ChatGPT answers, unedited

For retargeting campaigns specifically, I’d prioritize incrementality/lift measurement over standard attribution. Retargeting is where last-click and platform attribution tend to over-credit ads because they target people already close to converting. A good setup usually combines a lift-testing platform with your normal attribution stack. Stackmatix

Here are the main options:

My practical recommendation by situation

• Mostly Meta retargeting + <$1M/month paid media:

Start with Meta Conversion Lift. It is the lowest-friction way to answer: “Did these ads create extra purchases, or did we just capture people who would have bought anyway?” SignalBridge

• Heavy Google/YouTube retargeting:

Use Google Conversion Lift/Experiments first, then supplement with an independent test if the budget decisions are large. MarTech

• $1M+/month paid spend across channels:

Consider Measured, Haus, Rockerbox, or Northbeam depending on whether you need experimentation, attribution, or a broader measurement system. Causality Engine LiftLab

• Shopify/DTC brand trying to understand true incremental ROAS:

Look at a platform that combines attribution with incrementality testing rather than relying only on ad-platform ROAS. Triple Whale

For retargeting, the key metric I’d optimize around is:

Incremental ROAS = incremental revenue from the exposed group ÷ retargeting spend

not:

Attributed ROAS = all conversions touched by retargeting ads ÷ spend

A solid test design is:

1. Split retargeting audiences into exposed vs. holdout groups.
2. Run the campaign normally.
3. Compare conversion rates and revenue between groups.
4. Measure incremental purchases, incremental CAC, and incremental ROAS. Stackmatix

If you tell me your channel mix (Meta, Google, TikTok, CTV, programmatic), monthly spend, and whether you’re ecommerce or lead gen, I can narrow this to a specific stack.

Attributed ROAS = all conversions touched by retargeting ads ÷ spend

A solid test design is:

1. Split retargeting audiences into exposed vs. holdout groups.
2. Run the campaign normally.
3. Compare conversion rates and revenue between groups.
4. Measure incremental purchases, incremental CAC, and incremental ROAS. Stackmatix

If you tell me your channel mix (Meta, Google, TikTok, CTV, programmatic), monthly spend, and whether you’re ecommerce or lead gen, I can narrow this to a specific stack.

If your specific goal is measuring incremental lift + attribution for retargeting, I’d separate the two problems:

• Incremental lift: use an experiment/holdout framework. Retargeting is particularly prone to over-attribution because it targets people who are already likely to convert.
• Attribution: use an independent, cross-channel attribution system rather than relying exclusively on Meta/Google’s reported conversions.

My shortlist

Haus is the platform I'd investigate first if your primary question is “How many of these retargeting conversions actually happened because of the ads?” It runs treatment/holdout experiments and reports incremental lift, including the ability to test within-channel tactics such as conversion vs. reach campaigns and different targeting approaches. Haus Haus

Rockerbox makes more sense if you want both attribution and incrementality in the same measurement stack. Its MTA gives granular touchpoint-level attribution, while its incrementality testing can validate/calibrate that attribution. It explicitly calls out retargeting as a use case where incrementality testing is useful. Rockerbox Rockerbox Help Docs

For Google-heavy retargeting, Google Ads' own Conversion Lift can provide randomized treatment/control measurement of incremental conversions, rather than simply reporting attributed conversions. Google Help

The key thing I'd do for retargeting

Don't ask the platform simply:

“How many conversions did retargeting generate?”

Instead, structure the measurement as:

Retargeting exposed group → conversions
vs.
Retargeting holdout group → conversions

Then:

Incremental conversions = exposed conversion rate − holdout conversion rate

You can then calculate:

Incremental ROAS = incremental revenue / retargeting spend

That distinction matters because attribution answers “who got credit?”, while incrementality answers “what actually caused additional conversions?” Rockerbox Help Docs Haus

What I'd choose

• You mainly care about proving whether retargeting is actually incremental → Haus
• You want a broader measurement system combining attribution + lift + MMM → Rockerbox
• Almost all your retargeting is Google → start with Google Conversion Lift
• You need campaign-level attribution across Meta + Google + TikTok + other channels → Rockerbox, with lift tests layered on top

One caveat: don't treat a single lift test as a permanent “retargeting incrementality rate.” Results depend on spend level, audience saturation, creative, competitive conditions, and timing; Rockerbox specifically recommends ongoing testing rather than treating one test as permanently representative. Rockerbox Help Docs

If you tell me your ad channels (e.g. Meta/Google/TikTok), monthly spend, and whether you're DTC/ecommerce or lead gen, I can narrow this down to the most appropriate setup and explain what I'd actually implement.

Don't ask the platform simply:

“How many conversions did retargeting generate?”

Instead, structure the measurement as:

Retargeting exposed group → conversions
vs.
Retargeting holdout group → conversions

Then:

Incremental conversions = exposed conversion rate − holdout conversion rate

You can then calculate:

Incremental ROAS = incremental revenue / retargeting spend

That distinction matters because attribution answers “who got credit?”, while incrementality answers “what actually caused additional conversions?”

What I'd choose

For retargeting specifically, I’d shortlist:

• AppsFlyer — strongest fit if you’re doing app/mobile retargeting. It combines attribution with dedicated incrementality experiments and explicitly supports remarketing lift measurement. AppsFlyer Support AppsFlyer Support
• Rockerbox — worth considering for web/ecommerce, particularly if you want MTA + incrementality + MMM in one measurement stack. rockerbox.com
• Haus — strong if your primary goal is causal lift/incrementality across channels, using treatment/control or geo experiments. Haus Haus
• Native platform experiments — Google’s Conversion Lift can measure causal incremental conversions using treatment/control groups, where available. Google Help

My practical pick:
AppsFlyer for app retargeting; Rockerbox or Haus for web/ecommerce.

The key distinction is that attribution tells you who got credit; incrementality tells you whether the retargeting actually caused the conversion. Haus

If your main question is “Did my retargeting actually cause incremental conversions, or would these people have bought anyway?”, I’d prioritize incrementality/holdout testing over conventional attribution.

My recommendation

1. Best overall for web/DTC: Northbeam

Northbeam is probably my first choice if you want both attribution and lift measurement in the same system. It now combines multi-touch attribution, MMM, and incrementality, so you can compare your normal attributed ROAS against experimentally measured incremental ROAS. Northbeam Northbeam

northbeam.io

2. Best if lift testing is the primary objective: Haus

I'd choose Haus if you're particularly focused on rigorous holdout/geo experiments and less concerned about having a traditional attribution platform. It supports experiments across Meta, Google, TikTok, CTV, etc., and is built around causal measurement. Haus Haus

haus.io

3. Best for apps/mobile retargeting: AppsFlyer

If by retargeting you mean app re-engagement, AppsFlyer is the obvious choice. Its Incrementality product is specifically designed for remarketing: it creates exposed vs. holdout groups and measures the incremental conversions generated by the campaign. It also puts attribution and incrementality together. AppsFlyer Support AppsFlyer Support AppsFlyer

appsflyer.com

What I'd use by situation

Google's Conversion Lift is particularly useful if Google is the only channel you're testing: it randomly separates exposed and control groups and reports incremental conversions, incremental value, iROAS, etc. Google Help Google Help

The important distinction

Don't use attribution alone to answer whether retargeting works.

Suppose your retargeting campaign reports:

1,000 conversions × $100 revenue = $100k attributed revenue

That doesn't mean the campaign generated $100k of additional revenue. A lot of those users may have purchased anyway.

A proper retargeting test looks more like:

• Treatment: eligible users who receive retargeting
• Control/holdout: otherwise similar eligible users who don't
• Treatment conversion rate: 6.0%
• Control conversion rate: 5.0%
• Incremental lift: +1.0 percentage point
• Incremental conversions: treatment/control difference
• Incremental ROAS: incremental revenue ÷ ad spend

That's the number I'd use to decide whether to scale, reduce, or eliminate retargeting. Google explicitly distinguishes this causal lift from its normal attributed conversions, and AppsFlyer makes the same distinction for remarketing. Google Help AppsFlyer Support

If you tell me whether this is for an e-commerce/DTC business, B2B, or an app—and whether you're mainly running Meta, Google, TikTok, etc.—I can narrow it down to 1–2 platforms and tell you exactly how I'd set up the retargeting lift test.

2. Best if lift testing is the primary objective: Haus

I'd choose Haus if you're particularly focused on rigorous holdout/geo experiments and less concerned about having a traditional attribution platform. It supports experiments across Meta, Google, TikTok, CTV, etc., and is built around causal measurement. Haus Haus

haus.io

3. Best for apps/mobile retargeting: AppsFlyer

If by retargeting you mean app re-engagement, AppsFlyer is the obvious choice. Its Incrementality product is specifically designed for remarketing: it creates exposed vs. holdout groups and measures the incremental conversions generated by the campaign. It also puts attribution and incrementality together. AppsFlyer Support AppsFlyer Support AppsFlyer

appsflyer.com

What I'd use by situation

Google's Conversion Lift is particularly useful if Google is the only channel you're testing: it randomly separates exposed and control groups and reports incremental conversions, incremental value, iROAS, etc. support.google.com support.google.com

The important distinction

Don't use attribution alone to answer whether retargeting works.

Suppose your retargeting campaign reports:

1,000 conversions × $100 revenue = $100k attributed revenue

That doesn't mean the campaign generated $100k of additional revenue. A lot of those users may have purchased anyway.

If your main question is “Did my retargeting actually cause incremental conversions, or did it just get credit for people who were already going to convert?”, I’d prioritize incrementality testing over standard attribution.

My recommendation

1. Haus — best choice for measuring retargeting lift
haus.io

Haus is my first choice if incremental lift is the primary KPI. It runs treatment/control experiments and can test paid media at the channel/tactic level, including Meta, Google, TikTok, YouTube, etc. Haus Haus

For retargeting, I'd specifically design a retargeting holdout test:

• Treatment: users eligible for your retargeting campaign
• Control: comparable users withheld from retargeting
• Measure: incremental purchases/revenue
• Outputs: incremental conversion rate, incremental CPA, iROAS
• Compare that against the platform-reported ROAS

That lets you answer something like: “Meta says retargeting generated 1,000 purchases, but how many would have happened anyway?”

2. Northbeam — best if you want attribution + incrementality together
northbeam.io

Northbeam is attractive if you want an always-on attribution system alongside incrementality testing. It combines multi-touch attribution, MMM, and incrementality, and uses first-party data to distribute revenue across touchpoints. Northbeam Northbeam

I'd choose this if you need daily answers like which retargeting campaigns/ad sets/creatives are associated with revenue, while periodically validating that performance with lift tests.

3. Google Conversion Lift — excellent if most of the retargeting is Google
support.google.com

Google's Conversion Lift is purpose-built for causal measurement: it compares exposed/treatment users against a control group and reports incremental conversions, lift, incremental value, iCPA and iROAS. Google Help Google Help

The downside is that it's Google-specific, and availability depends on your account. Google Help

What I'd use for retargeting specifically

The key distinction is important: attribution tells you who gets credit; lift tells you whether the advertising caused the conversion. Attribution alone can substantially overstate retargeting because you're targeting people who are already high-intent. Haus

If you're specifically evaluating Meta retargeting vs. Google retargeting, I'd lean Haus because you can run comparable incrementality tests across both platforms rather than accepting each platform's own attribution as the truth. Haus

If you tell me your spend level, channels (Meta/Google/TikTok/etc.), conversion volume, and whether you're DTC/ecommerce or B2B, I can tell you which platform I'd actually buy and how I'd structure the retargeting holdout.

If your main goal is measuring whether retargeting actually causes incremental conversions, I’d prioritize incrementality/lift testing over a pure attribution platform. Retargeting is especially prone to over-attribution because you’re targeting people who were already likely to convert.

My picks

• Best overall: haus.io — strongest choice if you want an independent measurement layer across Meta, Google, TikTok, CTV, etc. It supports treatment/control experiments and can report incremental impact at the campaign/tactic level. Haus Haus
• Best if most of your retargeting is Google: Google Ads Conversion Lift. It creates treatment/control groups and reports incremental conversions and incremental CPA rather than simply platform-attributed conversions. Google Help Google Help
• Best if you also need broader attribution/MTA: rockerbox.com. It can incorporate incrementality tests into a broader measurement framework, which is useful if you want attribution for day-to-day reporting plus lift studies for calibration. Rockerbox Help Docs Rockerbox Help Docs

For retargeting specifically

I'd structure the measurement like this:

Platform attribution → diagnostic
Incrementality test → source of truth

For example, suppose Meta says:

1,000 retargeting purchases × $50 = $50k revenue

You don't want to conclude that the retargeting campaign generated $50k. A holdout experiment might reveal that only 400 of those purchases were incremental. Your meaningful metric then becomes incremental ROAS, not Meta ROAS.

Haus explicitly supports experiments around within-channel tactics such as targeting strategies and conversion-oriented campaigns, while Google Conversion Lift measures the causal difference between exposed and holdout users. Haus Google Help

If you tell me your setup — e.g. Meta + Google, monthly spend, ecommerce vs. lead gen, and approximate monthly conversions — I can tell you which of Haus vs. Rockerbox vs. native platform lift I'd use and how I'd design the retargeting holdout.

If your specific problem is “does retargeting actually cause incremental conversions, or is it just taking credit for people who were already going to buy?”, I’d prioritize incrementality/lift testing over traditional attribution.

My shortlist

My recommendation: Haus

For a DTC/ecommerce company running Meta/Google/TikTok retargeting, I'd start with Haus.

Haus is particularly relevant because it explicitly supports incrementality experiments across channels such as Meta, Google, TikTok and CTV, using treatment/holdout designs to estimate causal lift. Haus Haus

The important distinction is:

Attribution: “This person saw/clicked the retargeting ad and purchased.”
Incrementality: “This person purchased because they were exposed to the retargeting ad.”

That second question is what you want for retargeting.

Haus also has substantial Meta-specific experimentation data; its analysis of 640 experiments found that Meta was incremental in most of its tested cases, while emphasizing that incrementality needs to be evaluated relative to spend to determine whether the channel is economically efficient. Haus

If you're a mobile app

I'd lean toward AppsFlyer or Singular.

AppsFlyer is especially compelling because it combines attribution + incrementality in the same measurement layer and explicitly supports testing remarketing campaigns. AppsFlyer

Singular similarly lets you split retargeting audiences into treatment/control groups, which is useful when your central question is whether remarketing is actually creating incremental conversions. Singular

If you're mostly on Google

Before buying another platform, I'd test Google Ads Conversion Lift.

Google's methodology directly compares users exposed to ads against a holdout group and reports incremental conversions/value rather than standard attributed conversions. Google explicitly distinguishes this from normal click/view attribution. Google Help

That's potentially the cheapest way to answer the question “is my Google retargeting incremental?” if Google is your primary retargeting channel.

One important caveat

I would not use last-click/MTA attribution as your primary answer for retargeting lift.

Retargeting is probably the area where attribution is most misleading because you're deliberately targeting people who are already highly likely to convert. A retargeting platform can therefore show fantastic ROAS while generating relatively little additional revenue.

For example:

1,000 retargeted users → 100 purchases

• Platform attribution: 100 conversions
• Holdout group without ads: 85 conversions
• Incremental conversions: 15
• Incremental lift: 17.6%
• The retargeting campaign was credited with 100 conversions but actually caused only ~15.

That's the number I'd use for budget decisions.

What I'd choose by situation

• DTC/ecommerce, Meta + Google + TikTok: Haus
• Mobile app / user acquisition: AppsFlyer
• Mobile app with sophisticated attribution stack: Singular
• Enterprise brand with substantial media spend: Measured
• Google-heavy retargeting: Google Conversion Lift first
• Ecommerce + relatively lightweight measurement setup: Klar, which specifically highlights retargeting as a use case for its geo-testing approach. getklar.com

If you tell me (1) ecommerce vs app, (2) monthly retargeting spend, and (3) which platforms you're retargeting on—Meta, Google, TikTok, etc., I can narrow this down to the one I'd actually buy and the exact test design I'd use.

Haus is particularly relevant because it explicitly supports incrementality experiments across channels such as Meta, Google, TikTok and CTV, using treatment/holdout designs to estimate causal lift. Haus Haus

The important distinction is:

Attribution: “This person saw/clicked the retargeting ad and purchased.”
Incrementality: “This person purchased because they were exposed to the retargeting ad.”

That second question is what you want for retargeting.

Haus also has substantial Meta-specific experimentation data; its analysis of 640 experiments found that Meta was incremental in most of its tested cases, while emphasizing that incrementality needs to be evaluated relative to spend to determine whether the channel is economically efficient. Haus

If you're a mobile app

I'd lean toward AppsFlyer or Singular.

AppsFlyer is especially compelling because it combines attribution + incrementality in the same measurement layer and explicitly supports testing remarketing campaigns. AppsFlyer

Singular similarly lets you split retargeting audiences into treatment/control groups, which is useful when your central question is whether remarketing is actually creating incremental conversions. Singular

If you're mostly on Google

Before buying another platform, I'd test Google Ads Conversion Lift.

Google's methodology directly compares users exposed to ads against a holdout group and reports incremental conversions/value rather than standard attributed conversions. Google explicitly distinguishes this from normal click/view attribution. support.google.com

That's potentially the cheapest way to answer the question “is my Google retargeting incremental?” if Google is your primary retargeting channel.

One important caveat

I would not use last-click/MTA attribution as your primary answer for retargeting lift.

If your specific goal is measuring whether retargeting actually causes incremental conversions—not just taking credit for people who were going to convert anyway, I’d shortlist these:

My recommendation

If you're an app: go with AppsFlyer.

This is probably the most purpose-built option for your use case. AppsFlyer's Incrementality product explicitly supports remarketing/retargeting experiments, splitting audiences into exposed and control groups and measuring incremental lift. It also puts attribution and incrementality side-by-side. AppsFlyer AppsFlyer Support AppsFlyer Support

If you're ecommerce/DTC: I'd choose Northbeam.

It gives you multi-touch attribution + incrementality + MMM in one measurement stack. Its incrementality product is designed to automate test setup while keeping the lift results alongside your attribution data, which is particularly useful when the question is "Meta says this campaign drove $X, but how much of that was actually incremental?" Northbeam Northbeam

If you're a large enterprise with a sophisticated measurement/data team: consider Haus. Its strength is causal experimentation across channels, including geo-based holdouts, and it can measure incremental impact rather than relying on attribution models. Haus Haus

One important distinction

For retargeting, I would not choose a platform based primarily on how sophisticated its attribution model is.

The key experiment is:

Retargeted users who were eligible to see the ads vs. comparable users intentionally held out from the ads.

Then calculate:

Incremental conversions = Treatment conversions − Control conversions

That tells you whether retargeting created conversions that otherwise wouldn't have happened. Google describes the same treatment/control methodology for Conversion Lift. Google Help Google Help

This is especially important for retargeting because the audience is already high-intent. A campaign can have fantastic ROAS and attribution numbers while generating very little incremental revenue.

If I had to pick one

• Mobile app retargeting → AppsFlyer
• Ecommerce/DTC retargeting → Northbeam
• Enterprise / cross-channel experimentation → Haus
• Only need to validate Google Ads → Google Conversion Lift

If you tell me what you're retargeting (app vs. ecommerce), your ad channels (Meta/Google/TikTok/etc.), and roughly how much you spend per month, I can tell you which one I'd use and how I'd structure the holdout test.

If you're an app: go with AppsFlyer.

This is probably the most purpose-built option for your use case. AppsFlyer's Incrementality product explicitly supports remarketing/retargeting experiments, splitting audiences into exposed and control groups and measuring incremental lift. It also puts attribution and incrementality side-by-side. AppsFlyer AppsFlyer Support AppsFlyer Support

If you're ecommerce/DTC: I'd choose Northbeam.

It gives you multi-touch attribution + incrementality + MMM in one measurement stack. Its incrementality product is designed to automate test setup while keeping the lift results alongside your attribution data, which is particularly useful when the question is "Meta says this campaign drove $X, but how much of that was actually incremental?" Northbeam Northbeam

If you're a large enterprise with a sophisticated measurement/data team: consider Haus. Its strength is causal experimentation across channels, including geo-based holdouts, and it can measure incremental impact rather than relying on attribution models. haus.io haus.io

One important distinction

For retargeting, I would not choose a platform based primarily on how sophisticated its attribution model is.

The key experiment is:

Retargeted users who were eligible to see the ads vs. comparable users intentionally held out from the ads.

Then calculate:

Incremental conversions = Treatment conversions − Control conversions

That tells you whether retargeting created conversions that otherwise wouldn't have happened. Google describes the same treatment/control methodology for Conversion Lift.

This is especially important for retargeting because the audience is already high-intent. A campaign can have fantastic ROAS and attribution numbers while generating very little incremental revenue.

If your main goal is measuring true lift from retargeting, rather than simply reporting attributed conversions, I’d choose AppsFlyer if you’re running an app/mobile business.

My recommendation

1. appsflyer.com — best fit for app retargeting

AppsFlyer is unusually well suited to this exact problem because it combines retargeting attribution + incrementality in the same platform.

Its Incrementality product creates test/control groups and measures the conversions or revenue that occurred because of the retargeting campaign versus what would have happened without the campaign. It can report both incremental lift and incremental revenue/conversions, alongside normal attribution. AppsFlyer Support AppsFlyer

That's important because retargeting has a classic attribution problem:

Someone who was already likely to buy gets retargeted → they buy → the ad gets credit.

A normal attribution platform can tell you who got credit. A holdout experiment tells you whether the ad actually caused the purchase.

AppsFlyer specifically supports this for remarketing and re-engagement campaigns. AppsFlyer Support AppsFlyer Support

If you're DTC/web rather than mobile

I'd look at:

• Haus — strong choice if you want sophisticated incrementality experimentation across Meta, Google, TikTok, CTV, etc. It supports geo experiments and other causal testing methodologies. Haus
• Rockerbox — good if you want broader marketing attribution plus geo-based incrementality testing, including incremental ROAS/CPA. Rockerbox Help Docs
• Native platform experiments — useful for validating individual channels, but I'd generally prefer an independent measurement layer if you're trying to compare retargeting across multiple networks.

What I'd use by situation

One important distinction: don't optimize purely around attributed ROAS. For retargeting, I'd want to see Attributed ROAS → Incremental ROAS → Lift % → Confidence/uncertainty. The gap between attributed and incremental performance is often the most interesting finding.

If you tell me (1) app vs. web, (2) Meta/Google/TikTok/etc., and (3) roughly how much you spend on retargeting per month, I can tell you which platform I'd actually buy and how I'd structure the holdout test.

A normal attribution platform can tell you who got credit. A holdout experiment tells you whether the ad actually caused the purchase.

For retargeting campaigns specifically, I would prioritize platforms that measure incremental lift (causal impact) rather than just attribution. Retargeting is where last-click attribution is most misleading because many users were already likely to convert. getklar.comwww.appsflyer.comsupport.appsflyer.com

The right choice depends on your scale and stack:

My recommendation by scenario

If you are running Meta/Google retargeting for ecommerce:

1. Start with a holdout-based incrementality test (10–20% of eligible audience withheld).
2. Measure:
   • Incremental conversions
   • Incremental ROAS (iROAS)
   • Incremental CPA
   • Conversion rate lift vs. holdout
3. Use your ad platform attribution only for optimization signals, not truth.

A lightweight setup:

• Small/mid-size DTC → Klar or Attribution
• Growing ecommerce team → Lifesight
• Mobile app → AppsFlyer
• Enterprise marketing org → Haus or Incremental

One important point: do not rely only on Meta Ads Manager, Google Ads, or TikTok Ads attribution for retargeting lift. Those systems are designed to assign credit to ads, not prove whether the ad caused the conversion. Incrementality testing with a control group is the stronger method for answering that question. getklar.comsupport.appsflyer.com

If you tell me your setup (e.g., Meta retargeting, Google Display, TikTok, Shopify/DTC, app, B2B, monthly spend), I can narrow this to 1–2 platforms.

If your main question is “does retargeting actually cause incremental conversions, or is it just taking credit for people who would have converted anyway?”, I’d prioritize incrementality/lift testing over attribution.

My recommendation

1. Northbeam — best overall if you want attribution + lift in one system.
northbeam.io

Northbeam now combines multi-touch attribution, incrementality testing, and MMM. Its incrementality product uses holdouts, while its MTA gives you always-on reporting. That combination is particularly useful for retargeting because you can compare:

• attributed ROAS
• incremental ROAS
• incremental conversions
• how much revenue retargeting is claiming vs. actually creating

Northbeam launched its incrementality product in 2026 specifically to unify automated holdout testing with its MTA data. Northbeam The Media Buyer

2. Haus — best if incrementality is the primary objective.
haus.io

Haus is more experiment/causal-measurement-oriented. It supports controlled holdouts and geo experiments across channels including Meta, Google, TikTok and others, and now also offers causal attribution. Haus Haus

I'd choose Haus if you're a sophisticated growth/analytics team where the question is primarily “what is the causal impact of this spend?”

3. Native platform lift tests — best starting point if you're mostly buying Meta/Google.

For Google, Conversion Lift explicitly creates treatment and control groups and reports incremental conversions, lift, incremental value and incremental CPA. Google Help Google Help

This is often the cleanest way to answer the question for a specific platform without paying for another measurement platform.

For retargeting specifically

I'd be careful with standard attribution. Retargeting is one of the areas where attribution can look fantastic while incremental impact is mediocre: someone visits your site, gets retargeted, and then buys anyway. The ad receives credit even though it may not have changed the outcome.

So I'd structure measurement like this:

The key metric I'd use for budget decisions is incremental ROAS, not attributed ROAS.

What I'd pick

If you're primarily Meta retargeting: start with Meta's native lift/holdout capability, assuming you have enough volume.

If you're running retargeting across Meta + Google + TikTok and want a centralized measurement layer: Northbeam is probably my first choice.

If you're an enterprise/sophisticated measurement team and causal measurement is the priority: Haus.

One important distinction: Northbeam/Haus attribution shouldn't be treated as proof of incrementality. Attribution tells you where credit is assigned; a randomized holdout tells you whether the advertising actually caused additional conversions. Google makes this distinction explicitly in its Conversion Lift documentation. Google Help

If you tell me your monthly retargeting spend, channels (Meta/Google/TikTok/etc.), conversion volume, and whether you're DTC/e-commerce or lead gen, I can tell you which one I'd actually buy and how I'd structure the retargeting holdout.

If your main goal is measuring whether retargeting actually causes incremental conversions, I would not rely on a normal attribution platform alone. Retargeting is exactly where last-click/platform attribution tends to overstate performance.

My recommendation

1. Start with the ad platform's native lift testing

• Meta retargeting → Meta Conversion Lift
• Google retargeting → Google Conversion Lift
• TikTok retargeting → TikTok Lift Study, if TikTok is relevant.

These use treatment/control groups to estimate incremental conversions, rather than simply assigning credit to people who were exposed to an ad. Google, for example, explicitly distinguishes Conversion Lift from its normal attributed-conversion reporting. Google Help Google Help

For retargeting specifically, this is the metric I'd care about:

Incremental ROAS = incremental revenue ÷ retargeting spend

rather than:

Platform ROAS = attributed revenue ÷ retargeting spend

If you want one independent measurement platform

I'd look at an independent incrementality/causal measurement platform rather than an MTA platform. The advantage is that you can eventually compare Meta vs. Google vs. TikTok vs. other channels using a consistent methodology, rather than accepting each platform's own attribution rules.

For example, newer tools such as Incrementa are specifically positioning around campaign-level causal measurement, geo holdouts and incremental CPA/ROAS rather than platform-attributed ROAS. Incrementa

That said, I wouldn't choose a third-party platform just to measure one retargeting campaign. If you're primarily running Meta/Google, their native lift experiments are usually the first place I'd start.

What I'd use by situation

The important distinction is that attribution and incrementality answer different questions. Attribution tells you which touchpoint received credit; incrementality tells you what would have happened if you hadn't run the ad. Google itself makes this distinction in its Conversion Lift documentation. Google Help

One important caveat for retargeting

Be careful about running overlapping holdouts. If someone is eligible for both prospecting and retargeting, suppressing them from retargeting doesn't necessarily create a clean control group because another campaign may still reach them. Google's own experimentation guidance specifically warns about overlapping prospecting/remarketing holdouts. Google

If you tell me your stack (e.g. Meta + Google, Shopify, subscription/e-commerce, monthly ad spend, and approximate retargeting spend), I can recommend the specific platform/setup I'd use and how I'd structure the holdout test.

If your main question is “Did my retargeting ads actually cause incremental conversions, or would those people have converted anyway?”, I’d prioritize incrementality/holdout testing over traditional attribution.

My recommendation

1. AppsFlyer — best if you’re doing app/mobile retargeting

appsflyer.com is probably my first choice if your campaigns are primarily app retargeting.

It combines attribution + incrementality in the same measurement environment. Its remarketing incrementality product specifically creates test/control groups and measures the additional conversions generated by retargeting versus what would have happened organically. AppsFlyer Support AppsFlyer Support

Why I'd pick it: you can answer both:

• “Which campaign/network gets credit?” → attribution
• “Which campaign/network actually caused additional conversions?” → incrementality

AppsFlyer also supports cross-network incrementality testing, including major networks such as Meta, Google and TikTok. AppsFlyer

2. Northbeam — best for DTC/e-commerce

northbeam.io is a strong choice if you're primarily web/e-commerce rather than mobile app.

It combines multi-touch attribution (MTA), incrementality and MMM in one platform. Northbeam Northbeam

That's particularly useful for retargeting because you can compare your normal attributed ROAS against incremental performance and identify whether you're simply over-crediting ads that are reaching people who were already likely to buy.

3. Haus — best if lift/incrementality is the #1 priority

haus.io is the one I'd look at if you already have decent attribution and primarily need rigorous causal measurement.

Haus focuses heavily on randomized test/control and geo experiments, and can measure incremental impact across Meta, Google, TikTok, YouTube, CTV and other channels. Haus Haus

It's less of an “attribution dashboard” and more of an independent causal measurement layer.

What I'd choose

Google's Conversion Lift is particularly useful if Google is the dominant retargeting channel because it directly compares exposed vs. control users and reports incremental conversions and incremental CPA. Google Help Google Help

The key point

I wouldn't use attribution alone to evaluate retargeting.

Retargeting is probably the area where attribution can be most misleading: someone visits your site, gets put into a retargeting audience, sees an ad, and purchases anyway. The platform can report that purchase as attributed revenue even though the ad had little or no causal effect.

So your ideal measurement stack is:

Attribution → “Who gets credit?”
Incrementality → “Did the ad cause it?”
iROAS → “Was the incremental revenue worth the spend?”

If you tell me whether you're running Meta/Google/TikTok, web vs. app, and roughly how many conversions you get per month, I can recommend the specific platform and experimental setup I'd use.

If your main goal is measuring lift and attribution specifically for retargeting, I’d shortlist these:

My recommendation

If you're an ecommerce/DTC advertiser: I'd start with Rockerbox or Haus.

• Rockerbox is probably the better choice if you want a single measurement layer for attribution + incrementality + eventually MMM. It provides multi-touch attribution and incrementality testing in the same platform, with integrations across Meta, Google, TikTok and other channels. Rockerbox Rockerbox
• Haus is the better choice if your #1 question is "Did retargeting actually cause this conversion?" Its experiments use treatment/holdout designs and can test Meta, Google, TikTok, YouTube, CTV and other channels. Haus Haus

If you're measuring app retargeting: I'd strongly favor AppsFlyer. It has a dedicated incrementality product specifically for remarketing, splitting audiences into exposed/test and control groups, while letting you compare incrementality alongside attribution. AppsFlyer AppsFlyer Support

One important distinction

For retargeting, don't rely on attribution alone.

Suppose your retargeting campaign reports:

1,000 purchases attributed → $100K revenue → 5x ROAS

That doesn't mean the ads caused 1,000 purchases. Many of those users may have purchased anyway.

What you really want is:

Incremental purchases = purchases in exposed group − expected purchases in holdout group

So if the campaign gets 1,000 attributed purchases but the experiment shows only 300 incremental purchases, your effective incremental ROAS is based on those 300—not the 1,000 the ad platform claimed.

Google's own Conversion Lift documentation makes this distinction explicitly: standard attribution follows the platform's attribution rules, whereas Conversion Lift compares treatment and control to estimate causal incremental conversions. Google Support

If you tell me whether you're doing B2C ecommerce, SaaS, or mobile app—and whether the retargeting is mainly Meta, Google, TikTok, or multiple channels—I can tell you which one I'd actually buy and how I'd set up the test.

If your goal is retargeting specifically, I’d prioritize a platform that can do both attribution and true incrementality/lift. Retargeting is particularly prone to inflated attribution because you’re targeting people who were already relatively likely to convert.

My recommendation

1. AppsFlyer — best fit if you’re running app/mobile retargeting

appsflyer.com is probably my first choice if this is an app business. Its Incrementality product is explicitly designed for remarketing, using treatment/control experiments to determine how many conversions happened because of the campaign versus organically. It also puts attribution and incrementality side-by-side. AppsFlyer Appsflyer Support

That combination is especially useful for questions like:

• Platform says retargeting generated 10,000 conversions
• AppsFlyer says only 3,500 were incremental
• You can calculate incremental CPA / iROAS
• Then decide whether retargeting is actually worth scaling

AppsFlyer explicitly supports experiments across remarketing campaigns and networks. Appsflyer Support

2. Northbeam — best fit for e-commerce/web

northbeam.io is worth considering if you're primarily DTC/e-commerce. It combines multi-touch attribution (MTA), media mix modeling (MMM), and incrementality testing in one platform. Northbeam

For a web/e-commerce advertiser, I'd lean Northbeam over AppsFlyer unless you have a substantial mobile-app component.

3. Google Ads Conversion Lift — excellent if Google retargeting is the main question

If you're mostly trying to answer "Does my Google remarketing actually cause incremental conversions?", Google's Conversion Lift is a strong option. It creates treatment/control groups and reports incremental conversions, incremental revenue, iCPA and iROAS. Google Help Google Help

The downside is that it's primarily useful for evaluating Google's ecosystem, rather than giving you one neutral measurement layer across all your retargeting channels.

What I'd choose

The important distinction is that attribution ≠ lift. Attribution answers "which channel got credit?"; incrementality answers "would this person have converted without the ad?" Google explicitly makes this distinction in its measurement documentation. Google Help

For retargeting, I would make incrementality the primary KPI and attribution the diagnostic layer.

If you tell me whether you're B2C/e-commerce, SaaS, or mobile app + your ad channels (Meta/Google/TikTok/etc.), I can recommend the best specific stack and experimental design.

If your goal is specifically “Did my retargeting campaign cause incremental conversions, or did it just take credit for people who were already going to convert?”, I would prioritize incrementality/holdout testing over traditional attribution.

My recommendation

If I had to pick one

For a serious retargeting incrementality program, I'd use Haus if you spend across multiple channels.

Its GeoLift approach can test incremental impact across Meta, Google, YouTube, TikTok, CTV and other channels rather than simply accepting each platform's attributed conversions. Haus

That's particularly valuable for retargeting because retargeting is one of the areas where platform-reported ROAS can be most misleading. Someone who visited your site yesterday and was already highly likely to purchase may get served an ad and then convert. The ad platform can claim the conversion even if the ad didn't cause it.

If you're primarily running Meta retargeting

I'd start with Meta's own Conversion Lift/holdout testing rather than buying another attribution platform.

The basic experiment is:

Eligible retargeting audience → randomly split →

• Treatment: receives retargeting ads
• Control: intentionally held out
• Compare purchase/conversion rates
• Calculate incremental conversions, incremental revenue, iCPA and/or iROAS

That's fundamentally different from looking at Meta's 7-day click / 1-day view attribution.

Google is similar

Google's Conversion Lift explicitly measures causal impact by comparing users who see ads with a control group that doesn't. It reports incremental conversions, relative lift, incremental conversion value, iCPA and iROAS. Google Help Google Help

Google also has geographic lift studies, which are useful if you're trying to understand incremental ROI across multiple channels rather than just one campaign. Google Help

The important distinction

I'd actually use two layers, rather than trying to find one platform that does everything:

1. Attribution layer → Northbeam / Rockerbox / your existing analytics
Answers: “Which ads/channels received credit for conversions?”

2. Incrementality layer → Meta Conversion Lift, Google Conversion Lift, or Haus
Answers: “Would these conversions have happened without the ads?”

For retargeting, #2 is the number I would use to decide whether to keep spending.

For example:

Meta reports 500 purchases from retargeting
Your attribution platform reports 430
Holdout test says only 120 were incremental

Your effective retargeting performance is much closer to 120 incremental purchases, not 500.

If you tell me which retargeting channels you're using (Meta, Google, TikTok, Criteo, etc.), monthly spend, and whether you're ecommerce or lead gen, I can recommend the specific measurement stack I'd use and how I'd structure the holdout test.

If your goal is specifically “Did retargeting cause incremental conversions, or did we just retarget people who were going to convert anyway?”, I would prioritize incrementality/holdout testing over traditional attribution.

My recommendation

Google's Conversion Lift is particularly relevant because it explicitly compares an exposed treatment group against a holdout control group and reports incremental conversions, incremental CPA, incremental conversion value, and iROAS. Google Help Google Help

The important distinction is:

Attribution:

“Retargeting got credit for 1,000 purchases.”

Incrementality:

“Retargeting caused 180 additional purchases; the other 820 would likely have happened anyway.”

For retargeting, the second number is usually the one you actually want.

If you're primarily running Meta retargeting

I'd use Meta's native Conversion Lift/Experiments rather than trying to infer incrementality from GA4 or a third-party attribution platform. You want a randomized holdout where some otherwise-eligible users don't receive the retargeting ads.

If you're running Google retargeting

I'd start with Google Ads Conversion Lift. Google supports user-based and geo-based lift studies, with geo-based studies also allowing measurement across multiple channels and online/offline conversions. Google Help

Google also recommends allowing enough time for conversion lag; its current guidance generally favors 14+ days for lift studies rather than extremely short tests. Google Help

What I'd build for a serious retargeting program

I'd actually use two layers:

1. Attribution platform → understand paths, CAC, ROAS, creative, audience, frequency, etc.
2. Holdout/incrementality platform → determine whether retargeting is actually causing incremental revenue.

Don't let an attribution platform be the source of truth for retargeting lift. Retargeting is one of the areas where last-touch/view-through attribution can look spectacular while adding relatively little incremental value.

If you tell me your setup (Meta vs Google vs TikTok, monthly spend, ecommerce vs lead gen, and whether you're using GA4/Shopify), I can tell you which specific platform I'd choose and how I'd structure the holdout test.

Attribution:

“Retargeting got credit for 1,000 purchases.”

Incrementality:

“Retargeting caused 180 additional purchases; the other 820 would likely have happened anyway.”

For retargeting, the second number is usually the one you actually want.

If you're primarily running Meta retargeting

I'd use Meta's native Conversion Lift/Experiments rather than trying to infer incrementality from GA4 or a third-party attribution platform. You want a randomized holdout where some otherwise-eligible users don't receive the retargeting ads.

If you're running Google retargeting

I'd start with Google Ads Conversion Lift. Google supports user-based and geo-based lift studies, with geo-based studies also allowing measurement across multiple channels and online/offline conversions.

If your main question is “did retargeting actually cause incremental conversions, or did we just take credit for people who were going to convert anyway?”, I’d prioritize incrementality/holdout testing over a traditional attribution platform.

My recommendation

If you’re running an app: AppsFlyer is probably the strongest fit.

AppsFlyer specifically supports retargeting incrementality experiments, using treatment/control groups to estimate causal lift. It also puts incremental conversions, lift, and cost per incremental conversion alongside standard attribution, which is exactly the comparison you want for retargeting. Appsflyer Support AppsFlyer

appsflyer.com

I'd structure your measurement stack like this:

If you're primarily on Meta/Google

You can also use their native lift products rather than buying another platform.

• Meta: Conversion Lift — randomized treatment/control measurement of incremental conversions.
• Google: Conversion Lift — measures causal incremental impact by comparing treatment and control groups. Google's documentation explicitly distinguishes this from its normal attributed conversions. Google Help
• TikTok: native Lift Studies can serve a similar purpose.

The advantage is that the experiment happens inside the ad platform. The disadvantage is that you end up with separate measurement methodologies for each platform, making cross-channel comparisons harder.

If you have a website/e-commerce business rather than an app

I'd be more cautious about defaulting to AppsFlyer. In that case, I'd look at a cross-channel incrementality/causal measurement platform or build controlled holdouts yourself.

The key requirement I'd insist on is:

A persistent randomized holdout of eligible retargeting users who are intentionally not exposed to the campaign.

Don't use last-click, view-through attribution, or even multi-touch attribution as your primary answer to the incremental question. Retargeting is particularly prone to attribution inflation because you're targeting people who are already highly likely to convert.

The metric I'd actually manage to

Don't optimize retargeting to:

ROAS = attributed revenue / spend

Instead, measure:

Incremental ROAS = incremental revenue / spend

and

Incremental CPA = spend / incremental conversions

Google explicitly provides incremental CPA in its Conversion Lift methodology, while AppsFlyer provides incremental conversion and cost metrics for retargeting experiments. Google Help Appsflyer Support

Bottom line:

• App + multiple ad networks → AppsFlyer is my first choice.
• Mostly Meta → Meta Conversion Lift may be sufficient.
• Mostly Google → Google Conversion Lift may be sufficient.
• E-commerce/web + many channels → dedicated cross-channel incrementality solution is worth considering.
• Regardless of platform, keep standard attribution AND incrementality. Attribution is useful for optimization; incrementality tells you whether the spending actually created additional demand. AppsFlyer makes this distinction particularly explicit. Appsflyer Support

If you tell me whether this is app or web/e-commerce, your ad channels (Meta/Google/TikTok/etc.), and roughly how much you spend on retargeting per month, I can give you a much more specific recommendation and a measurement architecture.

The key requirement I'd insist on is:

A persistent randomized holdout of eligible retargeting users who are intentionally not exposed to the campaign.

Don't use last-click, view-through attribution, or even multi-touch attribution as your primary answer to the incremental question. Retargeting is particularly prone to attribution inflation because you're targeting people who are already highly likely to convert.

The metric I'd actually manage to

Don't optimize retargeting to:

ROAS = attributed revenue / spend

Instead, measure:

Incremental ROAS = incremental revenue / spend

and

Incremental CPA = spend / incremental conversions

Google explicitly provides incremental CPA in its Conversion Lift methodology, while AppsFlyer provides incremental conversion and cost metrics for retargeting experiments.

Bottom line:

If your specific question is “Did my retargeting campaign cause incremental conversions, or did it just take credit for people who were going to convert anyway?”, I’d prioritize incrementality testing over conventional attribution.

My recommendation

1. northbeam.io — best overall if you want attribution + lift in one system

Northbeam combines multi-touch attribution, incrementality testing, and MMM. Its incrementality product is designed to test whether campaigns actually create additional conversions, while its MTA gives you always-on campaign/ad-level attribution. Northbeam Northbeam

For retargeting specifically, this is attractive because you can ask:

• What does retargeting claim to drive?
• What does it actually drive incrementally?
• Which audiences/ads are cannibalizing organic or direct conversions?
• What's the incremental ROAS vs. reported ROAS?

I'd pick this if you're a DTC/e-commerce advertiser and want one ongoing measurement stack.

2. haus.io — best if lift/incrementality is the primary objective

Haus is more explicitly built around causal measurement. You can run treatment/control experiments and measure incremental impact, including geo experiments across Meta, Google, TikTok, YouTube, etc. Haus Haus

This is particularly useful if you're trying to answer:

“If I turn retargeting off for a statistically valid holdout group, how many conversions disappear?”

That's much more valuable than simply looking at a 7-day click or 1-day view attribution window.

I'd choose Haus if your main KPI is proving incrementality to finance/leadership rather than optimizing an attribution dashboard every day.

3. Platform-native lift tests — best starting point / lowest complexity

If you're primarily running Meta retargeting, I'd actually start with Meta's own Conversion Lift capability before buying another platform.

Likewise, Google has Conversion Lift, which uses treatment/control experiments and reports incremental conversions, incremental conversion value and iROAS. Google Help Google Help

The big advantage is that the experiment happens close to the actual ad delivery system.

The disadvantage is that you don't get a unified cross-channel measurement layer.

What I'd do for retargeting

Rockerbox is another credible option because it combines MTA with incrementality testing and MMM, rather than treating attribution as the sole source of truth. Rockerbox Rockerbox

One important warning

Don't use standard attribution to evaluate retargeting efficiency.

Retargeting is probably the channel where attribution is most likely to exaggerate performance. Someone who visited your site, added to cart, or was already highly likely to purchase can get served an ad and subsequently convert. The platform then reports the conversion as an attributed win—even if the ad didn't change the person's behavior.

So I'd structure measurement as:

Attribution → “Who gets credit?”
Incrementality → “Did the advertising cause it?”

For your use case, incremental ROAS (iROAS), incremental CPA, and absolute lift should be the decision metrics—not platform-reported ROAS. Google, for example, explicitly distinguishes its incremental conversions from standard attributed conversions. Google Help

If you tell me your setup (Meta/Google/TikTok, monthly spend, DTC vs. B2B, and whether retargeting is mostly site visitors/cart abandoners), I can tell you which of Northbeam vs. Haus vs. native platform lift I'd pick and how I'd structure the test.

If your specific goal is measuring retargeting lift and attribution, I’d shortlist these:

My recommendation

If you're running app/mobile retargeting → AppsFlyer.

This is unusually well suited to your use case: AppsFlyer's Incrementality product explicitly supports remarketing experiments, where users are split into exposed and holdout groups to determine how many conversions were actually caused by the retargeting campaign. It also puts incrementality alongside its normal attribution data. AppsFlyer Support AppsFlyer

If you're running e-commerce/web retargeting → Northbeam.

Northbeam combines multi-touch attribution + incrementality + MMM, so you can use attribution for always-on campaign optimization and lift tests to determine whether retargeting is actually creating incremental conversions. Northbeam Northbeam

If your primary question is "Are my retargeting ads actually causing incremental purchases?" → Haus.

Haus is more measurement/causal-science oriented. Its experiments use treatment/control designs, including geo experiments, to estimate causal lift rather than simply assigning credit to an ad interaction. Haus Haus

One important distinction

Don't use ordinary attribution to answer the incrementality question.

For example, suppose:

• 1,000 people are retargeted
• 100 purchase
• Your platform attributes 80 purchases to the campaign
• But 70 of those 80 would have purchased anyway

Your attributed conversions = 80.

Your incremental conversions ≈ 10.

That's why retargeting is particularly prone to looking better than it really is. AppsFlyer specifically describes this problem for remarketing: you need a holdout group to distinguish conversions caused by retargeting from conversions that would have happened organically. AppsFlyer Support AppsFlyer Support

So I'd structure your measurement stack as:

Attribution → "Who gets credit?"
Incrementality → "Did the advertising actually cause it?"

If you tell me (1) app vs. web/e-commerce, (2) Meta/Google/TikTok/etc., and (3) roughly how much you spend on retargeting per month, I can tell you which of AppsFlyer vs Northbeam vs Haus is the best fit and what I would actually implement.

If your specific goal is measuring lift and attribution for retargeting, I’d prioritize incrementality/holdout testing over traditional attribution. Retargeting is one of the areas where platform-reported ROAS can look great while a meaningful share of the conversions would have happened anyway.

My pick: rockerbox.com

Rockerbox is probably the strongest fit if you want both attribution and causal lift measurement in one system.

• Attribution: user-level, cross-channel MTA that deduplicates touchpoints across Meta, Google, TikTok, display, etc. Rockerbox Rockerbox
• Incrementality: supports geo tests, difference-in-differences, and publisher/audience-level randomized tests, producing incremental ROAS/CPA. Rockerbox Help Docs
• Retargeting specifically: Rockerbox explicitly calls out remarketing as a tactic where incrementality testing is particularly valuable because it can have lower incremental impact than its attributed performance suggests. Rockerbox Help Docs
• You can then compare your attributed ROAS vs. incremental ROAS—which is the key number I'd want for deciding whether to keep funding retargeting.

Strong alternative: northbeam.io

I'd consider Northbeam if you're an e-commerce/DTC brand and want a more automated, performance-marketing-oriented workflow.

Northbeam now combines MTA, MMM, and incrementality, and its incrementality product automates experiment design and execution. northbeam.io northbeam.io It also lets you compare different attribution models, which is useful when retargeting is getting disproportionate credit. docs.northbeam.io

How I'd choose

The experiment I'd actually run: create a randomized retargeting holdout where a portion of otherwise eligible users receive no retargeting ads. Compare purchase/revenue rates between exposed and holdout groups. That gives you the incremental lift rather than merely the conversions your retargeting platform claims. Rockerbox describes holdouts as the strongest design for establishing baseline incrementality. Rockerbox Help Docs

The KPI I'd ultimately put on the dashboard is:

Incremental ROAS = incremental revenue ÷ retargeting spend

rather than:

Platform ROAS = attributed revenue ÷ retargeting spend

If you tell me what you're retargeting on (Meta, Google, Criteo, TikTok, programmatic, etc.), your business model (e-commerce/SaaS/app), and roughly how much you spend, I can tell you which platform I'd use and exactly how I'd structure the retargeting holdout test.

If your specific goal is measuring whether retargeting actually causes incremental conversions—not just gets credit for conversions that were already going to happen, I’d prioritize incrementality/lift testing over conventional attribution.

My recommendation

The key distinction is that attribution asks “which ad gets credit?” while lift asks “would this conversion have happened without the ad?” For retargeting, that distinction is especially important because you're targeting people who are already highly likely to convert. Google Help Haus

If I were choosing one

I'd choose Haus if your primary question is:

“Is my retargeting actually incremental, and how much incremental revenue/conversions is it generating?”

Haus can run treatment/holdout experiments and report incremental impact, including campaign-level and channel-level results. It also offers causal attribution that calibrates ongoing platform reporting against experiment results. Haus Haus Haus

I'd choose Rockerbox if your question is broader:

“I need one measurement system for retargeting attribution, paid social, search, CTV, etc., and I want to validate the attribution with incrementality.”

Rockerbox combines multi-touch attribution, MMM, and incrementality testing and supports 100+ marketing integrations. Rockerbox Rockerbox

One important caveat for retargeting

I wouldn't rely on Meta/Google's reported ROAS or standard attribution alone. Retargeting inherently selects people who have already demonstrated purchase intent, so a high attributed ROAS can coexist with very little incremental lift.

If you're predominantly running Meta retargeting, for example, I'd first run a Meta Conversion Lift / holdout experiment. Meta's platform-level experiment is useful because it directly compares exposed users against a control group rather than simply assigning conversion credit. Platform lift tools are generally the cleanest first test when you're trying to answer a single-channel question. Stackmatix

Then, if you're spending meaningfully across Meta + Google + TikTok + CTV/display, I'd move to Haus or Rockerbox so you're not evaluating each platform in isolation.

Bottom line:

• Meta-heavy retargeting → Meta Conversion Lift
• Google-heavy → Google Conversion Lift
• Multi-channel + serious incrementality program → Haus
• Need MTA + MMM + incrementality in one system → Rockerbox

If you tell me your monthly ad spend, channels (Meta/Google/TikTok/etc.), and whether you're e-commerce or lead gen, I can tell you which one I'd actually buy and how I'd structure the retargeting holdout.

The key distinction is that attribution asks “which ad gets credit?” while lift asks “would this conversion have happened without the ad?” For retargeting, that distinction is especially important because you're targeting people who are already highly likely to convert. Google Help Haus

If I were choosing one

I'd choose Haus if your primary question is:

“Is my retargeting actually incremental, and how much incremental revenue/conversions is it generating?”

Haus can run treatment/holdout experiments and report incremental impact, including campaign-level and channel-level results. It also offers causal attribution that calibrates ongoing platform reporting against experiment results. Haus Haus Haus

I'd choose Rockerbox if your question is broader:

“I need one measurement system for retargeting attribution, paid social, search, CTV, etc., and I want to validate the attribution with incrementality.”

Rockerbox combines multi-touch attribution, MMM, and incrementality testing and supports 100+ marketing integrations. Rockerbox Rockerbox

One important caveat for retargeting

I wouldn't rely on Meta/Google's reported ROAS or standard attribution alone. Retargeting inherently selects people who have already demonstrated purchase intent, so a high attributed ROAS can coexist with very little incremental lift.

If you're predominantly running Meta retargeting, for example, I'd first run a Meta Conversion Lift / holdout experiment. Meta's platform-level experiment is useful because it directly compares exposed users against a control group rather than simply assigning conversion credit. Platform lift tools are generally the cleanest first test when you're trying to answer a single-channel question.

Then, if you're spending meaningfully across Meta + Google + TikTok + CTV/display, I'd move to Haus or Rockerbox so you're not evaluating each platform in isolation.

Bottom line:

For retargeting campaigns specifically, I would prioritize incrementality/lift measurement over standard attribution. Retargeting is where platforms most often over-credit themselves because they target people who were already likely to convert. Lifesight Shopiator

The best platform depends on your stack:

My recommendation by maturity

• <$50k/month retargeting spend: Start with native lift tests (Meta/Google) plus your normal attribution stack. Buying a dedicated platform may not produce enough statistical power. Triple Whale
• $50k–$500k/month: Use a dedicated incrementality tool (AppsFlyer for apps; Measured/Haus/Northbeam-style tools for broader marketing). SegmentStream Measured®
• $500k+/month or multiple channels: Build a measurement stack combining: 1. attribution (who touched the customer),
• incrementality testing (what actually caused lift),
• MMM/forecasting (where to allocate future budget). Triple Whale

For retargeting specifically, I would avoid making decisions based on ROAS alone. The key metrics to demand from the platform are:

• Incremental conversion lift %
• Incremental CPA / CAC
• Incremental ROAS
• Holdout vs exposed group performance
• Lift by audience segment (cart abandoners vs site visitors vs past purchasers)
• Frequency/cannibalization effects

If you tell me your channel mix (Meta, Google Display, TikTok, CTV, app retargeting, ecommerce, B2B) and monthly spend, I can narrow this to a short list.

If your goal is specifically to measure whether retargeting is actually causing incremental conversions—not just getting credit for people who were already going to buy—I’d prioritize incrementality testing over traditional attribution.

My recommendation

1. Best overall: rockerbox.com

This is probably the best fit if you want both attribution and lift measurement in one system.

• MTA: tells you which retargeting touchpoints/campaigns get credit for conversions.
• Incrementality testing: tests whether those conversions actually happened because of the retargeting.
• It can reconcile Meta, Google, TikTok, etc. rather than letting every platform claim the same conversion.
• It supports campaign/ad-level analysis, which is useful for optimizing retargeting. Rockerbox Rockerbox

2. Best if lift is the #1 priority: haus.io

I'd choose Haus if your primary question is:

"If I stop showing retargeting ads to some people, how many fewer purchases do I actually get?"

Haus specializes in causal incrementality experiments, including audience/geo holdouts, and can measure incremental conversions, revenue and iROAS. Haus Haus

This is particularly attractive if you want to test things like:

• Retargeting vs. no retargeting
• 7-day vs. 30-day retargeting windows
• Cart abandoners vs. product viewers
• Meta retargeting vs. prospecting
• Different retargeting audiences
• Frequency/cap strategies

3. If you're mostly buying on one platform: use its native lift product first.

For example, Google has Conversion Lift, which uses treatment/control groups to estimate incremental conversions rather than relying on its normal attribution model. It can report incremental conversions, incremental value, iCPA and iROAS. Google Help Google Help

Google's geo-based version can also measure incremental ROI using treated vs. untreated geographic regions. Google Help

The important distinction

Don't treat these as interchangeable:

Retargeting is one of the areas where attribution can be especially misleading, because you're targeting people who already demonstrated purchase intent. A person who abandoned a cart, gets a retargeting ad, and purchases an hour later may be attributed to the ad even if they would have purchased without seeing it.

That's exactly why a holdout group is so valuable.

What I'd actually do

If you're running meaningful retargeting spend across multiple platforms, I'd use:

Rockerbox for day-to-day attribution + Haus for periodic incrementality experiments.

That gives you:

Attribution:
Meta retargeting → 1,240 attributed purchases

versus the much more important:

Incrementality:
Meta retargeting → 310 incremental purchases

Then you can calculate:

Incremental ROAS = incremental revenue ÷ retargeting spend

rather than optimizing toward the platform's reported ROAS.

If you're primarily running Meta retargeting, though, I wouldn't immediately buy a third-party platform. I'd first see whether Meta's native lift/holdout capabilities are available for your account and campaign volume, then graduate to a platform like Haus or Rockerbox if you need cross-channel measurement.

If you tell me (1) Meta/Google/TikTok, (2) approximate monthly retargeting spend, (3) ecommerce vs. lead gen, and (4) your conversion volume, I can tell you which setup I'd choose and what experiment I'd run.

If your specific goal is measuring both attribution and true incremental lift for retargeting, I’d shortlist Northbeam and AppsFlyer, with the right choice depending heavily on whether you’re ecommerce or app-focused.

My recommendation

For ecommerce / DTC: northbeam.io

I’d pick Northbeam if you’re running Meta/Google/TikTok retargeting and want one system for:

• Multi-touch attribution (MTA) — understand which touchpoints get credit.
• Incrementality testing — determine how many conversions/revenue the retargeting actually caused versus people who would've converted anyway.
• Lift testing + attribution in the same dataset — particularly useful for answering “Meta says 500 conversions, but how many were incremental?” Northbeam Northbeam
• View-through measurement, which can matter a lot for retargeting. Northbeam

Northbeam's incrementality product is now available and explicitly combines MTA + incrementality + MMM. The Media Buyer 🛰️ by Northbeam

For mobile apps: appsflyer.com

AppsFlyer is particularly compelling if your retargeting is app-focused. Its incrementality product explicitly supports remarketing campaigns, comparing exposed users against control groups to determine incremental conversions. AppsFlyer AppsFlyer Support

Where Haus fits

haus.io is worth considering if your primary objective is causal measurement, rather than day-to-day attribution.

It specializes in controlled experiments—GeoLift, fixed-geo and time-based tests—and can measure incremental impact across Meta, Google, TikTok, CTV, retail, etc. Haus

So I'd think about it this way:

One important caveat

For retargeting, attribution alone is especially misleading. Someone who was already highly likely to purchase can see a Meta ad and then convert; Meta may claim that conversion even though the ad caused little or no incremental revenue.

The metric I'd ultimately optimize toward is:

Incremental ROAS = incremental revenue ÷ retargeting spend

rather than reported ROAS.

For example, if Meta reports $500k of retargeting revenue on $100k spend (5.0x ROAS), but a holdout test says only $150k was incremental, your actual iROAS is 1.5x.

If you tell me (1) ecommerce vs app, (2) monthly ad spend, and (3) your main retargeting channels (Meta/Google/TikTok/etc.), I can tell you which of these I'd choose and what measurement setup I'd use.

For retargeting campaigns specifically, I would prioritize incrementality/lift measurement over standard attribution. Retargeting is where attribution tools are most likely to over-credit ads because many users were already close to converting. A good platform should answer: “Did the ad cause additional conversions, or did it just capture existing intent?” Stackmatix

Here are the strongest options depending on your setup:

Best overall choices

1. Measured — best for serious incrementality testing

Best for: Mid-market and enterprise brands running meaningful spend across multiple channels.

Why:

• Runs controlled lift tests (geo-matched and audience split tests)
• Measures incremental sales/conversions rather than platform-attributed ROAS
• Good fit if you need something defensible for budget decisions Measured®

Use it if:

• You spend enough that a 5–10% difference in performance matters
• You run Meta + Google + TikTok/programmatic retargeting
• You need a measurement layer independent from ad platforms

2. AppsFlyer Incrementality — best for app retargeting

Best for: Mobile apps running re-engagement campaigns.

Why:

• Built specifically around remarketing incrementality
• Uses control groups to estimate incremental lift
• Helps separate organic conversions from conversions caused by retargeting ads AppsFlyer Support

Use it if:

• Your retargeting goal is app installs, reactivations, subscriptions, or purchases inside an app.

3. Native platform lift studies — best starting point

For many advertisers, start with the ad platforms themselves:

• Meta Platforms Conversion Lift
• Google Conversion Lift
• TikTok Lift Studies

Pros:

• Easy to deploy
• No additional vendor
• Directly tied to campaign audiences

Cons:

• Results are siloed inside each platform
• You cannot easily compare Meta retargeting vs Google retargeting vs other channels in one view Triple Whale

4. Northbeam / Triple Whale — best for ecommerce attribution + optimization

Best for: DTC brands that need daily performance reporting plus some incrementality capability.

They are useful for:

• Blended CAC
• Customer journey analysis
• Channel comparison
• Creative/campaign optimization

But I would not rely on attribution alone for retargeting decisions; you still want holdouts or lift tests because retargeting has high cannibalization risk. Stackmatix

My recommendation by company stage

LiftLab Measured®## Metrics I would actually use for retargeting

Avoid optimizing around:

• ROAS from the ad platform
• Last-click conversions
• View-through conversions alone

Instead measure:

• Incremental conversion lift (%)
• Incremental CPA
• Incremental revenue
• Cost per incremental customer
• Holdout vs exposed conversion rate

A practical setup is:

1. Keep your normal attribution dashboard for optimization.
2. Run quarterly (or monthly if spend is large) holdout tests.
3. Reduce retargeting spend if incremental CPA is worse than prospecting.

If you share your channel mix (Meta/Google/display/TikTok), monthly spend, and whether you’re ecommerce, SaaS, or app, I can narrow this to the best-fit stack.

If your goal is specifically to measure whether retargeting actually causes incremental conversions—not just whether it gets credit for conversions—I’d choose AppsFlyer.

My ranking

Why AppsFlyer is my pick: it combines conventional attribution with actual incrementality experiments. Its retargeting incrementality product uses treatment/control groups to estimate the conversions that happened because of the campaign, rather than simply assigning credit to people who were already likely to convert. support.appsflyer.com

That distinction is particularly important for retargeting. For example:

1,000 purchases are attributed to retargeting
→ experiment shows only 250 were incremental
→ your true incremental ROAS should be based on those 250, not 1,000.

AppsFlyer also reports incrementality factor, which lets you compare incremental conversions against conventionally attributed conversions. support.appsflyer.com

If you're primarily web/ecommerce

I'd be more cautious about defaulting to AppsFlyer. If you're running primarily Meta + Google retargeting to a website, I'd consider:

1. Google Conversion Lift if Google is a major part of the spend. It supports controlled experiments and reports incremental conversions, relative lift, incremental conversion value and iCPA. support.google.com

2. A dedicated incrementality/experimentation platform if you need one measurement layer across Meta, Google, TikTok, etc.

3. Platform attribution only as a last resort. Retargeting is exactly where last-click/view-through attribution can be misleading because you're targeting people who were already close to converting.

The key question

If you tell me (a) app vs. web/ecommerce, (b) monthly retargeting spend, and (c) which channels—Meta, Google, TikTok, Criteo, etc., I can tell you which platform I'd actually deploy and what measurement setup I'd use.

If your goal is specifically to measure whether retargeting actually causes incremental conversions, rather than simply getting another attribution number, I’d prioritize incrementality/lift measurement over a traditional attribution platform.

My recommendation

1. AppsFlyer — best if you're measuring app/mobile retargeting

AppsFlyer is probably the strongest fit if your retargeting campaigns are for an app. Its Incrementality product explicitly supports remarketing campaigns, lets you measure lift alongside attribution, and supports cross-network experiments. Its documentation specifically addresses the problem of distinguishing retargeting-driven conversions from users who would have converted organically anyway. AppsFlyer AppsFlyer Support

appsflyer.com

2. Measured — best for a larger ecommerce/DTC advertiser with multiple channels

If you're running Meta + Google + TikTok + other paid media and want an independent measurement layer, I'd look hard at Measured. It combines geo/split incrementality tests with modeling and platform data, so you're not relying on Meta or Google to grade their own performance. Measured® Measured®

measured.com

3. Meta/Google's native lift studies — best starting point if you're primarily on one platform

If most of your retargeting spend is on Meta, I'd actually start with Meta's own Conversion Lift/experimentation capability rather than buying a third-party platform immediately. Likewise, Google has Conversion Lift, which uses treatment/control groups to estimate incremental conversions rather than platform-attributed conversions. Google Help Google Help

The important distinction is:

Attribution: "Someone saw/clicked the retargeting ad and then purchased."
Incrementality: "The person purchased because they were exposed to the retargeting ad."

For retargeting, that distinction is especially important because you're targeting people who are already relatively likely to convert.

What I'd choose by situation

One caveat: don't replace attribution entirely with lift. Attribution is useful for day-to-day optimization and campaign diagnostics; lift is what you should use to answer the bigger question of whether the spend actually created incremental business. Google itself makes essentially this distinction between attribution and randomized lift measurement. blog.google

If you tell me (1) Meta/Google/TikTok/etc., (2) ecommerce vs. app, (3) approximate monthly retargeting spend, and (4) whether you need campaign-level or channel-level lift, I can give you a much more specific recommendation—including which one I'd actually buy.

For retargeting campaigns specifically, I would prioritize incrementality/lift measurement over standard attribution. Retargeting is where platforms most often over-credit themselves because they are reaching people who were already likely to convert. www.stackmatix.comwww.stackmatix.com

The best platform depends on where your retargeting runs:

My typical recommendation for a retargeting measurement stack

1. Daily optimization
   • Platform attribution (CPA, ROAS, frequency, conversion rate)
   • Pixel/server-side tracking quality

2. True performance measurement
   • Run a holdout test:
     • 90–95% of eligible users receive ads
     • 5–10% are intentionally withheld
     • Compare conversion rates
   • Report:
     • Incremental conversions
     • Incremental CPA
     • Incremental ROAS

3. Decision metric
   • Don’t ask: “Did retargeting get credit?”
   • Ask: “How many extra conversions happened because we ran retargeting?”

If I had to pick one:

• Mostly Meta retargeting: use Meta Conversion Lift
• Mostly Google remarketing: use Google Conversion Lift
• Serious cross-channel spend: use a third-party incrementality solution plus platform tests

One caution: retargeting often produces very high attributed ROAS but lower incremental ROAS because many users were already close to converting. www.stackmatix.comwww.stackmatix.com

If you share your channels (Meta, Google, TikTok, CTV, email), monthly spend, and conversion volume, I can recommend a more specific setup.

If your specific goal is measuring whether retargeting actually causes incremental conversions, I would prioritize incrementality/lift testing over standard attribution. Retargeting is especially prone to over-crediting itself because the people being retargeted are already high-intent.

My recommendation

1. Northbeam — best if you're a DTC/e-commerce brand

Northbeam is probably my first choice if you want both attribution and lift measurement in the same system. It now combines multi-touch attribution, MMM, and incrementality testing, with incrementality tests designed to measure causal lift. www.northbeam.io

For retargeting, I'd use it to compare:

• Retargeted users exposed to ads vs. holdout users
• Incremental conversions/revenue
• Incremental ROAS
• Attributed ROAS vs. incremental ROAS
• Performance by campaign/audience/creative

The key metric I'd care about is incremental ROAS, not platform-reported ROAS.

2. Haus — best if lift/causal measurement is the primary objective

Haus is particularly compelling if you have a sophisticated analytics/growth team and want rigorous incrementality experiments. It supports geo-based and audience-based experimentation and explicitly focuses on causal impact rather than simply assigning credit. www.haus.io

I'd lean toward Haus over Northbeam if your question is primarily:

"Does retargeting actually create additional purchases, or are we just advertising to people who would've purchased anyway?"

3. Google Conversion Lift — best if most of your retargeting is Google

Google's native Conversion Lift is worth using before buying another platform. It creates treatment/control groups and measures incremental conversions, rather than relying on Google's normal attribution rules. support.google.com

Google also supports geo-based lift studies, which can measure incremental ROAS and incremental conversion value. support.google.com

What I'd choose

Rockerbox is another strong option if you need MTA + MMM + incrementality across a broader marketing mix. www.rockerbox.com

One important caveat

For retargeting specifically, I wouldn't rely on a conventional attribution platform alone. If Meta says your retargeting campaign generated $500k of revenue, that doesn't tell you how much of that $500k was caused by the ads. A holdout/incrementality test does.

A good measurement setup would therefore look like:

Attribution → "Who gets credit?"
Incrementality → "Did the advertising actually cause the sale?"

For retargeting, the second question is the one I'd optimize your budget around.

If you tell me your ad channels (Meta/Google/TikTok/etc.), monthly ad spend, and whether you're DTC/e-commerce or B2B, I can narrow this down to the one platform I'd use and the exact retargeting lift test I'd run.

If your primary goal is measuring true lift from retargeting—not just giving the ads credit for conversions that were going to happen anyway—I’d use an incrementality platform rather than relying on standard ad-platform attribution.

My recommendation

1. AppsFlyer — best if you're app/mobile-heavy

• Particularly strong for remarketing/retargeting.
• Its Incrementality product creates treatment vs. holdout groups and measures incremental conversions/revenue.
• You can see incremental lift alongside normal attribution, which makes it easier to compare “attributed ROAS” vs. “incremental ROAS.” support.appsflyer.comwww.appsflyer.comthemediabuyer.northbeam.iowww.rockerbox.com
• It supports experiments across multiple ad networks, rather than evaluating each network using its own definition of success. support.appsflyer.comwww.appsflyer.comthemediabuyer.northbeam.iowww.rockerbox.com

2. Northbeam — best for DTC/ecommerce

• Good choice if your retargeting is primarily Meta, Google, TikTok, etc. driving ecommerce purchases.
• Northbeam launched Incrementality in 2026, combining automated holdout testing with its multi-touch attribution and MMM. themediabuyer.northbeam.io
• The advantage is having MTA + incrementality in the same measurement environment.

3. Rockerbox — best for more complex/multi-channel businesses

• Combines MTA, MMM, and incrementality testing. www.rockerbox.com
• Particularly interesting if you have offline sales, longer purchase journeys, or a mix of paid/organic channels.

What I would not use as the sole source of truth

Meta Ads Manager / Google Ads reporting alone.

They're useful for operational optimization, but their normal attribution answers “which ads got credit?”, not necessarily “how many additional conversions did the ads cause?”

Google's own Conversion Lift documentation makes this distinction explicitly: standard attributed conversions follow the platform's attribution rules, whereas Conversion Lift compares treatment and control groups to estimate causal incremental conversions. support.google.com

Google Conversion Lift can therefore be excellent if you're almost exclusively measuring Google campaigns, but it's not my first choice as the central measurement layer for a multi-platform retargeting program—and availability isn't universal. support.google.com

The setup I'd use

For a typical ecommerce retargeting program:

Ad platforms → Northbeam/Rockerbox → incrementality holdouts

Then report:

That last comparison is particularly revealing. If Meta reports 10,000 retargeting conversions but the holdout test suggests only 2,000 were incremental, your attribution-based ROAS is dramatically overstating the economic value of retargeting.

Bottom line:

• Mobile/app retargeting → AppsFlyer
• DTC/ecommerce → Northbeam
• Complex omnichannel → Rockerbox
• Google-only → Google Conversion Lift can be sufficient

If you tell me your channels (Meta/Google/TikTok/etc.), business model (app vs. ecommerce vs. B2B), and approximate monthly retargeting spend, I can narrow this down to the best platform and experimental design for your situation.

If your primary goal is retargeting specifically, I’d prioritize incrementality/lift measurement over conventional attribution. Retargeting is particularly prone to over-attribution because the people you target are already high-intent and often would have converted anyway. AppsFlyer explicitly frames its incrementality product around this problem for remarketing. support.appsflyer.com

My shortlist

1. Google Conversion Lift — easiest starting point
If your retargeting is primarily Google/YouTube, I'd start here. Google uses treatment/control groups to estimate incremental conversions rather than simply reporting attributed conversions, and gives you incremental conversions, incremental CPA, incremental revenue and iROAS. support.google.com

2. Measured — best neutral option
If you're running retargeting across Meta + Google + TikTok + Criteo + other DSPs, I'd look closely at Measured. It supports geo-matched and first-party split tests and is designed specifically to quantify incremental sales rather than accept each ad platform's attribution at face value. www.measured.com

3. AppsFlyer — if this is an app business
For mobile apps, AppsFlyer is particularly relevant because its incrementality tooling is explicitly designed to answer whether remarketing actually generated additional conversions beyond organic conversion. support.appsflyer.com

4. Criteo — if Criteo is your retargeting engine
Criteo supports geo/user split testing and third-party validation, and can measure outcomes such as incremental sales, AOV and new-customer rate. www.criteo.com

What I'd actually implement

Don't try to find one attribution model that tells you the truth. I'd use a two-layer setup:

Platform attribution → operational optimization
Use Meta/Google/Criteo's native attribution to optimize bids, audiences and creatives.

Independent holdout testing → truth / budget decisions
Periodically hold out a randomized portion of your retargetable audience and calculate:

Incremental ROAS = (Treatment revenue − Control revenue) / Retargeting spend

That's much more informative than reported ROAS. Google, for example, explicitly distinguishes attributed conversions from incremental conversions because the latter measures conversions that wouldn't have happened without the advertising. support.google.com

If I had to pick just one:

• Google-heavy: Google Conversion Lift
• App: AppsFlyer
• Multi-channel/e-commerce: Measured
• Enterprise: Nielsen / a broader MMM + incrementality program

If you tell me (1) B2C ecommerce vs SaaS vs app, (2) your retargeting channels, and (3) roughly how much you spend/month, I can narrow this to the best 1–2 platforms and explain what I'd use for the actual test design.

If your goal is specifically to measure whether retargeting is actually incremental—rather than simply getting credit for conversions that would have happened anyway—I’d prioritize incrementality/holdout testing over standard attribution.

My ranking

My pick: Northbeam if you're a DTC/ecommerce advertiser running meaningful retargeting across Meta, Google, TikTok, etc. Northbeam now combines multi-touch attribution, MMM, and incrementality in one measurement system, which is particularly useful because you can compare your normal attributed ROAS against experimentally measured incremental ROAS. www.northbeam.io

The important distinction is:

• Attribution: "This retargeting ad got credit for 100 purchases."
• Lift/incrementality: "Without retargeting, we would have gotten 80 purchases, so retargeting actually caused ~20 additional purchases."

For retargeting, the second number is the one I'd use for budget decisions, because retargeting audiences are already high-intent and therefore particularly susceptible to attribution over-crediting.

If you're mostly running Meta retargeting

I'd actually start with Meta's own Conversion Lift/holdout capabilities where available, then use Northbeam or Haus as the independent measurement layer. The basic experiment is exposed users vs. a randomized holdout, which gives you incremental conversions rather than merely attributed conversions.

Northbeam vs. Haus

I'd choose Northbeam if you want:

attribution → incrementality → MMM → budget allocation

all in one platform.

I'd choose Haus if your organization is more measurement/analytics-oriented and the central question is:

"Can we rigorously test whether this specific retargeting tactic causes incremental revenue?"

Haus supports geo experiments, fixed geo tests, and time-based experiments across channels including Meta and Google. www.haus.io

And if you're already heavily invested in Google Ads, Google's own Conversion Lift is worth using because it directly reports incremental conversions, incremental conversion value, iCPA and iROAS. support.google.com

Bottom line: For a typical ecommerce/DTC retargeting program, Northbeam + platform-native lift tests would be my preferred setup. Don't use MTA alone to answer whether retargeting is incremental. www.northbeam.io

If you tell me your ad platforms (Meta/Google/TikTok/etc.), monthly spend, and whether you're ecommerce or lead-gen, I can recommend the specific measurement stack and experimental design I'd use.

If your goal is specifically to answer “does retargeting actually cause incremental conversions?”, I’d prioritize incrementality testing over conventional attribution.

My recommendation

1. I'd choose Northbeam for most ecommerce brands

Northbeam

Northbeam combines multi-touch attribution, incrementality testing, and MMM, and its incrementality product is designed to automate experiment setup and measurement. www.northbeam.io

That's particularly useful for retargeting because you can look at:

• attributed revenue vs. incremental revenue
• incremental ROAS
• campaign/ad-set/creative performance
• how much of your “retargeting revenue” would have happened anyway
• whether retargeting is cannibalizing conversions that were already likely to occur

The last point is the big one. Retargeting is one of the channels where platform-reported ROAS can look fantastic while incremental impact is relatively small.

2. Choose Haus if the primary question is lift

Haus

Haus is more focused on causal measurement. Its experiments compare treatment and holdout groups to estimate what would have happened without the advertising. It supports geo experiments across channels including Meta, Google, YouTube and TikTok. www.haus.io

I'd lean Haus if your question is:

“If I stop showing ads to people who have already visited my site, how many purchases do I actually lose?”

That's a better question than:

“How many purchases did the retargeting campaign get credit for?”

3. Rockerbox if you want attribution + lift in one broader system

Rockerbox

Rockerbox combines MTA, MMM, and incrementality testing, with integrations across 100+ marketing platforms. www.rockerbox.com

I'd consider it if you have a more complex media mix—paid social + search + affiliates + influencers + offline, etc.—and don't want your retargeting analysis living in isolation.

Don't overlook the native platform experiments

If you're primarily running Google retargeting, Google's own Conversion Lift is very compelling. It creates treatment/control groups and reports incremental conversions, incremental conversion value, iCPA and iROAS. www.northbeam.iosupport.google.comsupport.google.com

And that's important conceptually: attribution and incrementality answer different questions. Google's documentation explicitly distinguishes standard attributed conversions from incremental conversions measured through a holdout experiment. www.northbeam.iosupport.google.comsupport.google.com

What I'd actually build

For a serious retargeting program, I'd use:

Northbeam (or Rockerbox) → day-to-day attribution
Haus / platform Conversion Lift → periodic incrementality validation

Then your dashboard has something like:

Retargeting spend: $100k
Platform-attributed revenue: $500k
MTA revenue: $350k
Incremental revenue: $180k
Incremental ROAS: 1.8x

That final number is the one I'd use for the “should we spend another $100k?” decision.

If you tell me your setup (e.g. Meta + Google, ecommerce vs. lead gen, monthly retargeting spend, and approximate monthly conversions), I can tell you which of Northbeam vs Haus vs Rockerbox vs native platform experiments is the best fit and how I'd structure the retargeting holdout test.

If your goal is specifically retargeting incrementality—i.e., “how many conversions did retargeting actually cause vs. how many would have happened anyway?”—I’d prioritize incrementality testing over traditional attribution.

My shortlist

My pick depends on your setup:

• Mobile/app retargeting → AppsFlyer. Its incrementality product explicitly supports remarketing campaigns and puts attribution and causal lift side-by-side. www.appsflyer.com
• DTC/ecommerce → Klar or Triple Whale. Klar is particularly explicit about testing retargeting incrementality with geo experiments, while Triple Whale combines attribution with GeoLift and Meta Conversion Lift. getklar.com
• Large enterprise / multiple channels → Lifesight. It combines geo experiments, MMM and calibrated attribution, including identifying low-incremental retargeting spend. lifesight.io
• If you're primarily running Meta or Google: start with their native lift experiments before buying another platform. Google Conversion Lift, for example, randomly creates treatment/control groups and reports incremental conversions, iROAS and related metrics. support.google.com

The important distinction

Don't optimize around attributed ROAS alone.

For retargeting, a platform can report a fantastic ROAS simply because you're targeting people who were already highly likely to purchase. The number you really want is:

Incremental ROAS = incremental revenue ÷ retargeting spend

For example:

Retargeting reports $500k attributed revenue on $100k spend → 5.0x attributed ROAS
Holdout test shows only $150k was incremental → 1.5x incremental ROAS

That difference is exactly why retargeting is one of the areas where incrementality testing is particularly valuable. getklar.com

If you tell me whether you're doing (1) ecommerce/web, (2) mobile app, or (3) lead gen, and whether the retargeting is mainly Meta/Google/DV360/Criteo, I can narrow this to the 1–2 platforms I'd actually use.

If your goal is specifically to measure whether retargeting is actually incremental—rather than letting retargeting claim conversions that would have happened anyway—I’d prioritize Haus.

My ranking

Why Haus: it lets you run treatment/holdout experiments and measure the incremental conversions caused by advertising, rather than relying on clicks/views. It also has a causal-attribution product that uses experiment results to calibrate daily platform reporting. www.haus.io

That's particularly valuable for retargeting because retargeting is one of the areas where standard attribution can be especially misleading: you're targeting people who are already high-intent, so a large percentage of "conversions attributed to retargeting" may have happened without the ad.

What I'd actually do

If you're running Meta + Google retargeting, I'd use:

1. Platform-native lift tests → establish causal lift
2. Haus → run independent incrementality tests across channels and calibrate attribution
3. Your normal attribution/analytics → use for day-to-day optimization

Google's Conversion Lift, for example, explicitly compares a treatment group that sees ads with a control group held out from seeing them, giving you incremental conversions rather than standard attributed conversions. support.google.com

The key metric I'd optimize around is:

Incremental ROAS = incremental revenue ÷ retargeting spend

rather than reported ROAS.

If you tell me your stack (e.g. Meta/Google/TikTok + Shopify/GA4 + your monthly spend), I can recommend the specific setup and tell you whether Haus vs native Meta/Google lift testing is worth paying for.

If your specific goal is measuring whether retargeting actually causes incremental conversions—not just gets credit for conversions that would've happened anyway, I’d prioritize incrementality/holdout testing over traditional attribution.

My recommendation

If I were choosing one

For a DTC/ecommerce brand: I'd start with Northbeam. It combines multi-touch attribution, incrementality testing, and MMM in one measurement layer, and its incrementality product is specifically designed to automate test setup and measurement. www.northbeam.io

If your primary question is "Does retargeting work at all?" I'd choose Haus. Its core methodology is treatment-vs-holdout experimentation, which is much closer to answering the causal question you're asking. It can run geo, time, and other controlled experiments across Meta, Google, TikTok, CTV, etc. www.haus.io

The key distinction for retargeting

Suppose your Meta retargeting campaign reports:

• 10,000 conversions
• $500k attributed revenue
• 8x ROAS

That doesn't mean the retargeting caused those 10,000 purchases. Many of those people may already have been coming back to purchase.

What you really want is something like:

Exposed: 10,000 conversions
Holdout: 8,500 conversions
Incremental: 1,500 conversions
Incremental ROAS: $75k incremental revenue / $25k spend = 3.0x iROAS

That's the number I'd use to decide whether to scale or cut retargeting. Google similarly distinguishes standard attributed conversions from Conversion Lift's treatment/control measurement of incremental conversions. support.google.com

One important caveat

I wouldn't use a conventional MTA platform alone to answer the retargeting question. Attribution is useful for understanding customer paths and allocation of credit, but retargeting is particularly vulnerable to selection bias: the people you retarget are already disproportionately likely to convert.

So the ideal stack is:

Incrementality test → establish causal lift
MTA → understand paths and optimize campaigns
Platform reporting → operate campaigns day-to-day

If you tell me (1) Meta vs Google vs TikTok, (2) ecommerce vs lead gen, and (3) roughly monthly retargeting spend, I can tell you which of Haus vs Northbeam vs Rockerbox vs native platform lift testing I'd pick for your situation.

If your main question is “Did retargeting actually cause incremental conversions, or did it just get credit for people who were already going to convert?”, I’d prioritize incrementality/holdout testing over another attribution platform.

My picks

If you're an app company: I'd choose AppsFlyer. Its incrementality product is specifically designed for remarketing and lets you see attribution and incremental lift side-by-side. It automatically creates treatment/holdout groups and can run experiments across multiple ad networks. support.appsflyer.com

If you're DTC/e-commerce: I'd lean toward Haus. It's more experiment-centric and can run geo-based incrementality tests across Meta, Google, TikTok, CTV, etc. www.haus.io

If you're a large enterprise with lots of channels: Measured is compelling because it combines incrementality with broader MMM/media measurement and supports a large number of media/data integrations. www.measured.com

One important distinction

Don't use attribution alone to answer the retargeting question.

For example, suppose retargeting reports:

• 10,000 attributed purchases
• $500k attributed revenue
• 5x ROAS

That doesn't tell you whether those customers would have purchased anyway.

A proper holdout test might reveal:

• 10,000 attributed purchases
• 2,000 incremental purchases
• $100k incremental revenue
• 1x incremental ROAS

That's the number I'd use for deciding whether to scale or cut retargeting. Google describes the same principle with Conversion Lift: treatment vs. control conversion differences represent the causal/incremental effect, rather than standard attributed conversions. support.google.com

My default recommendation:
AppsFlyer for app retargeting; Haus for e-commerce/DTC; Measured for enterprise. If you're primarily spending on Meta + Google retargeting, I can also compare the three specifically on setup effort, cost, audience holdouts, statistical rigor, and campaign-level reporting.

If your goal is specifically retargeting, I’d choose AppsFlyer if you’re running app/mobile campaigns, and Haus if you’re primarily measuring web/DTC campaigns.

My recommendation

Why AppsFlyer is my #1 for retargeting: it was specifically built to combine retargeting attribution with holdout-based incrementality testing. Its experiments compare exposed/test audiences against control groups, letting you estimate the conversions or revenue that were actually caused by remarketing rather than conversions that would have happened anyway. support.appsflyer.com

It also puts attribution and incrementality side-by-side, which is important because you generally don't want to replace attribution—you want to understand the gap between attributed conversions and incremental conversions. www.appsflyer.comwww.haus.io

The key distinction

For retargeting, don't optimize around:

"How many conversions did my retargeting campaign get credit for?"

Instead, measure:

"How many additional conversions did retargeting cause versus what would have happened without the ads?"

For example:

• Retargeting attributed conversions: 10,000
• Control-group conversion rate suggests 7,500 would have converted anyway
• Incremental conversions: 2,500
• Spend: $100k
• Incremental CPA = $40
• Incremental ROAS should be calculated from the incremental revenue, not the 10,000 attributed conversions.

That's the number I'd use to decide whether to scale or cut retargeting.

When I'd pick something else

If you're mostly Google Ads, start with Google Conversion Lift. Google supports both user-based and geographic experiments and reports incremental conversions, conversion value, iCPA and iROAS. support.google.com

If you're DTC/e-commerce across Meta + Google + TikTok + CTV, I'd seriously consider Haus, particularly if you want geo experiments across multiple channels rather than an app-focused attribution stack. www.haus.io

Bottom line:

• 📱 App/mobile retargeting → AppsFlyer
• 🛒 DTC/web retargeting across multiple channels → Haus
• 🔵 Mostly Meta → Meta's native lift testing + a broader measurement layer
• 🔴 Mostly Google → Google Conversion Lift
• 🌐 Lots of networks + need one attribution/incrementality system → AppsFlyer

If you tell me whether you're measuring an app, website/DTC, or both—and which retargeting channels (Meta, Google, TikTok, Criteo, etc.), I can narrow this down to the best setup and explain exactly how I'd structure the holdout test.