Experimentality

· 6 min read

It's hard to master any platform as a creator.

Sure, there are best practices, trends, and some generally accepted truths about what "works" on any particular platform – but those things also change all the time.

There's really only one reliable path forward...

Sustained success as a creator comes from experimentation.

When I spoke with Austin Belcak, arguably the most successful creator on LinkedIn, he told me that he built a spreadsheet to analyze his content:

I'll go back and I'll look at like the top five to 10 posts, and I'll look at a whole bunch of data points. So I'll look at the character count...And then I'll look at the topics. Is this a personal story? Is this an inspirational or motivational post? Is this a contrarian take? I'll aggregate that data across all of the top posts that I have. And then I will basically create a checklist to say, okay, my top posts for the last quarter have an average of like 552 characters. So every time I write a new post, I'm going to try to be within 100 characters of what I'm seeing be most successful.

Sometimes you get lucky.

Sometimes things go viral.

Sometimes your gut instinct is spot on.

But virality and luck are nearly impossible to predict or engineer.

You need to develop an experimentality.

Defining Experimentality

An experimentality is an experiment mentality (get it?).

Instead of relying on best practices or assumptions, an experimentality pushes you to run small, controlled experiments to find the truth in the data.

An experimentality is what makes you a creator scientist.

Of course, it takes a while to get there.

The Limits of Intuition

No one knows what they're doing when they get started.

So we start by modeling (or imitating) others. This is how we learn the rules of the game. From there, we begin to find our own voice. Now that we know the rules of the game, we can selectively choose which rules to break.

We publish, we gauge the response, and we use that information to inform the next iteration.

This "measurement" is typically done subconsciously. The way we understand the world – our personal mental model – changes as we capture more data.

And we subconsciously capture so much more data than you realize. The number of likes, comments, retweets, and shares your posts get are all data points. Email open rates, click rates, and replies are all data points.

Most creators passively consume this data and operate on gut feeling. You have a "sense" of what type of content "does well" and you do more of that.

This develops your intuition – and your intuition is really valuable. Your intuition allows you to make well-informed decisions quickly and it gets better as you collect more data. But your intuition isn't perfect and it isn't always right. Your intuition is still colored by assumptions.

Most creators stop there. They operate from a place of intuition.

But the best creators on the planet take it a step further. They don't rely solely on their intuition – they rely on data.

Look at this exchange:

It's really prevalent in YouTube. Creators are making changes to titles and thumbnails in order to influence the trajectory of videos:

But it's also true on other platforms and for outcomes like sales too.

Look at this tweet from Thomas Frank pinpointing where an incremental $24,000 in sales came from:

Data is a measuring stick. Data empowers you to run experiments with the goal of influencing that data.

When you influence data, you influence outcomes.

The Power of Experimentation

This is what the best creators in the world are doing. They're constantly running small, controlled experiments in order to learn how they can influence outcomes.

Controlled experiments mean changing one variable at a time in order to determine what variables actually influence the outcome.

For example, it's changing the thumbnail (but not the title). It's adding an announcement bar to your website to see if it influences traffic to another page. It's adding a new section to your sales page to see if it influences sales conversion.

This bias for experimentation is what allows top creators to achieve extraordinary outcomes.

There is a famous story of Dave Brailsford, who was hired as performance director for the British cycling team in 2003.

From Atomic Habits:

Since 1908, British riders had won just a single gold medal at the Olympic Games, and they had fared even worse in cycling’s biggest race, the Tour de France. In 110 years, no British cyclist had ever won the event.

Brailsford had a theory: if he could influence different aspects of cycling in order to achieve an incremental 1% improvement, those incremental improvements would have a massive impact when taken all together.

They tested things like:

  • Redesigning bike seats
  • Wearing heated shorts
  • New pillows and mattresses
  • Different massage gels for recovery

As a result, just five years later, the team won 60% of gold medals in the 2008 Olympics. Then, in the 2012 Olympic games, the British set nine Olympic records and seven world records!

I love this story. This is a perfect illustration of how running disciplines, rigorous experiments can have a massive, outsized impact. After all, the British just post faster cycling times...they posted the fastest times ever.

Rigorous experimentation is not only how you achieve improvement, but world-class results.

How To Foster Your Experimentality

This may seem complicated – but it doesn't have to be.

You may remember the scientific method from grade school:

  1. Make an observation
  2. Ask a question
  3. Form a hypothesis or testable explanation
  4. Make a prediction based on the hypothesis
  5. Test the prediction
  6. Iterate: use the results to make new hypotheses or predictions

I simplify things even further for most of my experiments. I use this framework for the experiments I run and share in The Lab:

  1. 🎯 Goal
  2. 🤔 Hypothesis
  3. 🧪 Experiment
  4. 📓 Results

This framework allows you to start with a Goal in mind. Then it challenges you to form a Hypothesis for how you can influence that goal. Then you design (and run) an Experiment to test that Hypothesis and measure the Results.


Here's an example Experiment I shared with The Lab:

🎯 GOAL
Get people to listen to/care about re-aired, past episodes as much as new episodes.

🤔 HYPOTHESIS
As a listener, I don't like when a podcast re-airs an episode but doesn't make that clear from the title or intro. There have been times that I listen to an episode and quickly realize, "Wait is this the same episode with this guest I listened to years ago?"

So in the past when I've re-aired episodes, I tag the title with [REPLAY].

I wondered if I could use literally just a different word/tag to signal that this is worth listening to. Maybe "Replay" makes it seem not new AND not exciting?

🧪 EXPERIMENT
I re-aired my episode with Codie Sanchez. The reality is, there are a lot of weeks where playing a past episode is a BETTER listener experience than me pulling together some off-the-cuff solo episode.

Instead of [REPLAY] I started the title with [GREATEST HITS]. I was hoping this would signal to folks that this was a POPULAR, HIGH-QUALITY episode, and even though it's not "new," if it's new to you then you should listen.

📓 RESULTS
We're only 48 hours in, but this episode is performing ~100% better than past re-aired episodes. It seems (so far) that it's performing on par with a NEW episode (and a GOOD new episode) and I've had several listeners talk about it on social media.

Very good signals!

If this type of performance is repeatable, not only will I publish a Greatest Episode at least once a month, I may publish 2-4 Greatest Hits episodes/month. With 140+ episodes, this would resurface episodes consistently while also giving me extra ad inventory to increase sponsorship revenue on the podcast (with little extra work).


To do this very well, you want to have well-structured experiments where you only change ONE variable at a time. But take some baby steps! Start by using this four-part framework above to design and run your own experiments.

Let's say your goal is to increase course sales. Start by getting a baseline for the current conversion percentage of unique visitors to customers. Then, you can design an experiment to try and influence either a.) traffic to the page or b.) conversion percentage.

I'm running that experiment right now! Here's a video I shared with The Lab:

I know it sounds like more work and maybe less fun than just throwing spaghetti against the wall and seeing what sticks...but an experimentality is the best way to future-proof yourself against a rapidly changing environment.

It will help you be more innovative and more resilient.

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