Content Strategy
Content Is a Power Law Game Now
Content outcomes are uneven. The advantage comes from building a system that finds what your ideal customers cannot ignore.
By Enzo Sison6 min read
Most companies still run content (opens in a new tab) like a publishing operation.
Make a calendar. Post consistently. Keep the quality high. Try to make every piece perform a little better.
That model is built for a follower-first internet. The internet has changed.
Instagram and TikTok increasingly distribute content through recommendation systems. TikTok says follower count and an account's past high-performing videos are not direct ranking factors in its For You system. Instagram now offers Trial Reels specifically so creators can test content with non-followers first.
Every strong piece has a chance to travel beyond the audience you already own. That creates a different distribution of outcomes.
Most posts do very little. A few do well. One can reach more of the right people than everything around it combined.
Content is a power law game now. Your strategy (opens in a new tab) should reflect it.
Optimize for outliers, not averages
Most content teams optimize for the average.
Can every post get a little more engagement? Can we maintain the calendar? Can we make this month's numbers look smoother than last month's?
Those are useful operating questions. They are not the highest-leverage objective.
When outcomes are heavily skewed, a small improvement across average posts can matter less than one extreme winner. The job is not to eliminate every quiet post. The job is to create more intelligent chances to discover the one that breaks through.
That changes the unit of work.
Content stops being a calendar to fill. It becomes an experimentation engine.
Relevant reach is the real prize
Virality is a weak goal because reach without relevance is mostly noise.
Ten million random views can produce less business value than one hundred thousand views from people who share the same urgent problem.
The objective is not maximum reach. It is maximum relevant reach.
That begins with a precise ideal customer profile. "Business owners" is not an audience. Neither is "entrepreneurs."
Imagine you sell software to independent fitness studios. The useful target might be an owner running a $1 million to $5 million studio with 10 to 30 employees, inconsistent lead flow, weak follow-up after trial classes, and a bad memory of money wasted on ads.
Now you can write for a real person.
"Five ways to grow your business" becomes "Why your fitness studio loses leads after the first trial class."
"Marketing tips for entrepreneurs" becomes "The follow-up sequence we would use to turn more fitness studio leads into members."
Specificity creates relevance. Relevance earns attention. Attention gives a strong idea the chance to travel.
The algorithm is downstream of human value
People talk about hacking the algorithm as if the platform is the audience.
It is not.
Recommendation systems are trying to predict what people will find valuable enough to keep consuming. TikTok publicly identifies interactions such as watching, liking, sharing, commenting, and searching as recommendation inputs. Meta describes Instagram systems that rank connected and unconnected content based on predicted relevance.
The mechanism is simple. If people scroll past, the system learns. If they stop, finish, replay, save, share, or respond, it learns something else.
The algorithm is not the source of value. It is the distribution layer reacting to value.
This gives content teams a better standard:
Would our ideal customer be glad this appeared in their feed?
The strongest content usually does at least one of four things:
- Teaches something unusually useful
- Gives language to a problem the customer already feels
- Changes how they see an important decision
- Provides a tool they can use immediately
"Define the role before you hire" is true and forgettable.
Showing the scorecard, the interview sequence, the five questions that expose a weak operator, and the difference between interviewing well and performing well gives the reader something to use. That is why they save it. That is why they send it to a cofounder.
Distribution follows the value created for a specific person.
Build a map of the customer's world
A strong content system begins before anyone writes a hook.
Map the customer's world:
- What are they trying to achieve?
- What keeps going wrong?
- What do they believe that is no longer true?
- What do they repeatedly ask?
- What are they embarrassed not to know?
- Which mistakes cost them the most?
- Which decisions feel hard to reverse?
- What would give them an immediate advantage?
These questions create better raw material than a blank content calendar.
Each answer is a hypothesis. Your audience may care about hiring, acquisition, pricing, operations, or the exact way another company solved the problem in front of them.
You will not know which idea becomes the outlier. That uncertainty is not a flaw in the system. It is the reason the system exists.
A winner is research
Most companies waste their best posts.
Something performs unusually well. The team celebrates, reports the number, and moves on to the next square on the calendar.
But a breakout piece is not just a result. It is information.
The market told you something. Your job is to find out what.
Was it the topic, hook, specificity, format, tension, timing, example, or practical value? Did the piece challenge a belief? Did it articulate something the audience already suspected but could not explain?
Once you understand the signal, mutate it.
A winning post about hiring can become a case study, checklist, teardown, founder story, visual framework, short video, long article, or interview. The point is not to repost the same idea forever. It is to explore the vein the winner exposed.
One outlier can reveal a year of useful content.
Volume creates more chances to learn
Volume matters because even excellent creators cannot reliably predict extreme winners.
They can improve the odds. They can understand the audience, sharpen the hook, strengthen the story, and study previous results. But timing, competition, culture, and the platform's first test audience still introduce uncertainty.
The rational response is to take more intelligent shots.
Not random shots. Informed experiments.
Most teams choose one side. They obsess over quality and publish too slowly, or chase volume until the work becomes generic.
The better system improves both:
- The value of each attempt
- The number of attempts
Volume cannot rescue weak ideas. Craft cannot learn from work that never ships.
The content loop
The operating loop is simple:
Understand → Create → Distribute → Measure → Learn → Mutate → Repeat
Understand the customer more deeply. Create something useful for them. Package it so they stop and consume it. Put it into the market. Measure the response. Find the abnormal winners. Study why they won. Turn those insights into the next experiments.
Then run the loop faster.
Over time, the company builds more than a library. It builds taste, customer understanding, and pattern recognition. It learns what its audience cannot ignore.
The real competitive advantage is not one viral post. Anyone can get lucky once.
The advantage is a machine that makes the next outlier easier to find.