The Butt Fumble Effect: Why A Lack of Certainty Is Killing Brands in Agriculture

In agriculture, decisions aren’t made on data alone—they’re made on the fear of repeating the last mistake.

It was the second quarter of a Thanksgiving Day game in 2012. The New York Jets were trailing, but not hopelessly. The kind of deficit that could be overturned with the right play, the right spark.

Mark Sanchez, the young quarterback with movie-star looks and a career still very much in progress, took the snap from center. He turned left. The fullback went right. There was no one to hand the ball to.

What happened next wasn’t a sack. It wasn’t even really a tackle. It was something stranger.

Sanchez stumbled forward and collided—face-first—with the rear end of his own offensive lineman, Brandon Moore. The ball came loose. The Patriots scooped it up and scored. And in that single, bizarre sequence of misfortune, Mark Sanchez wasn’t just tackled. He was immortalized.

The play would come to be known as the “Butt Fumble.”

For forty straight weeks, it topped ESPN’s “Not Top 10” list. It outlasted bloopers from every other sport, in every other season. It became a kind of cultural shorthand for a very specific kind of failure where something small and ordinary goes embarrassingly, irreversibly wrong.

Rex Ryan, Sanchez’s head coach, put it best:

“As soon as you say Mark Sanchez, people think Butt Fumble. But we did win a few games together. Sanchez was a good quarterback—he just had a horrible moment. Mark won more playoff games than any quarterback in Jets history—that includes Joe Namath. Everybody has a bad moment in their career that you'd like to forget. But this one, because of the way it was labeled and the disaster that the play turned out to be, unfortunately, this one lives on and probably always will.”

It didn’t matter that Sanchez had been competent, sometimes even clutch. One play rewrote the narrative. One failure became his identity. Sanchez’s career, once promising, soon petered out.

This happens outside of football, too. In business. In agriculture. In the very way customers experience your brand.

Because we don’t judge performance as a curve. We remember how something makes us feel when the stakes are high. We remember the moment when certainty disappears.

In the 1960s, a young copywriter named Joel Raphaelson was working at the famed ad agency Ogilvy & Mather.

He was surrounded by Madison Avenue’s best, in a business—and let’s be honest, still an industry—built on a simple belief: say it louder, say it often, say you're better.

But Raphaelson noticed something strange. People didn’t buy the brand they thought was better. They bought the one they were more certain wasn’t bad.

It was a quiet insight, yet profound. Customers weren’t optimizing for superiority, as most people assumed they were. They were frequently minimizing the chance of regret.

In agriculture, we’ve been trained to chase performance—yield bumps, ROI per acre, and biological breakthroughs. New traits, new tools, new tech.

But while companies compete to prove they’re better, most customers are asking something simpler:

Will this actually work for me?

Because by the time someone encounters your brand or offer, it’s rarely their first attempt to solve the problem. They’ve already tried to grow. Tried to spend smarter. Tried to make technology work on their farm. And underneath every “maybe next year” is a quiet, unspoken fear:

What if this doesn’t work and I look like an idiot?

What if I spend $10,000 and it fails? What if I recommend this to a colleague and it backfires? What if my neighbor sees me using it and I can’t prove it made a difference?

Certainty isn’t just rational. It’s emotional, too. And the moment your product makes someone feel exposed, even if it’s technically “better,” you’ve lost the ability to charge a premium for your brand.

Raphaelson didn’t just uncover a better way to write copy. He exposed the foundation of trust. People don’t buy what’s best; they buy what feels like it has the least amount of associated downside.

Suppose I were to ask you to play a simple game of chance.

In this game, each player starts with $100. Every round, you flip a coin. If it lands on heads, you gain 50%. If it lands on tails, you lose 40%. Would you agree to play this game?

Most people, I think, look at this written on paper and think "of course I would play that game." On average, after all, you should gain 5% every time you flip the coin. But when the physicists Ole Peters and Alexander Adamou ran the simulation a few years ago with four players, they discovered something strange.

The average outcome per round was, in fact, positive across the entire group. But the more rounds each individual played, the more likely they were to lose money. When Peters and Adamou modeled the game, they tracked four players flipping coins over multiple rounds. Each started with $100.

• Player One flipped heads twice. First $100 became $150, then $225. A win.

• Player Two flipped heads, then tails. $100 grew to $150, then dropped to $90.

• Player Three flipped tails first, then heads. Same: $100 to $60 to $90.

• Player Four flipped tails twice. $100 to $60, then down to $36. He now needed three straight heads just to get back to where he started.

The group average after two rounds was $110.25. Up 10.25%.

But three of the four individuals had lost money.

This is an example of what mathematicians call a non-ergodic system, a system where the average of the group does not reflect what happens to the individual over time.

In real life, you don’t get to reset after a bad round. Losses compound. One bad outcome changes the next set of decisions. And over time, the consequences of volatility stack higher than the promise of upside.

Agriculture is a non-ergodic system.

Every decision builds on the one before it. One bad season can erase five good ones. One underperforming product, one recommendation that backfires, one year of betting wrong, and suddenly your strategy isn’t about optimizing anymore. It’s about recovering.

Our customers are not trying to optimize for better performance, they’re trying to protect against downside.

Yet most ag marketing still pitches to the average. The average yield increase. The average ROI. The average performance across trials.

And then when our customers don’t react to this type of message, we call them irrational. We shake our heads about how silly they are not to follow our carefully crafted economic models, but ergodicity and the cautionary tale of Mark Sanchez shows us that they are not irrational at all.

For some reason, this is a very difficult lesson for brands to learn. We have, I think, a very rigid and limited definition of what it means to “prove value.” We measure upside. We forecast averages. We assume the customer sees what we see when we show them trial data and charts that climb.

Why do we treat the fear of downside like irrational behavior, instead of seeing it as the most rational response to living inside a system where volatility compounds, and trust is hard to recover?

And what would change if we started marketing, not to the average outcome, but to the individual who’s still recovering from the last fumble?

Because across agriculture, that’s exactly who we’re selling to.

• The grower who watched last year’s “proven” seed underperform.

• The retailer who trusted a data set that didn’t translate to their region.

• The agtech customer who still has to justify a failed rollout.

• The borrower who has been burned before.

They don’t need more upside. They need someone who understands the cost of being wrong.

And this is where most brands lose their relationship with the customer and their ability to charge a premium price.

Not because the product wasn’t strong.

But because the experience failed to address the stakes from the customer's perspective.

In seed, it’s not just about yield trials. Everyone has them. Everyone claims an edge. But few acknowledge that the biggest question on a grower’s mind isn’t “Can this hit 250 under ideal conditions?” It’s: What happens when the season turns sideways? Show me how dealing with your brand protects my downside, not just how your product performs at the top.

In crop protection, the fear is that I’ll try your product, and it won’t work like you said it would and then I’ll be the one holding the bag. And next year, I’ll be back to square one, with a few less dollars and a few more regrets. You’re not competing against another product. You’re competing against the memory of failure.

In feed, it’s not about who has the most proprietary blend or published trial. It’s about which company understands the daily volatility I deal with,,,input costs, weight gain variability, weather swings…and builds its service around managing that volatility, not just pitching formulas. Because I don’t need more “science.” I need predictability.

In agtech, every new tool promises transformation. Most don’t deliver. And the buyer knows: If this flops, it’s my name on the line. So the most successful agtech companies aren’t the most advanced. They’re the ones that offer the clearest path to upside without demanding the customer stake their reputation to get it. Low cognitive load. Low behavioral risk. High clarity.

In every case, the question underneath the sale is the same:

Will you still be here if this doesnt work like you said it would?