In the agriculture industry, many marketers stick to the same playbook year after year, never questioning whether their creative or messaging still works. But the truth is, playing it safe isn’t actually safe at all. It leads to missed opportunities, stagnant growth, and audience fatigue. On the other hand, launching bold new campaigns without proper testing can compromise your budget. The difference between a good marketer and an excellent one? Good marketers step outside the box. Excellent marketers test their ideas before committing the full budget. Smart experimentation lets you try new tactics affordably, so you’re making decisions based on proven data—not expensive assumptions.
What You’re Actually Risking When You Don’t Test
You might become apprehensive when thinking about adopting an experimental approach when it comes to ag marketing, but the real risk is not knowing what works. When you run campaigns based on unproven tactics, you’re gambling with your budget. While you’re playing it safe, your competitors are testing, learning, and pulling ahead. That means your team is always playing catch-up, trying to stay relevant while others set the pace.
Testing helps you identify what actually drives results—so your full budget goes toward proven creatives, audiences, and messaging instead of guesswork. Making data-driven decisions gives you clear insight into what resonates with your target audience, leading to more predictable and consistent results. And maybe most importantly? It gives you a competitive edge in ad auctions and engagement.
Why You Should Always Test Before You Spend
Pre-launch testing is an investment because it helps allocate your total budget in a smarter way. Testing with smaller budgets lowers your risk. If a tactic fails, you’ve lost hundreds, not thousands. If it works, you can scale confidently knowing your budget is going toward proven winners, improving your overall ROI.
Testing also leads to faster optimization when using the full budget. No need to start from scratch; you can launch with a strong foundation. Most importantly, you’ll have a competitive advantage in ad auctions and engagement.
What Root+Beta Learned by Testing (That We Wouldn’t Have Guessed)
Experimentation is rooted in our strategy with each client, particularly A/B testing. Running tests ensures our clients get quality leads and conversions, and it lets us optimize campaigns as much as possible. Through testing, we’ve uncovered insights we never would have guessed.
Here’s what the data showed us:
- Carousel ads beat static on social every single time (no matter the client, creative, or audience)
- Video creative preferences vary by audience—it’s not one-size-fits-all
- Display campaigns perform best with both animated and static images (not just one or the other)
- Platform performance differs by creative type—what works on Facebook doesn’t always work on LinkedIn
These aren’t theories. They’re data-backed findings that only experimentation revealed. Without testing, we’d still be guessing. Now when we launch new campaigns, we pull from this data to drive the results our clients need.
How to Set Up Your First Real Test
You don’t need a massive budget or extensive experience to run a useful test. All you need is a simple system for guaranteed clarity.
Here’s the bare minimum framework for a successful experiment:
- Define one clear objective (what are you trying to improve?)
- Pick one measurable KPI tied to that objective
- Keep your audience consistent across test versions
- Set up trackable conversion events (no guessing allowed)
- Test at least two variables (two creatives, two messages, two targeting approaches)
- Allocate a small but sufficient test budget to generate meaningful results
This structured, repeatable process turns raw numbers into clear insights and next steps. Every experiment should produce clear, trustworthy, and actionable learning.
How to Measure Test Success
To accurately measure whether your test worked, define one primary KPI per test. Make sure you have enough of a sample size—whether that’s impressions, clicks, or conversions.
To attribute results correctly, change only one thing at a time. Keep budget, timing, and objectives equal while running both versions simultaneously. The more disciplined your setup, the more powerful and actionable your learnings become.
Failed Test vs. Poor Execution
Sometimes our predictions don’t always pan out as we think. Before you write off a tactic entirely, check whether the test had a fair chance to work. A tactic may look like it failed when the setup was actually the problem.
Signs of Poor Execution:
- Broken tracking
- Audience mismatch
- Weak or unclear creative
- Landing page problems
- Insufficient budget or test window
- External events (weather, holidays, market volatility)
- Performance way below historical baselines
Signs of a True Tactic Failure:
- Even strong creative underperforms in this specific tactic
- Multiple test rounds show the same poor results
- Historical data confirms the pattern
Run a diagnostic test: Swap in your best-performing creative or audience from another channel. If performance improves, execution was the issue. If it stays poor, the tactic itself is likely the problem.
Start Small
If you’ve never run an A/B test before, start ridiculously small. Don’t jump into complex tactics right away.
Start with a simple, high-impact test with clearly defined KPIs and tight control. Change only one variable at a time. This cuts down confusion and leaves little room for false learnings. Once you build confidence, you can scale up to bigger, bolder experiments.
Trying something new isn’t reckless—it’s strategic. It’s the best response to an industry that’s moving faster than ever. The marketers who experiment will outpace the ones who wait for certainty.
Want help setting up your first marketing experiment? Email us at howdy@rootandbeta.com, give us a call at (501) 291-1642, or schedule a meeting with us today.