Noticed you’re on an iOS device.
Get our mobile app for effortless planning on the go.
Log in with planable.io
Noticed you’re on an Android device. Get our mobile app for effortless planning on the go.
Log in with planable.io
Planable is the best client-facing social media tool we've ever used and we've used a lot.
The platform has moved far beyond job hunting; it's now where brands earn trust, spark conversations, and meet the people who shape buying decisions. As you build your approach, it also helps to think about the practical side of staying consistent. Learning how to...
Dec 9, 2025
Think back to the last post you published or campaign you launched. You probably spent hours perfecting the caption, choosing the right visuals, and timing it just right.
The results? All over the place.
I’ve been exactly where you are. Over my 5+ years in social marketing, I’ve managed more accounts than I can count. And I know how disappointing numbers stung. But what really got to me? Not knowing what was actually moving the needle.
That’s when I made a shift: I started treating content as experiments. This is what helped me grow my Grad Girl Marketing community to 400K+ and partner with 70+ brands:
Why do I believe in this mindset? Because predictions eliminate randomness. Tests reduce risk. Patterns reveal strategy.
This transformed into a 7-step experimentation process I now follow. And I’m going to share it with you, along with frameworks and checklists, so you can test this approach yourself.
Here’s what I like about content experiment planning: you never start from zero.
You’ve got nine content experiment sources constantly running in the background, feeding you ideas. Think of these as your content testing pipelines, places where experiment ideas naturally emerge from what’s already happening in your business and industry.
What keeps your audience up at night? What goals are they chasing? Each pain point becomes a hypothesis. If you address this specific frustration, engagement might increase because it hits what they actually care about.
Questions your support team gets are potential content experiments. Test different formats for answering them. Does a quick video perform better than a carousel? Do people prefer step-by-step tutorials or conceptual explanations?
Myth-busting content works because people love learning something surprising. You can test different angles here: Do dramatic hooks about doing things wrong perform better than gentle corrections? Does humor lower resistance to being corrected? Spoiler: it does. Planable’s Social Media Manager, George Danaila, tested this himself:
Humor was the thing. It consistently stopped the scroll long enough for the core message to land. It created instant attention, lowered resistance, boosted engagement, and quickly became an important part of our content strategy.
What topics are competitors covering that get engagement? More importantly, what are they missing? Use their content as signals for what your shared audience cares about, then test your unique angle.
There’s a gap between what you think is valuable and what customers actually understand. Test different ways to bridge that understanding gap: before/after comparisons, time-saving calculators, customer stories.
People are curious about the mechanics behind products they use. You can test different formats here: Does polished behind-the-scenes content perform better than raw, unedited clips? Do people engage more with process explanations or outcome reveals?
If everyone in your industry says one thing, and you have evidence to say the opposite, that’s your experiment. Test it. You’ll probably see that safe content keeps your current audience, but risky content, though, attracts new ones. That’s what Planable’s SMM, George, learned from running hundreds of content experiments:
Experimental topics attracted new audiences faster than safe ones. Sometimes the posts I was least sure about pulled the most non-follower reach, meaning riskier angles were better for growth.
If you sell running shoes, test content about training plans, injury prevention, or race day preparation. See if this broader context builds more engagement than product-focused content. Sometimes the adjacent topics outperform direct pitches.
Carousel template trending? A sound going viral? A format everywhere? These are experiment opportunities. Plug your message into a format that’s already proven to capture attention. Test whether the format carries your content better than your usual approach.
But ideas alone are not enough. You need to turn them into testable hypotheses.
Most social teams skip this step and go straight from idea to production to hitting publish and crossing their fingers.
But here’s what I learned: experimentation needs a middle layer. You need a specific, testable hypothesis about what will happen and why.
The formula I use:
If we post [format + idea] for [audience], then [specific metric] will increase because [reason rooted in insight].
Let me break down each piece:
🚨Important! Map intent to a specific metric because optimizing for everything is optimizing for nothing.
Weak hypothesis: Let’s try Reels about the industry. Our audience might like it.
This tells you nothing. What should the Reel be about? Who’s it for? What metric should improve? Why should it work?
Strong hypothesis: If we post 15-second myth-busting Reels targeting social media managers, saves will increase because this audience values quick, actionable corrections they can reference later.
Now you have everything: format (15-second Reels), idea (myth-busting), audience (social media managers), predicted metric (saves), and reasoning (they value reference material).
Another example.
Weak hypothesis: Let’s try thought leadership on LinkedIn.
Strong hypothesis: If we share founder POV hot takes on AI content for marketing directors on LinkedIn, shares will increase because people signal expertise by sharing contrarian views in their networks.
A good experiment is controlled, simple, and deliberate. It isolates the element you want to learn from so you can actually attribute the outcome to a single cause. Change everything at once, and you won’t know what worked or what flopped.
Here are the 5 variables I focus on:
Not every post needs a CTA. People have had enough of ‘click the link,’ ‘tag a friend,’ or ‘share this post.’ I found that forcing a CTA too often actually hurts performance. Sometimes the most effective posts were the ones that simply delivered value and let the audience engage naturally.
My golden rule is to isolate one variable at a time.
If you change the format AND the hook AND the platform simultaneously, you won’t know what caused the results. Was it the topic that failed or the packaging? Was the idea good with the wrong format? Does this concept work only on specific platforms? With variable control, you can diagnose the problem.
After running hundreds of experiments, I know that to get results you can actually learn from, you need clean execution. This requires discipline around timing, volume, and process.
Here’s my testing protocol:
These rules might feel rigid. But when you follow protocol, you can confidently say this format works instead of maybe this format works but we also changed three other things so who knows.
This is the most challenging part for me, and I guess for most social media managers. Analytics can overwhelm you with too many numbers or leave you lost because you don’t know what matters. The way through is to cut through the noise.
Go back to your hypothesis. You already defined your primary and secondary metrics when you created your hypothesis (Step 2). Don’t get distracted by every number in your analytics dashboard. Focus on what you predicted would increase.
After my testing window closes, I analyze each experiment. I use Planable analytics for this entire step because opening five platform dashboards to compare performance was killing me.
Here’s what I check:
There are some things you can check during the first few hours after posting. This can still tell you something, though not everything. Find out how I read early signals vs. noise in the free kit.
After running and analyzing experiments, sort experiments into three buckets: winners, near-misses, and dead ends. Here’s how I do it:
What qualifies: Consistently outperformed on your target metric across multiple posts (not just one lucky post). This format, topic, or approach works for your audience.
The thresholds I use:
What to do: Scale these. Make them a regular part of your content mix. These go directly into your official strategy.
What qualifies: Something worked (maybe the topic resonated), but something didn’t (maybe the format felt wrong). There’s potential here, but it needs refinement.
The thresholds I use:
What to do: Iterate and retest. Change ONE variable and try again. This is where teams often give up too soon; you shouldn’t.
What qualifies: Didn’t validate the hypothesis, even after iteration. This approach doesn’t work for your audience right now.
The thresholds I use:
What to do: Drop it. Don’t force it. It’s okay to kill experiments. Don’t waste your time here; better think of another experiment.
My simple decision rule:
Create a library of tested, evidence-based patterns that actually move your metrics. This should include:
This will help you move from we should post educational carousels because education provides value to educational carousels with myth-busting hooks increase saves by 28% on average across 12 tests. Post these twice weekly on Instagram and LinkedIn.
Here’s how this played out for Planable.
George and the team ran experiments testing creative, personality-led videos against purely educational content. The hypothesis was that educational content would perform well because it delivers clear value. But after running multiple tests over several weeks, the data told a different story:
The real surprise was how much better creative, personality-led videos performed over time compared to purely educational posts. Creative formats kept compounding: stronger repeat engagement, more non-follower reach, and better long-term retention. Educational content tended to be more niche and didn’t consistently match the audience’s appetite. That insight shaped our content strategy: We didn’t abandon educational content, but we made creative, personality-driven content our foundation.
As you run more experiments and discover new patterns, add them to your playbook. Your strategy improved as your evidence base grows.
Never stop experimenting cycles because your winners won’t work forever. Here’s the distribution I aim for:
You’ve seen the framework. You understand the mindset. You know the seven steps. Now it’s time to test. But first, grab my free kit with all the templates, checklists, and tracking sheets you’ll need to run your first experiment cycle.
I started Grad Girl Marketing in 2020 to build the go-to global community for marketers who love what they do. Every Monday I drop my top 5 campaigns, host buzzing London networking events, collaborate with brands on killer content, and share daily career + marketing insights across socials. Let’s make marketing more human (and a lot more fun).
Create
Schedule
Plan
Engage
Collaborate
Analyze
Approve
