Shopify Affiliate Program Statistics: What 1,178 Real Programs Tell Us in 2026

Most affiliate marketing statistics come from surveys, affiliate networks, or numbers that have been copied from one blog to another for years.

We wanted something more useful.

So we looked at actual affiliate activity across Shopify stores using Affilitrak: real programs, real affiliates, real referral visits, and real orders.

The dataset covers:

• 2,582 Shopify stores
• 8,695 affiliates
• 1,178 affiliate programs
• 12,532 referred orders

There are a lot of interesting numbers in there, but one stands out immediately:

Affiliate sales usually happen much faster than you might expect.

The typical store's referred order happened just 9.5 minutes after the affiliate referral visit.

That doesn't mean every customer buys immediately.

Some people click an affiliate link, leave the store, and come back days later. But the data suggests that when an affiliate sends someone who is actually going to buy, that purchase decision is usually made fairly quickly.

That has implications for how merchants recruit affiliates, evaluate new partners, think about attribution windows, and decide whether an affiliate program is actually working.

Data as of August 6, 2026.

Shopify affiliate program statistics at a glance

Here are the numbers that stood out most from the dataset:

• 9.5 minutes is the typical time between an affiliate referral visit and the resulting order, based on 47 stores with at least five attributable orders.
• 93.1% of affiliate programs on stores with real orders have never changed the default 30-day attribution window.
• 10% is the most common commission rate, applying to 4,243 of 8,695 affiliates.
• The typical store with enough commissioned orders had an actual commission rate of 10.0%.
• Higher commission rates were not associated with better affiliate performance across the programs we analyzed.
• 61.3% of affiliate programs have never generated a referred sale.
• Only about 16% of recruited affiliates ever make a sale.
• Among stores with at least two affiliates who have generated sales, the best-performing affiliate accounts for a typical 54.5% of referred orders.
• Instagram is the most common identifiable affiliate traffic source, appearing at 30 of 36 stores in our 200+ visit sample.
• Affiliate traffic is overwhelmingly mobile: 80% on average, with the typical store seeing 87% mobile traffic.
• Affiliates send 54.2% of referral visits to the homepage, compared with 37.2% to product pages.

The bigger story isn't any one of these numbers.

It's what they tell us about how affiliate programs actually behave.

1. Most affiliate sales happen within minutes

The typical store's affiliate sale happened 9.5 minutes after the referral visit.

That number comes from 47 stores with at least five attributable orders each.

The middle half of those stores fell between 5.7 and 32.3 minutes.

Looking at individual orders gives us an even clearer picture:

{
  "title": "When affiliate orders happen after a referral",
  "labelHeading": "Time after referral",
  "valueHeading": "Share of orders",
  "unit": "%",
  "max": 100,
  "data": [
    { "label": "Within 5 minutes", "value": 51.4 },
    { "label": "Within 1 hour", "value": 79.3 },
    { "label": "Within 24 hours", "value": 84.6 },
    { "label": "Within 7 days", "value": 89.4 },
    { "label": "Within 30 days", "value": 96.8 },
    { "label": "After 30 days", "value": 3.2 }
  ],
  "caption": "12,532 referred orders across the dataset. Timing could be reconstructed for 2,712 orders."
}

At first glance, you might expect affiliate purchases to gradually become less likely as more time passes.

The data doesn't really look like that.

Instead, there appear to be two different types of customers.

There is the person who clicks an affiliate link and buys almost immediately.

Then there is the person who clicks, leaves, thinks about it, and comes back days later.

The first group is much larger.

By 23 minutes, about three-quarters of the orders that can be measured have already happened.

But by the time we reach the 90th percentile, we're suddenly looking at customers who returned as much as 7.9 days later.

That distinction gets lost if you only look at an average.

What does this mean for merchants?

It makes the first few days of an affiliate's activity more informative than you might think.

If an affiliate is sending genuinely interested buyers, you will often see some evidence relatively quickly.

That doesn't mean you should remove an affiliate because they haven't generated a sale in 48 hours.

Affiliate performance depends on audience size, content schedule, traffic source, and what the affiliate is actually promoting.

But it does suggest that waiting months for an affiliate to eventually start working probably isn't a great strategy.

There is usually an early signal.

The better question is what you do with that signal.

If an affiliate joins your program but isn't getting any clicks, they may need better promotional material.

If they're getting clicks but no sales, they may have an audience-product mismatch.

If they're generating sales, you have a completely different problem: figuring out how to help that affiliate do more.

An important limitation

We could only calculate the exact time between a referral and an order when we could match the customer's checkout activity to the resulting order.

That was possible for 2,712 of 12,532 eligible referred orders, or 21.6%.

The other orders weren't necessarily less legitimate.

We simply couldn't reliably reconstruct the exact timing for them.

There are also customer journeys that this type of measurement can miss.

For example, someone might click an affiliate link on their phone and complete the purchase later on their laptop.

Those longer journeys are more difficult to track, so the actual median could be somewhat higher than 9.5 minutes.

The important takeaway is still clear:

A large share of affiliate purchases happen very close to the original referral.

2. Most merchants never change their 30-day attribution window

If you expected merchants to spend a lot of time adjusting their affiliate cookie duration, the data says otherwise.

93.1% of programs on stores with real orders have never changed the default 30-day attribution window.

That's 783 programs compared with only 54 that changed the setting.

Looking at all 1,178 programs with at least one affiliate, the number is even higher: 94.3% have left the default unchanged.

Among programs that did change their attribution window, 60 days and 90 days were the most common alternatives.

Interestingly, the 30-day default looks fairly sensible when we compare it with the actual order data.

If we look at what happens between day 7 and day 30, extending the attribution window captures roughly 7.4 additional percentage points of orders.

There are still some purchases after 30 days, but they represent only 3.2% of the attributable orders in this dataset.

So the lesson isn't that attribution windows don't matter.

It's that 30 days already captures the overwhelming majority of affiliate purchases we observed.

If you're choosing an attribution window for your own program, the right answer will depend on your sales cycle, product type, and customers.

But there's no obvious reason to assume that a much longer window is automatically better.

3. 10% is the most common affiliate commission rate

So what are Shopify merchants actually paying their affiliates?

For most merchants, the answer is 10%.

{
  "title": "The most common affiliate commission rates",
  "labelHeading": "Commission rate",
  "valueHeading": "Affiliates",
  "unit": "",
  "max": 4500,
  "data": [
    { "label": "10%", "value": 4243 },
    { "label": "15%", "value": 1171 },
    { "label": "0%", "value": 912 },
    { "label": "5%", "value": 585 },
    { "label": "30%", "value": 382 },
    { "label": "20%", "value": 366 },
    { "label": "25%", "value": 281 }
  ],
  "caption": "8,695 affiliates across 1,178 Shopify affiliate programs."
}

There's an important detail behind these numbers.

The commission rate isn't always individually assigned to each affiliate.

In fact, 59% of affiliates are paid according to a commission tier.

In other words, a merchant might have different groups of affiliates with different commission levels, rather than manually setting a rate for every person.

Looking only at stores with at least five commissioned orders, the typical actual commission rate was also 10%.

So 10% isn't just a software default that merchants leave untouched.

It's also the rate merchants commonly end up using in practice.

About half of the programs in the dataset use at least one commission rate that differs from the software default, and 228 programs use multiple commission rates.

The takeaway is pretty simple:

10% is a reasonable description of the current Shopify affiliate norm, but it isn't a universal rule.

Many merchants use different rates for different affiliates or tiers.

4. Higher commissions don't automatically produce better affiliates

This is probably one of the most interesting findings in the dataset.

You might assume that a merchant offering a 20% commission would naturally get better affiliate performance than one offering 5%.

But we couldn't find evidence that this is generally true.

We compared commission rates with how much affiliate sales each program was actually generating.

The result was essentially a flat line.

Programs paying higher commissions did not consistently generate more sales per affiliate than programs paying lower commissions.

We saw the same pattern when we looked only at programs where the commission rate actually varied.

In plain English:

There wasn't a meaningful connection between how much merchants paid and how well their affiliate programs performed.

That doesn't mean higher commissions are bad.

It also doesn't mean you should never increase your commission.

It means something more useful:

Commission rate alone doesn't appear to explain why some affiliate programs succeed and others don't.

If you're paying 10% and getting no sales, jumping to 20% might not solve the underlying problem.

You may have a recruitment problem.

You may have an activation problem.

Your affiliates may not have the right audience.

They may not know what to promote.

Or your store may simply not convert the traffic they're sending.

The commission affects your economics.

But based on this dataset, it doesn't appear to be the main reason some affiliate programs perform better than others.

5. Most affiliate programs never generate a sale

This is one of the numbers that changes how you should think about affiliate programs.

61.3% of programs with at least one affiliate have never generated a referred sale.

That's 722 out of 1,178 programs.

Only 456 stores in the dataset had generated at least one referred sale.

And even among those 456 stores, the results were heavily concentrated.

285 had only one affiliate who had ever generated a sale.

So the typical affiliate program isn't a healthy distribution of ten or twenty affiliates all contributing a little.

It's much closer to:

a lot of affiliates doing nothing, followed by one person doing most of the work.

That matters because an affiliate program isn't really "running" just because the software is installed and affiliates can sign up.

Recruitment is only the beginning.

The real progression looks more like:

signed up → activated → first click → first sale → repeat sales

The data suggests that most programs are losing affiliates somewhere along that journey.

That may be one of the biggest opportunities for merchants.

Instead of asking only: "How do I recruit more affiliates?"

It may be more useful to ask: "How do I get the affiliates I already recruited to make their first sale?"

6. One affiliate usually does most of the selling

The concentration becomes even clearer when we look at the best-performing affiliate in each store.

Among stores with at least two affiliates who had generated sales, the top affiliate accounted for a median 54.5% of referred orders.

{
  "title": "How concentrated affiliate sales are as programs grow",
  "columns": [
    "Selling affiliates",
    "Stores",
    "Top affiliate's share",
    "Compared with an even split"
  ],
  "rows": [
    ["2+", "171", "54.5%", "3.5×"],
    ["3+", "100", "44.6%", "4.3×"],
    ["5+", "53", "35.1%", "5.3×"],
    ["10+", "18", "26.4%", "8.4×"]
  ],
  "caption": "Among stores with at least the stated number of selling affiliates. The comparison shows how much larger the top affiliate's share is than an equal split among all selling affiliates."
}

Here's why that last comparison matters.

Imagine a store has 10 affiliates who generate sales.

If all 10 performed equally, each would generate about 10% of the orders.

Instead, the best affiliate accounts for a median 26.4%.

That's more than 8 times the share they'd have in an even distribution.

The same general pattern appears when we look at revenue rather than order count.

So this isn't simply one affiliate generating lots of cheap orders.

The concentration exists in the money being generated too.

What should merchants do with this?

Don't obsess over affiliate count.

Finding one genuinely strong affiliate can be much more valuable than adding ten average ones.

A program with 100 registered affiliates and two people generating sales may be less valuable than a program with 15 affiliates and three excellent ones.

Affiliate roster size is not the same thing as affiliate program health.

7. Affiliates that are going to sell usually show signs early

We also looked at how long it takes affiliates to generate their first sale.

Here's the data across 8,687 affiliates:

{
  "title": "How quickly affiliates make their first sale",
  "labelHeading": "Time since joining",
  "valueHeading": "Affiliates who had made a first sale",
  "unit": "%",
  "max": 20,
  "data": [
    { "label": "1 day", "value": 4.8 },
    { "label": "7 days", "value": 9.1 },
    { "label": "30 days", "value": 13.1 },
    { "label": "90 days", "value": 15.7 }
  ],
  "caption": "Share of 8,687 recruited affiliates who had generated at least one sale by each point after joining."
}

Eventually, only about 16% of recruited affiliates make a sale at all.

And that number stays remarkably consistent when we only look at affiliates who have been around long enough to have had the opportunity:

• all affiliates: 15.8%
• affiliates around for 30+ days: 16.6%
• affiliates around for 90+ days: 16.8%
• affiliates around for 180+ days: 16.4%

So this isn't simply a case of counting lots of brand-new affiliates who haven't had enough time.

Most affiliates really don't sell.

But among the affiliates who eventually do sell:

{
  "title": "When affiliates make their first sale",
  "labelHeading": "Time since joining",
  "valueHeading": "Share of eventual sellers",
  "unit": "%",
  "max": 100,
  "data": [
    { "label": "Within 1 day", "value": 28.9 },
    { "label": "Within 7 days", "value": 46.5 },
    { "label": "Within 30 days", "value": 69.8 },
    { "label": "Within 90 days", "value": 89.8 }
  ],
  "caption": "Percentages are calculated only among affiliates who eventually generated a sale."
}

There's an important distinction here.

Those percentages apply only to the affiliates who eventually make a sale.

They do not mean that 89.8% of all affiliates make a sale within 90 days.

The overall ceiling is only around 16%.

What does that tell us?

Put this together with the 9.5-minute median referral-to-order time and an interesting pattern appears.

Affiliates who are going to work often show signs fairly early.

That doesn't mean every good affiliate will generate a sale in their first week.

But the first week appears to contain a disproportionate amount of useful information.

If someone joins your program and does absolutely nothing for several weeks, simply waiting longer probably isn't the best strategy.

Give them something to promote.

Help them choose a product.

Give them content they can use.

Show them which products are selling.

Ask whether they actually have an audience that fits your store.

The program needs an activation process, not just a signup form.

8. Instagram is the biggest affiliate traffic source

We also looked at where affiliate referral traffic actually comes from.

The analysis covers stores with at least 100 referral visits during the measurement period.

The average share of referral visits looked like this:

{
  "title": "Where affiliate referral traffic comes from",
  "labelHeading": "Traffic source",
  "valueHeading": "Share of referral visits",
  "unit": "%",
  "max": 100,
  "data": [
    { "label": "Instagram", "value": 28.8 },
    { "label": "No identifiable referrer", "value": 25.5 },
    { "label": "YouTube", "value": 15 },
    { "label": "Facebook", "value": 14 },
    { "label": "Other websites", "value": 11 },
    { "label": "TikTok", "value": 2 },
    { "label": "X", "value": 2 }
  ],
  "caption": "Store-weighted averages from stores with at least 100 affiliate referral visits."
}

Instagram appeared at 30 of 36 stores in the 200+ visit sample.

That's what makes it particularly interesting.

YouTube has a meaningful average share, but its traffic is much more concentrated. Some stores get a lot of YouTube traffic while most get very little.

Instagram appears much more consistently across the dataset.

A surprising amount of affiliate traffic has no identifiable source

The second-largest category is traffic with no identifiable referrer.

It accounts for around 25.5% of affiliate referral visits on average.

That can include things like:

• DMs
• Group chats
• Link-in-bio traffic
• Direct link sharing
• Private communities
• Other situations where the original source isn't passed through

This is easy to underestimate because analytics software can't always tell you where the person originally came from.

But it isn't a tiny edge case.

For many affiliate programs, a meaningful amount of traffic is happening in places where traditional referral analytics can't identify the original source.

TikTok isn't dominating this dataset

TikTok gets a huge amount of attention in affiliate marketing.

But in this dataset, it represented only around 2% of referral visits on average.

That doesn't mean TikTok doesn't work.

It means the average across these Shopify programs doesn't support the idea that TikTok is the dominant affiliate channel.

The right channel will depend heavily on the affiliate, the product, and the audience.

9. Affiliate traffic is overwhelmingly mobile

This one is hard to miss.

Affiliate referral traffic is overwhelmingly mobile.

Here's the data:

{
  "title": "Affiliate referral traffic is mostly mobile",
  "labelHeading": "Device",
  "valueHeading": "Share of referral traffic",
  "unit": "%",
  "max": 100,
  "data": [
    { "label": "Mobile", "value": 80.0 },
    { "label": "Desktop", "value": 16.4 }
  ],
  "caption": "Store-weighted average across the analyzed Shopify stores."
}

The typical store was even more mobile-heavy:

• 87.0% mobile
• 8.5% desktop

That has a very practical implication.

Your affiliate program might be managed from a desktop computer.

Your affiliates might create their content on laptops.

Your merchant dashboard might be desktop-first.

But the people clicking those affiliate links are overwhelmingly using phones.

So your affiliate landing experience is a mobile experience.

That means things like:

• page speed
• mobile navigation
• product-page clarity
• checkout friction
• how quickly the offer is visible
• whether the affiliate's link takes someone to the right place

can all affect affiliate performance.

Mobile optimization isn't just a general Shopify best practice here.

It's part of affiliate optimization.

10. Affiliates usually send people to the homepage

Here's another result that surprised us.

You might expect affiliates to send traffic directly to the product they're recommending.

Instead, the majority of affiliate referral visits land on the store's homepage.

Here's the data across 63 stores:

{
  "title": "Where affiliates send their visitors",
  "labelHeading": "Landing page",
  "valueHeading": "Share of referral visits",
  "unit": "%",
  "max": 100,
  "data": [
    { "label": "Home page", "value": 54.2 },
    { "label": "Product page", "value": 37.2 },
    { "label": "Collection page", "value": 6 },
    { "label": "Content / blog", "value": 0.8 }
  ],
  "caption": "Average share across 63 Shopify stores."
}

More than half of affiliate traffic goes to the homepage.

That isn't necessarily wrong.

If an affiliate is introducing someone to an entire brand, the homepage can make sense.

But if an affiliate is recommending a specific product, sending someone to a generic homepage adds another step between the recommendation and the product they were interested in buying.

There is also an interesting signal in the checkout data.

Collection pages started checkout for 8.2% of visits, compared with 5.0% for homepages and 4.5% for product pages in this dataset.

The sample isn't large enough to turn those numbers into universal conversion benchmarks.

But the ordering is interesting.

It suggests that merchants should test where affiliate traffic lands rather than assuming the homepage is always the best destination.

For example, an affiliate recommending "the best skincare products for dry skin" may be better served by a relevant skincare collection than by the store's homepage.

What the data says about running an affiliate program

The individual statistics are interesting.

The combination is more useful.

Three patterns show up repeatedly.

1. Most affiliates won't sell

Only about 16% of recruited affiliates ever generate a sale.

That means recruitment volume by itself isn't a good measure of program health.

You need to identify the affiliates who are actually capable of producing results.

2. Affiliates who work tend to show signs early

Nearly half of eventual sellers make their first sale within seven days.

Combined with the short time between referral and purchase, that suggests the early stage of an affiliate relationship is unusually informative.

The first week shouldn't be passive.

It's an opportunity for merchants to help affiliates get activated.

3. The best affiliate matters a lot

Most stores don't have a perfectly balanced affiliate roster.

One or two affiliates often account for a large share of the results.

That means the objective shouldn't necessarily be "Get as many affiliates as possible."

It should be "Find affiliates who can actually reach the right customers, then help those affiliates succeed."

That's a very different approach to affiliate program management.

What about commission rates?

The data gives merchants a useful reality check here too.

10% is clearly common.

But paying more doesn't automatically produce more sales.

That doesn't mean merchants should always pay 10%.

It means you shouldn't assume that commission rate is the first lever to pull when your program isn't working.

If you have 50 affiliates and zero sales, increasing the commission from 10% to 20% doesn't fix the fact that those affiliates aren't sending buyers.

The bigger questions are:

• Are you recruiting the right people?
• Are they actually promoting you?
• Do they know what to promote?
• Are you helping them get their first sale?
• Does the traffic they're sending match your product?
• Does your store convert the traffic they're sending?

Those questions are much closer to the actual bottleneck.

Methodology

This analysis covers 2,582 merchant stores after removing app-owner accounts and 140 Shopify Partner development stores.

The development stores were excluded because they contained 5,413 test-pattern referred orders, which would materially distort the results.

Of the remaining stores:

• 1,337 have at least one paid Shopify order
• 1,178 have at least one affiliate
• 456 have generated at least one referred sale

How we calculated "typical store" numbers

When we describe a "typical store," we give every store equal weight.

That means a small store with 10 orders counts just as much as a large store with 10,000 orders.

We do this because otherwise a handful of very large merchants can dominate the results.

For example, one large merchant accounts for 51% of referral visits and 19% of orders in the combined dataset.

Where we use all orders or visits together, we use those numbers to describe the overall dataset rather than what a typical merchant experiences.

Referral visits

Referral visits are deduplicated by store, affiliate code, visitor, and 24-hour period.

They should therefore be thought of as visitor-days rather than raw clicks.

Click-to-order timing

The click-to-order analysis requires us to match a checkout-start event to the resulting order.

That was possible for 2,712 of 12,532 eligible referred orders, or 21.6%.

Because of this limitation, we don't publish a conventional affiliate conversion rate from this dataset.

Doing so would understate the true rate.

Instead, we use the timing data and checkout-start data where the underlying information is reliable enough to support a useful comparison.

Comparing commission rates and performance

We also tested whether programs paying higher commissions tended to generate more orders per affiliate.

The answer was essentially no meaningful relationship.

We used a statistical test designed for data like this because affiliate performance varies enormously between programs.

Some affiliates generate hundreds of orders while others generate none.

The technical result was close enough to zero that there was no meaningful evidence of a relationship between commission rate and affiliate performance.

For readers interested in the technical details, the analysis covered 471 programs and included a 95% confidence range around the result.

The important takeaway for everyone else is simply:

"Higher commission rates did not consistently translate into better affiliate performance in this dataset."

What we learned from 1,178 Shopify affiliate programs

If you only take one thing from this analysis, it shouldn't be that the ideal commission is 10%.

And it shouldn't be that Instagram is the best affiliate channel.

The bigger lesson is about activation.

Most programs already have affiliates.

They just don't have affiliates who are selling.

Most affiliates don't ever make a sale.

And when affiliates do start selling, they often show evidence relatively early.

That changes the job of running an affiliate program.

The goal isn't simply to recruit more people and wait.

It's to:

Find the right affiliates → get them active → help them make their first sale → identify the ones who work → help those affiliates sell more.

The data also gives merchants some useful benchmarks along the way:

• 10% is a common commission rate.
• 30 days is a common attribution window and captures almost all referred orders.
• 80%+ mobile traffic means the affiliate experience needs to work exceptionally well on phones.
• One affiliate can account for a surprisingly large share of your results, even as your program grows.
• Only around 16% of recruited affiliates ever generate a sale, making affiliate activation just as important as recruitment.

We're going to keep updating these numbers as more Shopify stores run affiliate programs through Affilitrak.

If you're running an affiliate program and want to see how your own numbers compare, Affilitrak is free to install and gives you the tracking needed to see exactly which affiliates, links, and referrals are producing sales.

Start free with Affilitrak.