and how can I apply it here? That's usually lost because they don't think in terms of experiments.

— George Bonaci

Junior people don't have a playbook to cling to. They're more willing to run weird experiments, test channels no one has validated, and operate without the safety net of "this worked at my last company." Bonaci believes a good leader should know how to do everyone on their team's job, but poorly—the "poorly" part matters because it keeps the leader from micromanaging execution while still understanding the constraints.

This preference for junior talent ties directly to his view on failure rates. He expects the majority of experiments to fail. If a growth team isn't failing most of the time, they're not taking enough risk. That mindset is incompatible with senior hires who have reputations to protect and frameworks to defend.

The Portfolio: Time Horizons, Not Just Impact and Effort

Most teams prioritize experiments on two axes: impact and effort. Bonaci adds two more: confidence and time to results. If you're highly confident something will work, just do it—don't waste cycles debating. If you're uncertain but can get an answer fast, do that too. The four-dimensional framework forces teams to balance short-term wins with long-term moonshots.

He structures his portfolio like a venture fund, but the asset allocation depends on the stage of the company and whether the priority is growth or profitability. Early-stage companies should skew toward high-risk, high-reward bets. Later-stage companies need a heavier weighting toward high-confidence, incremental improvements to hit quarterly numbers. The mistake is doing only one type of bet.

You have to have some bucket of bets that are going to be those big swing, huge step changes in impact. But those are generally high risk, high reward. You can't just do that, otherwise you're going to fail and miss your number this quarter.

— George Bonaci

Content is the clearest example of a long-horizon bet. Bonaci acknowledges it can take 12 to 18 months to see real returns, which is why it belongs in the 20–30% bucket allocated to long-term experiments. The key is defining leading indicators upfront so you're not flying blind for a year. If you can't find early signals, scope the experiment down until you can.

Premortems Predict Failure, Postmortems Find the Black Swans

Before launching any experiment, Bonaci's team writes a premortem: a document listing every way the experiment could fail. Not just the top three risks, but all of them—insufficient sample size, misaligned stakeholder incentives, technical blockers, broken attribution. For high-confidence bets, the premortem is right about 90% of the time. When an experiment fails for a reason already in the premortem, there's no postmortem. It's wasted motion.

Postmortems are reserved for surprises—experiments that failed for reasons no one anticipated. These are the black swans, the learnings that can reshape how the team thinks about other channels or customer segments. The person who owned the experiment writes the postmortem in a Google Doc, sends it out 24 hours in advance, and then leads a live conversation. Bonaci hates comment threads that replace real dialogue.

No one should be that attached to the experiment that they're running. They should acknowledge that the vast majority of what they work on is going to fail. If you're not failing, you're probably not doing your job well.

— George Bonaci

This cultural expectation—that failure is the default—eliminates the morale problem of killing someone's pet project. If a team member is emotionally attached to a failing experiment after three months, that's a red flag about culture, not a sign of passion. At Ramp, experiments are hypotheses, not identities. The goal is to learn fast, not to be right.

LTV Is a Lie You Tell Yourself to Feel Smart

Bonaci calls LTV-to-CAC ratios "false precision." If your company has been around for six months, you have no idea what customer lifetime value actually is. You're guessing, extrapolating from incomplete data, and pretending the number means something. He still uses the framework—because you need some threshold for what you're willing to spend versus what a customer is worth—but he refuses to pretend it's rigorous.

The better approach is to set a spending threshold the business is comfortable with, treat it as provisional, and update it as experiments produce real data. This threshold should change every quarter as the team learns which channels drive higher retention, which customer segments expand, which geographies have different unit economics. The metric is a starting point for conversation, not an end point for analysis.

This pragmatism extends to his view on alpha in growth. You find it by doing things no one else knows about, or by doing things everyone is convinced won't work. The second path is harder because it requires ignoring conventional wisdom—the same conventional wisdom that senior hires bring in their playbooks. Bonaci's edge at Ramp comes from his willingness to test the ideas that sound stupid in planning meetings, to move faster than feels comfortable, and to accept that most of what he tries will fail. The companies that win aren't the ones with the best strategy. They're the ones that run the most experiments before the market shifts.