My Subscriber Count Grew. My Open Rate Fell From 34% to 18%.

Across my first nine articles, later posts clustered between 18% and 23% while my subscriber count continued climbing. A bigger list did not automatically create a more engaged audience.

The Truth About My Substack Growth — Part 2 of 5

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Subscriber count told me I was growing.

Open rate told me to slow down.

Neither number told the whole truth.

I went from zero to more than 150 subscribers during my first week on Substack.

By the time of this audit, the publication had reached 241 subscribers.

From the outside, the direction was obvious:

More subscribers meant more growth.

But after auditing the Notes responsible for that growth, I looked at what happened after people subscribed.

The result was less flattering.

On August 3, one of my articles recorded a 34% open rate.

Ten days later, my newest article recorded 18%.

My Substack Posts dashboard, August 20. Nine articles published August 1–13, open rates as recorded — the 34% peak and the 18% latest are circled.

That is a decline of 16 percentage points—or roughly 47% relative to the earlier rate.

My list was getting bigger.

The percentage of it opening my new articles was getting smaller.

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The pattern across my first nine articles

The decline did not happen in a perfectly straight line.

These were the recorded open rates:

Open rate per article, August 1–13. Each point is a different article, not the same reader cohort over time.

The 34% result was the high point, not the permanent baseline.

But the later pattern is still difficult to ignore.

Every article published after August 5 recorded an open rate between 18% and 21%.

Meanwhile, the subscriber count continued rising.

The list was expanding faster than reader attention.

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A falling open rate does not automatically mean fewer readers

This distinction matters.

A percentage can fall while the absolute number of readers still rises.

For example:

• 100 subscribers at a 34% open rate means 34 opens.

• 200 subscribers at an 18% open rate means 36 opens.

The second list has a much weaker rate but slightly more total readers.

So I cannot honestly say that my audience disappeared simply because the percentage declined.

A larger list can still create more reach.

The problem is efficiency.

I needed almost twice as many subscribers to produce roughly the same number of opens.

That means subscriber growth and audience growth are not always the same thing.

One measures how many people joined.

The other measures how many people continue paying attention.

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The explanation I cannot prove—but cannot ignore

The most obvious explanation is acquisition quality.

In Part 1, I found that the two strongest networking Notes accounted for 56 of the 62 subscribers Substack attributed to individual Notes.

One explicitly offered reciprocal support.

The other told writers I was reading, subscribing and supporting them.

Both generated subscribers quickly.

But someone who subscribes because they expect support in return is not necessarily subscribing because they want my next article.

When the next email arrives, the original reason for subscribing matters.

Did they join because they wanted:

• Substack growth experiments?

• data and practical tactics?

• updates about building Subshack?

• or simply another subscriber in return?

Those motivations all produce the same +1 in the subscriber count.

They do not produce the same reading behaviour afterward.

The falling open rate is consistent with audience dilution.

But it does not prove that reciprocal growth caused it.

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What the data cannot tell me

This audit covers only nine articles from a publication that was a few weeks old.

The articles also had different:

• titles

• subjects

• publication dates

• levels of relevance

• amounts of promotion

The 34% article discussed why subscribe-for-subscribe was not really win-win.

The 18% article documented my first Substack Chat experiment.

The difference in subject alone may explain part of the gap.

I also do not have a clean cohort analysis showing:

• which acquisition source produced each reader

• whether reciprocal subscribers opened less often

• whether organically acquired subscribers returned more frequently

• how engagement changed for the same subscribers over time

So the accurate conclusion is not:

Reciprocal subscribers caused my open rate to fall.

It is:

My subscriber count increased while the open rates on later articles remained materially below my early high points. Reciprocal acquisition is one plausible explanation, but the available data cannot isolate the cause.

That sentence is less dramatic.

It is also more honest.

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The subscriber count hides different types of growth

Before this audit, I treated every new subscriber as an identical unit of growth.

Now I see at least three different possibilities.

Transactional growth

Someone subscribes because I subscribed, replied or offered support first.

Community growth

Someone subscribes because we interacted, share the same experience or belong to the same creator network.

Editorial growth

Someone subscribes because the content itself created enough interest for them to want the next piece.

All three subscribers are real people.

All three may eventually become genuine readers.

But their original motivation is different.

A dashboard that combines them into one number cannot explain why the list grows while the open rate weakens.

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What I should have measured from the beginning

Subscriber count is still useful.

It just needs context.

I should have tracked it alongside:

• article open rate

• total views

• comments and replies

• restacks

• returning readers

• unsubscribes after each publication

• the mechanism that produced each subscriber

The most important question is no longer:

How many subscribers did this tactic produce?

It is:

What did those subscribers do after joining?

Did they open the next article?

Did they read a second one?

Did they reply without expecting anything in return?

Did they share the work with their own audience?

That behaviour is much closer to audience growth than the initial subscription.

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What I am changing now

I am not deleting reciprocal subscribers or pretending the early growth never happened.

The raw numbers remain part of the story.

But I am changing what I allow those numbers to teach me.

A networking Note can be excellent for meeting creators.

It should not automatically become evidence that the subject of the Note created editorial demand.

A reciprocal subscription can begin a real relationship.

It should not automatically carry the same weight as someone who subscribed after reading an article.

And a growing list should not be celebrated without checking whether people continue opening the work.

For the next articles, I am watching both sides:

• acquisition: who subscribes and why

• retention: who returns and continues reading

Growth needs both.

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The uncomfortable conclusion

My publication reached 241 subscribers quickly.

That achievement is real.

But the open-rate pattern suggests that the list may have grown faster than the audience’s interest in my work.

I did not necessarily build a smaller audience.

I may have built a larger audience with weaker average intent.

That is not the same failure.

But it requires a different strategy.

The goal is no longer to make the subscriber count rise as quickly as possible.

The goal is to make the next subscriber more likely to become a reader.

That starts before the subscription, on the profile they land on. I built a free Substack profile audit that scores what a first-time visitor sees, out of 100.

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If your subscriber count doubled while your open rate nearly halved, would you still call it growth?

Would you prefer a smaller, highly engaged list—or a larger list that produces more total reach but weaker average engagement?

Tell me which one you would choose in the comments.

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Next in Part 3: How I taught Subshack to distinguish organic, community-driven and reciprocal growth—after the first version classified my own article as reciprocal content.