Incrementality in Affiliate Marketing: A 2025 Complete Guide to Measure ROI

Have you ever asked yourself how many affiliate sales were truly incremental and how many were just converting from your organic traffic? This is what makes the concept of incrementality in affiliate marketing fascinating in 2025.

With the global affiliate marketing industry worth around $37.3 billion and marketers seeing an average ROI of $12 for every $1 spent, understanding incrementality in marketing is not just interesting; it’s essential to measuring true impact.

In this blog, you will learn what incrementality is in marketing, why incrementality in marketing matters, the real-world complexities of tracking it, and actionable ways to measure and optimize it.

You will see how Trackier helps in providing the smarter incremental insights, allowing you to push for greater incremental growth. Let’s get started in learning how to measure, optimize, and profit through incrementality in marketing.

What is Incrementality in Affiliate Marketing?

Incrementality in affiliate marketing refers to the additional value, or conversion, that happens only because of an affiliate, as it would not have happened without that affiliate. This means not only counting clicks and attributed sales, but understanding the net new impact as well.

In a more expansive marketing context, incrementality in marketing describes growth specifically due to efforts, while filtering out what is not just organic or baseline brand lift. 

So, when we use the term “incremental marketing,” we are talking about strategies that create results beyond the usual or expected growth.

Ask yourself: What does incrementality in marketing mean as relates to your affiliate strategy? For some, this may mean new customer acquisition, while for others the term may relate to bigger order values, first‐time email sign‐ups, etc. Clearly defining this is the first step in the entire process.

Why Incrementality Matters in Affiliate Marketing?

Tracking metrics such as last-click conversions or ROAS is tempting but misleading. When you focus on incrementality in marketing, you reveal the net new value of an affiliate, giving a new axis of decision-making for data-informed marketing strategies.

Here is why it matters more, especially now:

A. Neutralize Attribution Bias and Inflated ROI

Traditional attribution models, be it last-click, first-click, or multi-touch, can’t delineate the customers you should have gained, versus actual customers gained with incrementality. This often results in inflated performance numbers and wasted expenditures.

The benefit of incrementality testing is that it can determine the real-life effect of your affiliate program channels through contrasting control vs. exposed groups to show the underlying lift.

B. Budget Optimization

As per the Gartner report, sixty-four percent of CMOs do not have enough budget to deliver fully on their marketing strategies. Incrementality helps identify which affiliate relationships actually create incremental growth so that you can allocate spend appropriately.

Incrementality in marketing monitoring allows you to make decisions based on return on investment rather than just putting spend in channels that may just replicate demand or patterns of behaviour.

C. Improved Partner Accountability & Fairness

In traditional attribution, some affiliates get credit just by being the last touch attribution, even if they did not meaningfully contribute to the transaction. 

By measuring incrementality, you ensure your work is fair and accountable; instead of rewarding partners just for being causal, you reward partners based on their actual incremental value that contributes to incremental growth.

This added transparency will provide better alignment, connection, trust, and sustainability of partnerships.

D. New Growth Discovery

Affiliate content, usually, such as evergreen blog titles, reviews, or video content, will continue to create revenue long after they are published. 

However, traditional analytics systems do not typically recognize this impact, there is a lag effect, or it is not regarded as “evergreen”.

Incrementality in marketing will allow you to measure and recognize the significant contribution of affiliate assets.

Incremental vs. Non-Incremental: What is the Difference?

Understanding the difference between incremental and non-incremental affiliate conversions can make or break your strategy and budget efficiency. We can explore this concept further in detail.

What is Non-Incremental and Why Can It Hide the Truth?

Non-incremental conversions are those sales you would have gotten anyway, without the affiliate’s influence. They are valuable conversions, but most often hide the opportunity to spend dollars more wisely.

Example: Cashback Browser Extensions

A loyal customer who was already planning to make a purchase and has a cashback extension engaged at checkout. 

Technically speaking, the affiliate extension gets credit for the conversion, but this does not create a new sale.

That sale has still occurred without the affiliate nudging it. This is just a non-incremental sale disguised as performance.

What Defines True Incrementality in Marketing?

Next, consider the incremental conversions; the conversion inspired, influenced, or triggered by your affiliate partners.

Example: Coupon Sites Driving New Customers

According to Lodestar Marketing, coupon-driven purchases are 57% more likely to be new users, and the average order value (AOV) is 14% higher on purchases with coupons. 

Most of the coupon referrals are full-price buyers. This is a clear incremental lift, new customers bringing new revenue. Such results are a true sign of incremental growth in affiliate programs.

Example: Unique Conversions – Not All Sales Are Created Equal

An example from impact illustrates this: imagine two affiliates, Affiliate A and Affiliate B, each accounting for $93,840 in incremental sales. 

However, affiliates drive more new customer revenue, which translates to better long-term value.

This layer of visibility about your partners changes everything about how you evaluate them, and the commission models, too.

Real-World Impact: Affiliate Channel Beyond Just Conversions

Affiliate channels often deliver more than immediate sales; they can shape brand perception, engagement, and lifetime value.

Example: Gen3 & Commission Junction Study – A comprehensive study found that shoppers interacting with affiliates exhibited:

• 46% higher shopper-to-customer conversion
• 29% higher spend per customer
• 88% higher revenue per customer

Which Affiliate Types Drive More Incrementality in Marketing?

Every affiliate doesn’t contribute to real growth at the same level. Some affiliates create new customers, while others just get customers who were already heading their way to buy. 

Knowing which affiliates provide real value and why will help you create affiliate programs that are a true ROI strategy. Let’s illustrate with examples, data, and actionable takeaways.

1. Content Affiliates (Blogs, Review Sites, Niche Publishers)

These affiliates are storytellers. They present your brand to new audiences who inherit trust for their authors (the affiliates), and ultimately have the power to influence purchase decisions.

So why do they work:

• They drive discovery traffic.
• They build SEO through quality backlinks.
• They educate and resonate with readers on a deeper level, laying the foundation for incremental growth.

Pro tip: Consider hybrid payouts like a flat fee for content creation, but bonus compensation for new-user signups. Long-form in-depth reviews can work particularly well with niche readers.

2. Review and Comparison Websites

This type of site captures customers in the process of comparing options. They won’t necessarily recommend new traffic, but if you’re thinking of someone very close to buying, they often convert those people.

Why they work:

• Act as the “last push” before someone buys.
• Fit nicely with content affiliates for a full-funnel strategy.

Pro tip: If you’re not careful, it can be easy to get duped into thinking that they’re actually driving new sales through holdout tests or layered attribution when they may just be taking credit originally.

3. Coupon & Deal Affiliates

Many discount coupons are considered low-value, but research shows they appeal to a much higher % of new users (57% coupon buyer = new user), and they actually spend more (14% more per order), and they convert at twice the rate as average shoppers.

Why they work:

• Appeal to shoppers who are price-obsessed and maybe wouldn’t buy.
• Provides a trial purchase where long-term loyalty may become a reality.

Tactical:

• Minimum spend coupon play (e.g. $10 off $75). One test almost doubled AOV, and the increase in revenue was 30%.
• Share codes with new customer restrictions to be confident you are acquiring new buyers.

4. Loyalty & Cashback Affiliates

While often not great for new acquisition, they’re perfect for maintaining engagement and actively bringing back lapsed customers.

Best for:

• Recovering lapsed customers.
• Assisting with large sales campaigns.

Optimization tip: Create a tiered payout, normal commission on standard purchases, but additionally pay out on reactivations or first-time repeat purchases.

5. Influencers & Sub-Affiliate Networks

Influencers are strong in categories of beauty, fashion, and lifestyle. In fact, on Cyber Monday 2024, influencers created 20% of all e-commerce revenue, and affiliate-linked products were 6x more likely to convert. 

Why do they work?

• Authentic, real-time recommendations.
• Strong emotional connection to followers.
• UGC builds trust and visibility. 

Pro-Tip: Start with micro-influencers (10K–100K followers). They typically drive greater engagement and create more genuine conversions. Additionally, test micro-influencers by comparing similar audiences, with and without influencer contact.

6. Email & Newsletter Affiliates

These affiliates send your offers directly to people who want to hear the offers; as a result, conversions can be good. Affiliate email campaigns usually see about a 2% conversion rate and outperform many other broader campaigns.

How to get the most?

• Provide segmented deals for new users.
• Provide early bird or exclusive access to create urgency.

7. PPC & Search Affiliates

These affiliates run ads and generate clicks through affiliate links. They can increase volume quickly, but sometimes they can compete with your own paid campaigns.

How to stay protected?

• Do not allow them to bid on your brand keywords.
• Monitor overlaps and incrementality closely.

How to Measure Incrementality in Affiliate Marketing?

When it comes to measuring incrementality in affiliate marketing, it’s not sufficient to run a test or look at how many clicks an affiliate sent your way; what you really want to know is what value affiliates bring to your business.

With global affiliate marketing advertiser spending reaching $15.7 billion in 2024 (up from $14 billion in 2023), and the total industry valued at $18.5 billion globally, knowing which conversions were completed because of affiliates and which would’ve happened anyway is critical.

Marketers can go beyond metrics and rely on actionable, data-driven insights into ROI by using a straightforward and consistent step-by-step approach.

Step 1 — Define What Incrementality Will Mean for Your Test

Why does this matter? If your team does not have an agreement on what is “incremental,” your results will not mean anything to you.

Decide on what you’re measuring (one or more):

• New customer signups or first purchase
• Revenue that would not have happened without affiliates
• An increase in average order value (AOV) or lifetime value (LTV) from affiliate customers
• More signups, or subscriptions

Action checklist:

• Write down a simple one-liner: “Incremental = first-time orders that only happened because of affiliate X.”
• Select the KPI, period of time (for example, 30 days or 90 days), and unit of measurement (orders, revenue, LTV).

Trackier tip: Label your measured metric, for example, “incremental_test_v1” in your campaign URLs. Later, you can filter your results quickly. (SmartLinks + custom fields/parameters in Trackier makes doing this very simple.)

Step 2 — Make Sure Your Data & Tracking Setup Is Right

Why it matters: A messy data set ruins your whole test.

What to do:

• Confirm your tracking setup: ensure S2S events, pixels/webhooks, and order mappings run perfectly from start to finish.
• Confirm deduplication rules (both web + server) and have cookie-less backups set up.
• Confirm you can report breakdowns by affiliate, geo, and device type.

Quick tests:

• Try a test conversion and see if it ends up in your Trackier dashboard and your BI tool.
• Check if your affiliate IDs, order values, and customer type (new vs returning) are registered correctly.

Trackier tip: Use Trackier’s S2S integrations and SmartLink setup to get reliable attribution for your promotional efforts and to reduce dropouts from the client side.

Step 3 – Choose Measurement Method (primary + backups)

Why this is important: Each method has its own costs, speed, and accuracy trade-offs. Select your primary method (pick one):

• Hold-out / Randomized Control (gold standard): Turn off or withhold affiliate exposure for a random group and compare the results. Gives the clearest “cause-and-effect” story.

• Geo / Matched-Market Test: Run the program in similar geos (Group A = exposed, Group B = control). A very solid option when you can’t randomize users.

• Predictive / Causal Modeling: Use some kind of regression, MMM, or AI tools, if you need ongoing measurement or can’t run large experiments.

Back-up checks (always do these):

• Multi-touch attribution
• Cohort analysis

Pro tip: If you run a randomized hold-out test, do it; it sidesteps a lot of the assumptions of modelling.

Step 4 – Design Your Experiment (Sample Size, Split, Timing)

Why this matters: A poorly designed test = Untrustworthy results. 

Design rules: 

• Randomize where you can, at the user or session level.
• Run the test long enough to encompass full buying cycles + seasonality. 
• For most e-commerce, 2 – 6 weeks to test is fine.
• For longer funnels (e.g., B2B, high-ticket, etc.), probably a 6 – 12 week timeframe is better. 
• Use an A/B testing calculator to calculate sample size. 
• What you’ll need to know: baseline conversion rate, minimum detectable effect (MDE), power (80%), alpha (0.05). 

Example flow: 

• Baseline conversion = 1.5% 
• We want to detect a 20% lift (1.8% vs 1.5%)
• Insert numbers into the calculator → you’ll get the visitors needed per group.

Trackier tip: Use SmartLink + campaign tags to vertically split audiences cleanly, and capture exactly the data needed for analysis.

Step 5 — Conducting the Experiment (Operational Checklist)

The Importance: Even if done well, poor testing execution can eliminate the value of the best design.

Operational tasks:

• Have a stable condition: Avoid major marketing changes during the test (no big promotions or paid media changes).

• Control group management: Ensure that affiliates in the control group are paused or routed to a neutral link.

• Log everything: Note the start date/time, test groups, sample sizes, and any unusual activity.

Capture necessary data: Orders, revenue, average order value (AOV), new vs. returning customers, device type, and geography.

Step 6 — Analyze results with statistical rigor (but keep it simple)

Why: Don’t confuse random noise with a real win, dig in and make sure the growth is real.

Core numbers to compute: Absolute incremental lift (percentage points) = Conversion rate (test) − Conversion rate (control)

Example:

• Control conv. rate = 1.50%
• Test conv. rate = 2.10%
• Absolute lift = 2.10% − 1.50% = 0.60 percentage points.
• Compute (digit-by-digit): 2.10 − 1.50 = 0.60.
• Relative lift (%) = (ConvRate_test − ConvRate_control) ÷ ConvRate_control × 100

Example (using the numbers above):

• Relative lift = 0.60 ÷ 1.50 = 0.40 → 0.40 × 100 = 40%.
• Compute: 0.60 ÷ 1.50 = 0.4 → 0.4 × 100 = 40%.

Statistical checks (keep these non-negotiable):

• Aim for p ≤ 0.05 (i.e., ~95% confidence).
• Report confidence intervals (CI) for the lift and for absolute counts (incremental conversions, incremental revenue). If the CI includes zero, the lift may not be real.

Incremental ROAS:

• Incremental revenue = revenue_test − revenue_control
• Incremental ROAS = incremental_revenue ÷ incremental_spend

Example:

• Incremental revenue = $15,000
• Incremental spend = $3,000
• Incremental ROAS = 15,000 ÷ 3,000 = 5.00 (5x).
• Compute step-by-step: 15,000 ÷ 3,000 = 5.

Quick checklist before you act:

• Is the lift statistically significant (p ≤ 0.05 and CI excludes 0)?
• Where did the lift come from: more conversions, higher AOV, or more new customers?
• Is the incremental ROAS profitable?
• If yes to the above, scale carefully and keep monitoring.

Trackier tip: Export test vs control cohorts from Trackier, then visualize lift across revenue, AOV, and new-customer rates so you can see where the gains are coming from.

Step 7 — Validate with modeling & attribution

Why: Experiments are not perfect (and can be a little noisy), so you can use modeling to help validate things and get a broader perspective. 

What to do:

• Use some sort of regression or causal model (time series, difference in difference, CausalImpact, etc.) to estimate what your baseline would have been, and compare it with your actual results.

• Compare any multi-touch attribution results with your experimental results for any overlap or signs of cannibalization.

Pro tip: If both your models and experiments agree in terms of direction (or causal inferences), you can be more confident in your results and either do so quicker if scaling up.

Common Challenges in Measuring Incrementality

Finding incrementality in affiliate marketing is awesome value, but it isn’t always easy. Let’s identify the major challenges marketers encounter, in addition to some of the tangible insights and data that highlight why this is a difficult (but necessary) pursuit.

1. Platform bias and exaggerated results

Platforms will rarely let us know the last time they found any kind of incrementality testing that didn’t result in a clear-cut success.

Research has shown that traditional attribution methods often lead to inflated lift measurements due to selection bias and methodological flaws in comparing exposed versus unexposed users. 

When advertisers don’t use proper randomized controlled trials, they may observe higher conversion rates among exposed users simply because targeting algorithms naturally show ads to high-intent consumers. 

This creates attribution bias, but it stems from measurement methodology issues rather than intentional manipulation by platforms like Facebook and Google.

Bottom line: Don’t take platform-reported data at face value; always look for external validation.

2. External Factors Interfering with Results

Even well-designed tests can be disrupted by uncontrollable external variables.

• Traditional observational methods can inflate estimated conversion lifts by as much as 6x because they lack any method of accounting for external factors such as the economy or events happening locally.

• Geo-based tests are particularly susceptible, competitor promotions, cultural fluctuations, or even weather events that could affect your results.

The main point to remember is: look at the context, not just the test results in isolation.

3. Operational Challenges with RCTs and Holdouts

RCTs (Randomized Controlled Trials) look great in theory; not so much in practice.

• Inherently discoverable affiliates make it difficult to split audiences into a test group and a control group.

• Holdouts on geographical controls don’t work either. States or countries have different media habits, are differently brand-present, or have different consumer behavior, making it impossible to compare apples to apples.

Marketers often find ways to shift these approaches mid-test in order to make them work.

4. Pausing Acquisitions Causes Disruption 

Incrementality tests usually require you to pause your normal campaigns. 

• This pause in normal activity is disruptive to your short-term revenue, slows growth, and creates challenges for your team and affiliate partners.

• Where tests should boost performance in reality can stall momentum.

Smart testing should create less disruption, not hinder your progress.

5. Short-Term Thinking vs. Long-Term Value

Most incrementality tests measure net short-term gains and miss the long haul.

• They rarely measure brand-building, customer loyalty, or word-of-mouth effects.

• 80% of CMOs are dissatisfied with their ability to measure marketing performance, and 64% of marketing leaders find demonstrating marketing impact on financial outcomes challenging.

6. Lack of Tools and Blended Data

Additionally, while many marketers genuinely want to measure incrementality, most do not have the structural resources to do it.

• 41% of respondents said that they do not have the right tools or technology to measure it correctly.

• 35% said there’s not even a clear definition of the term “incrementality”.

• In fact, the vast majority of affiliate tracking software further hinders measurement by keeping data in silos and duplicating data, complicating getting a holistic view of the customer across channels.

Without the right tools and integrated data, measuring incrementality is one big challenge.

Conclusion

Understanding incrementality in marketing isn’t optional; it’s a must for affiliates and marketers alike. As we’ve seen, measuring the real impact of your affiliate partnerships goes beyond just tracking clicks or sales.

It’s about figuring out which conversions truly happen because of your affiliates, and which would have happened anyway.

Key takeaways:

• Incrementality shows real impact: Knowing the true contribution of your affiliates helps you spend your marketing budget wisely and achieve sustainable incremental growth.

• Data-driven decisions boost ROI: Running proper incrementality tests helps you make smarter choices, improving your overall results.

• Keep checking regularly: The affiliate space keeps changing. Monitoring incremental value ensures you stay ahead and competitive.

Next steps for marketers:

• Test for incrementality: Regularly check how much impact your affiliates really have with Trackier’s marketing analytics.

• Know the data: Understand which affiliates are driving real value.

• Optimize partnerships: Focus on top performers and rethink relationships with those underperforming.

• Use smart tools: Trackier can help track data, measure impact accurately, and give insights to grow your incremental results.

Taking these steps ensures your affiliate marketing is not just working, but working efficiently, driving real growth you can measure.

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