Almost Half My Attention Clicks Came From Just 20 Visitors

Small group of repeat visitors generating a large share of advertising engagement

My experiment recorded 143 attention clicks.

But they didn’t come from 143 different people.

They came from 94 distinct tracked visitors.

And just 20 of those visitors generated 69 of the clicks.

Almost half.

That was the final surprise in my Safelist Attention Project.


Most People Clicked Once. A Small Group Kept Clicking.

Throughout this experiment, I used a persistent browser cookie to identify returning visitors.

That doesn’t guarantee every visitor ID represents a completely separate physical person. Someone using another browser or device could receive another ID.

But it gave me a reasonable way to distinguish between a tracked browser appearing once and one coming back later.

Out of 7,380 distinct tracked visitor IDs, only 94 ever clicked the attention button.

Of those 94:

Clicker TypeTracked ClickersAttention ClicksShare of Clicks
Clicked once747451.7%
Clicked on multiple visits206948.3%
Total94143100%

That’s the number that really changed how I looked at the experiment.

74 tracked visitors clicked once and generated 74 clicks.

20 repeat clickers generated 69 clicks.

Nearly the same number of clicks.

From dramatically different numbers of people.


That Small Group Was Really Small

Those 20 repeat clickers represented only 21.3% of the people who clicked at all.

Yet they generated 48.3% of every attention click I recorded.

Put against the entire experiment, the number gets even more surprising.

There were 7,380 distinct tracked visitor IDs.

Only 20 became repeat clickers.

That’s about 0.27% of all tracked visitors.

Now, I want to be careful with that number.

I’m not saying 0.27% of the audience created half the value of the campaign.

They didn’t.

This experiment measured one very specific thing: whether somebody deliberately clicked the button telling me they had noticed the page.

What the number shows is much narrower—and still interesting:

A very small group generated a surprisingly large share of the measured interaction.


Repeat Clicking Usually Meant More Than One Extra Click

At first, I wondered if “repeat clicker” mostly meant somebody saw the experiment twice and clicked both times.

That did happen.

But it wasn’t the whole story.

Of the 20 repeat clickers:

  • 9 clicked twice
  • 11 clicked three or more times
  • several clicked four, five, or six times
  • one tracked visitor clicked on eight separate visits

So more than half of the repeat-clicker group interacted at least three times.

And the result wasn’t being distorted by one extreme visitor.

The most active tracked visitor produced eight clicks.

The remaining repeat clicks were spread across a small group that kept interacting when they encountered the experiment again.

Why?

I don’t know.

Maybe they recognized the experiment.

Maybe they enjoyed participating.

Maybe the page became familiar.

Maybe they remembered the unusual image.

Maybe they simply thought, “There’s Jerry’s experiment again. I’ll click the button.”

The experiment never asked them why they clicked again, so I don’t want to invent an explanation.

The safest conclusion is simply this:

The same tracked visitors remained willing to deliberately interact on later visits.


Most Returning Visitors Still Never Clicked

There’s another number that keeps all of this in perspective.

In my previous post, How Many Times Did People See My Ad Before They Clicked?, I looked at when people first responded.

There were 288 tracked visitors who appeared more than once during the experiment.

But returning did not automatically mean engaging.

Of those 288 repeat visitors:

  • 247 never clicked
  • 21 clicked on exactly one visit
  • 20 clicked on multiple visits

So only 6.9% of all returning visitors became repeat clickers.

That’s important.

I don’t want to look at these numbers and say:

“Just keep showing people the same ad and they’ll eventually become highly engaged.”

The data doesn’t say that.

Most returners still never clicked.

What happened instead was that a relatively small subgroup behaved very differently from everybody else.


Ten Clicks Can Tell Two Completely Different Stories

This may be the most useful lesson I’ve taken from this final part of the experiment.

Imagine two campaigns.

Campaign A gets 10 clicks from 10 different people.

Campaign B gets 10 clicks from three people who keep returning and interacting.

If you’re only looking at the click counter, both campaigns say:

10 clicks.

But those numbers are telling very different stories.

Campaign A shows more breadth.

Campaign B shows more repeat engagement.

Which would I rather have?

That depends on what I’m trying to accomplish.

If I’m looking for new leads, I’d probably be more interested in reaching more different people.

If I’m trying to build recognition or familiarity, repeat interaction may also be useful.

And if I’m trying to make sales?

Then neither number tells me enough.

I’d want actual conversion data.

That’s something this experiment has kept reminding me:

The value of a metric depends on what you’re trying to learn from it.


Different Safelists Produced Different Patterns

This also helped explain something I had noticed earlier in the project.

Not every safelist produced the same kind of attention.

Mister Safelist generated 14 attention clicks from 14 different tracked visitors.

That’s broad participation.

SendCircle produced 32 clicks from 20 tracked clickers, including five repeat clickers who generated 17 clicks between them.

My Daily Mailer showed a similar mix: 30 clicks from 19 tracked clickers, with five repeat clickers generating 16 clicks.

Then there were sources such as Zodiac Mailer, where eight clicks came from two tracked visitors who both interacted repeatedly.

I don’t look at those patterns as better or worse.

They’re different.

One source may produce broader participation.

Another may produce stronger repeat engagement from a smaller responsive group.

The important thing is that the total click number by itself doesn’t show the difference.


Why I Want Two Numbers From Now On

Before this experiment, if somebody told me an ad received 100 clicks, my first instinct would probably be to compare that number with another source that received 80 or 120.

Now I want another number sitting beside it:

How many different tracked visitors produced those clicks?

Because:

100 clicks from 100 people tells me one story.

100 clicks from 50 people tells me another.

100 clicks from 20 people tells me something else entirely.

None of those outcomes is automatically good or bad.

But without knowing both total clicks and unique clickers, I don’t really know what kind of response I’m looking at.

That’s a lesson I can use far beyond safelists.

The same idea could matter with email, content marketing, recurring advertising, social media, or anywhere else people can interact with something more than once.


One More Interesting Connection To The Eyes

There was one other result I couldn’t help noticing.

Earlier in this series, I looked at what people said made them notice the experiment page.

The eyes in the image barely won among people’s first responses.

But among the 29 additional follow-up answers submitted by repeat respondents, 21 selected the eyes.

That doesn’t prove the eyes caused repeat engagement.

It doesn’t even prove they were the reason somebody remembered the page.

But it does make me wonder whether that visual became especially recognizable once people had seen the experiment before.

Maybe the creative wasn’t only noticeable.

Maybe, for some people, it became familiar.

That’s something I’d have to test separately.


What This Doesn’t Prove

There are a few important limits to these results.

The visitor IDs were cookie-based, so they represent tracked browsers rather than guaranteed individual human identities.

A repeat click does not equal a new lead, a sale, or stronger buying intent.

The experiment didn’t ask people why they clicked again.

Visitors weren’t randomly assigned a certain number of exposures.

And this wasn’t a normal sales page.

The page openly told people they were part of an experiment and asked them to click a button if they noticed it.

Someone who returned later may simply have recognized the page and remembered what I was asking them to do.

That’s still deliberate interaction.

But I wouldn’t assume a commercial offer would produce exactly the same behavior.


What This Whole Experiment Changed For Me

When I started this project back in July, I really thought I was going to find out which safelists were best at getting attention.

I did learn quite a bit about the safelists.

But that wasn’t the most interesting part.

I learned that traffic and attention aren’t the same thing.

I learned there can be more than one kind of winner, depending on what I measure.

I learned that people notice different things.

I learned that some people don’t respond the first time they see an ad.

And now I’ve learned that even after people do respond, the attention itself isn’t necessarily spread evenly.

Some of it was broad.

Some of it came from repeat engagement.

Some visitors never responded at all.

And a very small group generated a surprisingly large share of the visible activity.

I started with a traffic question.

I ended up with a measurement lesson.

The number on the counter is only the beginning of the story.

From now on, if I see that an ad got 100 clicks, I don’t think I’m going to be satisfied with knowing there were 100 clicks.

I’m going to want to know one more thing:

Who produced them?

That’s probably the biggest lesson I’m taking away from the Safelist Attention Project.

Don’t just count the clicks. Understand who is producing them.

And with that, I’m going to call this the final core article in this experiment.

I’ve gotten far more out of that strange little page than I expected when I started sending it through safelists in July.

I’m not finished experimenting, though.

So now I’d like to turn the next one over to you.

If I run another marketing attention experiment, what would you like me to test?

Different headlines?

Different images?

Short emails versus long emails?

Curiosity versus benefits?

A plain page versus a designed page?

Whether attention actually predicts conversions?

Leave me a comment and let me know.

Your idea might become my next experiment.

Thanks for following along,

Jerry

I Tested 45 Safelists: Which Ones Sent Visitors Who Actually Paid Attention?

45 safelists tested to determine which visitors deliberately paid attention.

Hello!

For the first half of July, I sent the same unusual page through 45 different safelists.

It wasn’t a sales page.

There was no product to buy, no form to fill out, and no promise of making money.

Instead, the page told visitors that they had become part of a safelist experiment and asked them to click one simple button:

“Yes… I Noticed This Page”

Safelist attention experiment page with the “Yes, I Noticed This Page” button.
The page used for the Safelist Attention Project. Visitors were asked to confirm that they had deliberately noticed it.

That was the entire point of the test.

I wasn’t simply trying to find out which safelists could generate the most page loads. I wanted to know which ones sent visitors who were present enough to notice what was in front of them and deliberately respond.

After 8,433 visits, the experiment recorded 389 confirmed submissions.

I expected the safelists that sent the most traffic to produce the most attention.

That isn’t what happened.

The results showed something I have suspected for a long time:

Traffic and attention are not the same thing.

A traffic counter can tell us that a page loaded. It cannot tell us whether the person on the other side actually noticed it.

That is what the Safelist Attention Project was designed to explore.

Why I Ran the Safelist Attention Project

I have been using safelists for more than 20 years.

During that time, I have published plenty of safelist rankings and traffic reports. Those reports can be useful. They show which sites are active, how much traffic they send, and sometimes which ones produce sign-ups or sales.

My Best Safelist Rankings for 2025 followed that more traditional approach.

The problem is that a normal traffic counter can only tell me that a page loaded.

It cannot tell me whether anybody was mentally present.

The page may have opened in a background tab. Someone may have been clicking through several messages at once. The visitor may have waited for a timer, collected a reward, and moved on without really processing the page.

That does not necessarily mean the visit had no value.

Repeated visibility, branding, familiarity, and future recognition can all matter. Someone may notice an offer today and respond to it weeks later.

But I wanted to measure something more deliberate.

Earlier this year, I ran a very simple safelist experiment that asked visitors to click a button simply to show that they had participated.

The response made me curious about what else this kind of test might reveal.

This time, instead of looking only at the experiment as a whole, I wanted to compare the safelists themselves.

Which sites would send the most traffic?

Which would produce the highest percentage of deliberate interactions?

Would the same platforms lead both lists?

What Counted as Attention?

I used the same email, landing page, button, and tracking rules for every safelist.

The source code in the URL was the only intentional campaign difference.

The page did not sell anything.

There was no opt-in form, payment button, affiliate offer, or long sales presentation.

Visitors were told that they had become part of an experiment. The main action on the page was the button:

“Yes… I Noticed This Page”

Clicking that button was what I counted as an attention click.

After clicking, visitors were asked what had made them notice the page. That gave me a second layer of information that I will explore in another article.

Each safelist received its own tracking code. The system recorded the source, visit, visitor ID, session, timestamp, click, and follow-up answer.

A new visit was recorded each time the page loaded. Refreshing the page created another visit.

A persistent browser cookie was used to recognize returning visitors. That allowed me to separate total clicks from distinct tracked visitors who clicked.

This distinction is important:

Total clicks measure deliberate interactions.

Unique clickers measure how many distinct tracked browsers or visitor IDs interacted.

The unique counts do not guarantee that every ID represents a different physical person. Someone using two devices could receive two IDs. Two people sharing a browser could share one.

Still, it gives us a much better view than treating every page load as a completely different person.

I also chose not to use time on page as the main signal.

A safelist page can remain open while someone is doing something else. A deliberate button click is not perfect proof of deep concentration, but it does show that the visitor saw enough of the page to understand the request and respond.

This was a structured real-world marketing experiment, not a laboratory-controlled scientific study.

The goal was to create a consistent comparison under normal safelist advertising conditions.

The Experiment by the Numbers

From July 1 through July 15, 2026, I logged 391 submission records across 45 safelists.

The experiment recorded 8,433 raw page visits.

Here is the overall picture:

MeasurementResult
Safelists with confirmed sends45
Confirmed submissions389
Raw recorded visits8,433
Final analyzed visits8,392
Distinct tracked visitors7,380
Attention clicks143
Distinct tracked clickers94
Follow-up answers105
Overall attention rate1.70%

In other words, 1.70% of the analyzed visits produced a deliberate click on the attention button.

That percentage may look small, but remember what was being measured.

These were not ordinary clicks from an email to a website.

Everyone included in the visit count had already opened the email and reached the experiment page. The button measured whether they noticed and deliberately interacted with what they found there.

The Safelists That Stood Out

I used a minimum of 100 final analyzed visits for the main leaderboard.

The table below shows the qualifying platforms that stood out most clearly during this experiment.

The “Clicks” column shows total deliberate interactions. The number in parentheses shows distinct tracked clickers.

RankSafelistVisitsClicks (Unique)Attention Rate
1SendCircle17432 (20)18.39%
2Zodiac Mailer1278 (2)6.30%
3My Daily Mailer1,00530 (19)2.99%
4Click Leverage34210 (8)2.92%
5List Avail1043 (3)2.88%
6Fast List Mailer2385 (4)2.10%
7Mister Safelist66814 (14)2.10%

SendCircle Was the Clear Attention Winner

SendCircle’s result was in a category of its own.

It produced:

  • 174 analyzed visits
  • 32 attention clicks
  • 20 distinct tracked clickers
  • an 18.39% attention rate

SendCircle provided only about 2.1% of all analyzed visits, but it produced approximately 22.4% of all attention clicks.

That is a large difference.

It also was not a case of one visitor repeatedly clicking and inflating the total.

Fifteen of SendCircle’s tracked clickers clicked once.

Five returned and clicked during additional visits. Those five repeat visitors produced 17 clicks between them, but no single visitor clicked more than five times.

Repeat engagement contributed to the result, but the response was spread across enough different visitors to make it meaningful.

Under this particular experiment, SendCircle was the unmistakable attention leader.

That does not mean it will outperform every safelist with every offer.

It means its visitors responded exceptionally well to this email, page, and request during this test.

My Daily Mailer Combined Reach With Attention

My Daily Mailer produced one of the best combinations of traffic volume and deliberate interaction.

It sent 1,005 analyzed visits, making it one of the largest traffic sources in the experiment.

Those visits produced:

  • 30 attention clicks
  • 19 distinct tracked clickers
  • a 2.99% attention rate

My Daily Mailer generated almost as many total attention clicks as SendCircle while working with a much larger audience.

Its percentage was nowhere near SendCircle’s, but that is exactly why volume and rate need to be viewed together.

A high response rate from a modest traffic source and a solid response rate from a high-volume source are two different kinds of success.

My Daily Mailer showed that it could deliver substantial reach without losing the ability to generate deliberate interaction.

Full disclosure: I own My Daily Mailer and Mister Safelist. Members of those sites may already be familiar with me, my writing, or the way my pages look, and that familiarity could have influenced how quickly they recognized and interacted with the experiment.

I included both sites because they were part of the same tracked test, but that possible familiarity effect is worth keeping in mind when reading the results.

Click Leverage Was a Strong Independent Performer

Click Leverage delivered 342 analyzed visits and produced 10 attention clicks from eight distinct tracked visitors.

Its attention rate was 2.92%.

That placed it very close to My Daily Mailer and List Avail on a per-visit basis.

It delivered a healthy sample, a competitive attention rate, and clicks spread across several different tracked visitors.

I would consider it one of the strongest all-around independent performers in the experiment.

Mister Safelist Produced Broad Unique Attention

Mister Safelist generated 14 attention clicks from 668 analyzed visits.

Its 2.10% rate looks modest next to SendCircle, but there is something important inside that number:

All 14 clicks came from different tracked visitors.

There were no repeat clickers driving Mister Safelist’s total.

My Daily Mailer produced more total attention, while Mister Safelist spread its attention across a broader set of unique visitors without relying on repeat participation.

Again, these are different kinds of performance.

One platform generated more total interaction.

The other provided a very clean example of broad unique response.

Zodiac Mailer Shows Why Unique Clickers Matter

Zodiac Mailer had the second-highest raw attention rate in the table:

  • 127 analyzed visits
  • 8 attention clicks
  • 2 distinct tracked clickers
  • a 6.30% attention rate

At first glance, that percentage looks like a clear second-place finish.

The unique-clicker count changes the interpretation.

All eight clicks came from two tracked visitors. One of them clicked during six separate visits.

I do not think that result should be hidden or disqualified.

The original measurement counted legitimate attention clicks per visit, and those visitors repeatedly noticed and interacted with the experiment.

That is real repeat engagement.

It is simply not the same thing as receiving eight clicks from eight different visitors.

The positive interpretation is that Zodiac Mailer produced unusually strong repeat attention from a small number of highly responsive people.

More data would be needed before concluding that the result represents its wider audience.

List Avail and Fast List Mailer

List Avail just cleared the 100-visit qualification threshold with 104 analyzed visits.

It produced three clicks from three different tracked visitors, giving it a 2.88% attention rate.

That is a promising result, although the smaller sample means that a few additional visits or clicks could change the percentage quickly.

Fast List Mailer delivered a larger sample of 238 visits and generated five clicks from four tracked visitors.

Its exact attention rate was 2.1008%.

Neither platform should be overinterpreted from one experiment, but both earned a place among the more interesting results.

There Was More Than One Way to Perform Well

This experiment did not produce one universal definition of “best.”

It revealed several different strengths:

SendCircle: Highest attention rate and strongest overall response

My Daily Mailer: Strong combination of high volume and substantial attention

Click Leverage: Strong independent balance of sample size and response

Mister Safelist: Broad unique attention with no repeat clickers

Zodiac Mailer: Strong repeat engagement from a small responsive group

List Avail: Promising attention rate at the qualification threshold

A normal traffic ranking would mostly reward the platforms that delivered the most page loads.

An attention ranking tells a different story.

The biggest traffic source does not automatically produce the highest response rate.

The highest response rate does not automatically represent the broadest audience.

The platform with the most unique clickers does not necessarily produce the most total interactions.

Each measurement describes something slightly different.

What the Rankings Really Show

The central lesson is not that traffic volume is unimportant.

Without traffic, there is nobody available to notice the page.

The lesson is that traffic and attention are not interchangeable.

One safelist can send a large audience and create valuable reach.

Another can send fewer visitors but have a higher percentage of them deliberately engage.

A third may create repeated exposure that causes the same visitors to notice the message more than once.

That is why I have become less interested in traffic numbers by themselves.

As I wrote in Most People Don’t Need More Traffic, traffic often acts as an amplifier.

Sending more visitors does not automatically fix a page or message that people ignore.

The way an idea is presented still matters.

The same audience can react very differently to a different headline, image, email, or call to action.

The Safelist Attention Project gives us another way to look at that problem.

It does not just ask:

“How many visitors arrived?”

It asks:

“How many were present enough to respond?”

What Made People Notice the Page?

After visitors clicked the attention button, I asked them what had caught their attention.

There were 105 recorded answers.

The eyes image was the most frequently selected response, followed by the overall page design and the headline.

That is interesting, but it needs its own article.

Repeat visitors could answer during more than one visit, so the total answers and the number of distinct respondents are not the same.

I will examine that part of the experiment separately rather than squeezing a second study into this report.

For now, the important point is that the page itself mattered.

The safelist delivered the visitor, but the message and design still had to earn the interaction.

What These Rankings Do Not Prove

This experiment measured one specific kind of deliberate interaction.

It did not measure:

  • sales
  • opt-ins
  • long-term customer value
  • affiliate referrals
  • brand recognition over time
  • whether someone returned days later through another route

The results also apply to one subject line, one email, one landing page, one visual approach, one call to action, and one period in July 2026.

A different offer could produce a different ranking.

I also used my existing safelist accounts.

Those accounts did not all have identical membership levels, mailing intervals, or potential audience reach. That affects how much traffic each safelist could deliver.

The attention-rate comparison helps separate interaction quality from raw volume, but differences in membership privileges and audience composition still matter.

Small samples can also create unstable percentages, which is why I required at least 100 final analyzed visits for the main table.

Finally, a platform that did not stand out under this particular experiment may still provide value through reach, repetition, branding, delivery speed, or better performance with a different type of offer.

This is not a list of good safelists and bad safelists.

It is a record of what happened when I asked 45 safelists to send visitors to the same attention test.

Safelist Traffic Kept Arriving After I Stopped Mailing

My final confirmed submission was sent on July 15.

I left the experiment open so I could see how long traffic continued to arrive.

A full week later, on July 22, the page still received 22 human-likely visits after identifiable automated activity was removed.

Two of those visitors clicked the attention button.

One came through SendCircle.

The other came through List Avail.

That means the final day was not simply crawler traffic or leftover technical checks.

Real visits and deliberate interaction were still happening seven days after the last mailing.

I will look more closely at the delayed traffic in another article because it raises an interesting question:

How long does a safelist mailing continue producing exposure after it leaves the newest-message area?

Final Thoughts

I started this experiment expecting the largest traffic sources to dominate.

Instead, SendCircle delivered the clearest example of why traffic volume and attention quality need to be measured separately.

My Daily Mailer showed the value of combining reach with response.

Click Leverage delivered a strong independent result.

Mister Safelist demonstrated broad unique participation.

Zodiac Mailer showed how repeat engagement can create a very different kind of attention.

No single number tells the entire story.

That may be the most useful finding of all.

This experiment did not prove which safelist is universally the best.

It showed which platforms stood out when all 45 were asked to send visitors to the same page using the same email, button, and tracking rules.

There is still plenty left to examine.

In the next parts of this series, I will look more closely at traffic volume versus attention, what visitors said made them notice the page, repeat participation, how long safelist traffic continues after mailing stops, and the differences between My Daily Mailer and Mister Safelist.

In the meantime, I would like to hear from you.

Do these results match what you have seen in your own safelist advertising—and what would you like me to test next?

Thanks for reading,

Jerry

P.S. If you are working on your own safelist campaigns, the most important thing you can do is track more than raw hits. My free Safelist Marketing Tactics guide explains the practical side of creating, testing, and improving your campaigns.

How I Track My Safelist Marketing Results (Without Losing My Mind)

Man analyzing safelist ad tracking stats for better performance

One of the most common questions I get is how I track which safelists are working for me.

It’s a good question—because with so many safelists out there, and dozens of emails flying every day, it’s easy to get overwhelmed. For years, I just kind of guessed which sites were performing based on the occasional burst of traffic or a random signup. But guessing isn’t tracking, and I eventually realized I needed a more reliable system.

Now, I want to be clear: I don’t claim to be the ultimate expert on tracking stats. I’ve just found a method that works well for me, and maybe it’ll help you too.


What I Actually Track (And Why)

I focus on conversions first. That’s what matters most. A conversion means someone saw my ad and actually took action—usually joining my list. That’s the ultimate goal.

After that, I look at response rate, which tells me how many people clicked through to my site after reading my email. I use LeadsLeap for this, and I love how it gives me both the raw clicks and the engagement data.

Lastly, I consider total traffic, but only after I know the other numbers. Just sending a flood of visitors doesn’t mean much if nobody’s taking action.


My Tracking Habits

I’m a bit of a stat junkie—I check conversions throughout the day. Not obsessively, but yeah, I like to see if anything’s working.

But I only do a deep dive once a month. That’s when I review which safelists and which ads actually brought results. It gives me a solid 30-day view that smooths out the ups and downs of daily fluctuations.


What I Look For in a “Bad” Ad

Not every ad is going to be a winner. If one of my emails gets lower conversions and lower click-throughs than others, that’s usually a sign it’s time to retire it—or at least rework it.

I don’t throw everything out. Sometimes, I’ll rotate older ads back in just to see if they still perform. Some of them surprise me.


What Makes a “Good” Test

I try to test different ads across the same safelists. That way I can isolate the variable. Was it the ad that underperformed—or was it the safelist?

Still, it’s tough to get clean data. Safelist traffic tends to be up and down, and mailing schedules aren’t always consistent. That’s why I try to track over the long haul, not just after a few days.


Final Thoughts

You don’t need to be a data nerd to track your results. You just need a system that helps you see what’s working and what’s not.

I’m still refining my own process all the time. But the more I track, the more I learn—and the easier it is to make smart decisions with my time and my traffic.

If you’re new to safelist marketing or want to learn how I turned safelists into one of my most consistent traffic sources, check out this post:
Why Most Safelist Marketers Fail (And How to Do It Right)