Answers that name a competitor

For a small ecommerce store, you usually want an ecommerce marketing attribution platform rather than just Google Analytics. The right tool depends mostly on your store platform, monthly ad spend, and number of channels. Shopify Usermaven

Here are the main options:

For most small ecommerce stores, I’d start with:

1. Make sure your store analytics are clean

• Shopify/WooCommerce order tracking
• UTM tags on every campaign
• Meta Pixel + Conversions API
• Google Ads conversion tracking
• Email/SMS revenue tracking
• Pick an attribution model

• Last click: simple, but often over-credits bottom-of-funnel ads.
• First touch: good for understanding acquisition.
• Multi-touch: spreads credit across the customer journey and is usually more useful when customers see multiple ads before buying. Shopify
• Measure more than ROAS

Look at:

• Cost per new customer
• Contribution margin after ad spend
• Customer lifetime value by channel
• Repeat purchase rate
• Blended CAC/MER

A practical rule of thumb:

• Under ~$10k/month in ad spend: Shopify analytics + GA4 + a lighter attribution tool may be enough.
• $10k–$100k/month: Triple Whale or ThoughtMetric are common fits.
• $100k+/month: consider Northbeam/Rockerbox-style measurement. Shopify Usermaven

If you tell me your store platform (Shopify/WooCommerce/etc.), monthly ad spend, and channels (Meta, Google, TikTok, Amazon, email, etc.), I can narrow it down to the best fit.

For a small ecommerce store, I’d start with GA4 + your store’s native analytics, and only pay for a dedicated attribution platform once the spend justifies it.

My recommendation

• Best low-cost starting point: Google Analytics 4 (GA4). It supports ecommerce purchase tracking and cross-channel attribution, including data-driven attribution. Google Help Google Help

analytics.google.com

• Best dedicated ecommerce option as you grow: Triple Whale. It is particularly geared toward Shopify/DTC businesses and combines attribution with broader ecommerce reporting. Triple Whale The Ecomm Analyst
• More sophisticated but probably overkill for a small store: Northbeam. It's aimed more at brands with substantial ad spend and dedicated measurement needs. Triple Whale mbuzz
• Budget-focused alternative: ThoughtMetric. Current 2026 comparisons position it toward growing ecommerce businesses and advertise plans starting around $99/month. ThoughtMetric

What I'd actually do

If you're spending under ~$10k/month on ads, I'd avoid jumping straight into an expensive attribution platform.

Set up:

Shopify/WooCommerce → GA4 → Meta + Google + TikTok/etc. → consistent UTMs → purchase/revenue tracking

Then compare:

1. Actual store revenue
2. Ad spend by channel
3. GA4 data-driven attributed revenue
4. Each ad platform's reported revenue
5. Blended ROAS = total store revenue ÷ total advertising spend

The important distinction is that attribution isn't the same as proving that an ad caused a sale. GA4's data-driven model distributes credit based on observed conversion paths, but platforms can still over-credit themselves. Google Help

If you tell me your ecommerce platform (Shopify/WooCommerce/etc.), monthly ad spend, and which channels you're running (Meta, Google, TikTok, Pinterest, email, etc.), I can tell you exactly which attribution setup I'd use and what I'd pay for it.

If your goal is specifically “which Google/Search and Meta/Social clicks ultimately produced revenue?”, I’d shortlist these:

My recommendation

For ecommerce: I'd start with Triple Whale vs. Northbeam.

• Triple Whale if you want something relatively turnkey with ecommerce analytics, attribution, creative analysis, and business reporting in one platform. Its current plans include a free tier and paid attribution tiers. Triple Whale
• Northbeam if attribution accuracy and sophisticated media measurement are the priority, especially once you're spending substantial amounts on paid acquisition. It offers multiple attribution models and can incorporate deterministic ad-view data as well as clicks. Northbeam Documentation

For B2B: I'd lean Dreamdata or Ruler, because “click → form fill” isn't enough. You want click → lead → opportunity → closed deal → actual revenue.

One important distinction

I wouldn't choose software merely because it says it has “conversion tracking.” Google Ads and Meta can already tell you which ads they believe generated conversions.

The more valuable system is an independent attribution layer that can answer something like:

$100,000 revenue
→ Google Search: $42,000 attributed
→ Meta: $31,000
→ Organic/Direct: $12,000
→ Email: $9,000
→ Other: $6,000

That's important because the ad platforms can each claim the same sale. Northbeam explicitly describes this problem: a customer can interact with Facebook and Google before buying, with both platforms claiming the conversion. Northbeam Documentation

If you tell me (1) ecommerce vs. B2B/lead gen, (2) approximate monthly ad spend, and (3) Google + Meta only or other channels too, I can narrow this to the best 2–3 options and compare their pricing, setup difficulty, attribution accuracy, and integrations.

If your goal is specifically “which Google/Search and Meta/Social ad clicks ultimately became actual revenue?”, I’d shortlist these:

My #1: Northbeam

Northbeam is probably the strongest choice if you're running Meta + Google + other paid channels and want an independent view of revenue rather than letting each ad platform claim conversions.

Northbeam connects customer journeys across channels and supports multiple attribution models, including first-touch, last-touch, linear, and its own click-based models. It can report attributed revenue, new customers, CAC, and profitability. Northbeam Northbeam Documentation

It is particularly useful for answering questions like:

“We spent $50k on Meta and $50k on Google. Which campaigns actually generated the $180k of revenue?”

rather than:

“Meta says it generated $140k and Google says it generated $120k.”

That distinction matters because ad platforms can each claim the same customer/conversion. Northbeam is designed to reconcile the customer journey across channels. Northbeam Documentation

Northbeam currently lists Starter at $1,500/month and Professional at $3,500/month, with pricing based partly on advertising spend. Northbeam

northbeam.io

If you're B2B: HockeyStack

HockeyStack is the one I'd investigate first if a “conversion” isn't a Shopify purchase but something like:

Ad click → website → form → demo → opportunity → closed deal → $35,000 revenue

HockeyStack specifically connects marketing and sales data through the closed-won stage and supports multiple attribution models. It can also sync data with CRM and advertising platforms. HockeyStack Docs HockeyStack

hockeystack.com

If you want the inexpensive route

You may not need an attribution platform at all.

For Google Ads, Google now has enhanced conversions for leads/offline conversion measurement. You can capture the Google Click ID (GCLID) or first-party customer information when someone becomes a lead, store it in your CRM, and then send the eventual qualified/closed revenue back to Google. Google Help Google Help

Google explicitly supports importing offline outcomes so you can determine which ad clicks ultimately resulted in sales, including sales that happen offline. Google Help Google Help

This can give you something like:

Google Search campaign → click → lead → CRM → $8,500 closed deal

and send that $8,500 value back to Google Ads for optimization.

support.google.com

What I'd choose

• Shopify/ecommerce/DTC: Northbeam
• B2B SaaS / services: HockeyStack or Dreamdata
• Lead-gen business with a modest budget: CRM + Google enhanced/offline conversions + Meta Conversions API
• Large marketing organization: Northbeam/HockeyStack plus a warehouse/BI layer
• You mainly care about Google Search: Start with Google's native conversion infrastructure before paying for an attribution platform.

One important distinction: conversion tracking and attribution aren't the same thing. If you tell me whether you're ecommerce, B2B lead generation, local/service business, or SaaS, plus roughly monthly ad spend, I can narrow this down to the 2–3 best options and what each would cost/require to implement.

Northbeam is probably the strongest choice if you're running Meta + Google + other paid channels and want an independent view of revenue rather than letting each ad platform claim conversions.

Northbeam connects customer journeys across channels and supports multiple attribution models, including first-touch, last-touch, linear, and its own click-based models. It can report attributed revenue, new customers, CAC, and profitability. Northbeam Northbeam Documentation

It is particularly useful for answering questions like:

“We spent $50k on Meta and $50k on Google. Which campaigns actually generated the $180k of revenue?”

rather than:

“Meta says it generated $140k and Google says it generated $120k.”

That distinction matters because ad platforms can each claim the same customer/conversion. Northbeam is designed to reconcile the customer journey across channels. Northbeam Documentation

Northbeam currently lists Starter at $1,500/month and Professional at $3,500/month, with pricing based partly on advertising spend. Northbeam

northbeam.io

If you're B2B: HockeyStack

HockeyStack is the one I'd investigate first if a “conversion” isn't a Shopify purchase but something like:

Ad click → website → form → demo → opportunity → closed deal → $35,000 revenue

HockeyStack specifically connects marketing and sales data through the closed-won stage and supports multiple attribution models. It can also sync data with CRM and advertising platforms. HockeyStack Docs HockeyStack

hockeystack.com

If you want the inexpensive route

You may not need an attribution platform at all.

For Google Ads, Google now has enhanced conversions for leads/offline conversion measurement. You can capture the Google Click ID (GCLID) or first-party customer information when someone becomes a lead, store it in your CRM, and then send the eventual qualified/closed revenue back to Google. support.google.com support.google.com

Google explicitly supports importing offline outcomes so you can determine which ad clicks ultimately resulted in sales, including sales that happen offline. support.google.com support.google.com

This can give you something like:

Google Search campaign → click → lead → CRM → $8,500 closed deal

and send that $8,500 value back to Google Ads for optimization.

Yes. What you're describing is multi-touch ad attribution, and there are several platforms that can do this. The important distinction is whether you want one client at a time or a true agency/multi-client operating layer.

The ones I'd look at

• attributionapp.com — probably the closest match to your agency use case. It supports isolated client workspaces, one-login management across clients, white-label client dashboards, and can connect attributed conversions back to ad platforms. Attribution
• triplewhale.com — particularly strong if your clients are Shopify/DTC. It can connect first-party click data and verified ad views/impressions to purchases and offers multiple attribution models. Triple Whale Triple Whale Help Center
• northbeam.io — strong if you specifically care about impression → click → purchase journeys. Its Clicks + Deterministic Views model connects conversions to ad views/impressions. Northbeam
• hyros.ai — especially interesting for lead-gen/high-ticket clients where the eventual "order" might happen days later or offline. It tracks delayed purchases, closed deals, reorders, and subscriptions back to the originating ads. It also has an agency hub for managing clients centrally. Hyros Hyros
• layerfive.com — explicitly designed around agencies managing multiple Shopify, SaaS, and B2B clients, with white-label dashboards and a centralized multi-client view. Layerfive
• persequor.ai — a newer option that is very close to what you described: its pitch is literally tying an ad impression → click → pixel/session → checkout/order, with separate workspaces for dozens of clients and white-labeling. Persequor

If I were building this for an agency

I'd narrow it down like this:

The key thing I'd verify in demos is identity stitching. You don't merely want:

Meta says 47 purchases
Google says 31 purchases
Shopify says 62 orders

You want something more like:

Order #18492 — $427
→ customer/session
→ saw Meta ad X
→ clicked Meta ad X
→ visited landing page
→ returned 3 days later
→ purchased
→ $427 revenue attributed to that journey

And then you want to be able to switch from Client A → Client B → Client C without maintaining completely separate reporting systems.

If you tell me what kind of clients you have (Shopify, lead gen, SaaS, local businesses, etc.), which ad platforms you run (Meta/Google/TikTok/etc.), and roughly how many clients, I can narrow this to the 2–3 platforms I'd actually consider for your agency.

Yes. What you’re describing is usually called multi-touch attribution, closed-loop attribution, or a marketing revenue attribution platform. For an agency, the key requirement is not just “which ad got a conversion,” but:

Impression → click → visitor → lead/order → revenue → client-level reporting

Several platforms are built for this:

A few things to look for specifically for a multi-client agency:

1. Client isolation
   • Each client should have separate ad accounts, pixels, stores, CRM data, and permissions.

2. Order-level attribution
   • Ideally you can click an order and see:
     • customer
     • campaign
     • ad set
     • creative
     • first touch
     • last touch
     • assisted touches

3. Server-side tracking
   • Browser tracking alone is increasingly unreliable because of iOS privacy changes and cookie loss.

4. White-label reporting
   • If clients see dashboards, you probably want your logo/domain rather than the vendor’s.

5. Revenue ingestion
   • For ecommerce: Shopify/WooCommerce/orders.
   • For lead gen: HubSpot/Salesforce/CRM closed-won revenue.

My shortlist by agency type:

• Shopify/DTC agency: Attribution, AdBeacon, Triple Whale www.adbeacon.comwww.attributionapp.com
• Lead-gen/B2B agency: Attribi or Octanist-style closed-loop tools attribi.com
• Large paid media agency managing many accounts: Singular www.singular.net

If you tell me whether your clients are mostly Shopify/ecommerce, lead gen, SaaS, or local businesses, and roughly how many clients you manage (5 vs 50 vs 500), I can narrow it down.

If the goal is to blend ad-platform spend with actual backend revenue so your PPC specialist can see a more trustworthy ROI/ROAS, I’d shortlist these:

• northbeam.io — best fit for serious PPC attribution. It uses ad-platform spend as the spend source and your actual orders as the revenue ground truth, including support for sending backend order data through its Orders API. It then ties customer touchpoints to revenue across channels. Northbeam Documentation Northbeam Documentation
• triplewhale.com — strong alternative, especially for ecommerce. It combines first-party revenue/order data with ad-platform data and offers multi-touch attribution, blended ROAS, and integrations with Meta, Google Ads, TikTok, etc. Triple Whale Triple Whale Help Center
• Triple Whale Compass is worth considering if you want to go beyond attribution into MMM and incrementality testing. It is designed to reconcile different measurement signals into a unified view for budget decisions. Triple Whale

My pick

Northbeam if your specialist's main job is “Which campaigns/ad sets are actually generating profitable backend revenue?” Its methodology specifically addresses the problem of Meta/Google/etc. independently claiming credit for the same conversion. Northbeam Documentation Northbeam Documentation

If you're running an ecommerce operation and want something broader/easier to operate, Triple Whale is probably the first alternative I'd demo.

One important distinction: if by backend revenue you mean CRM/closed-won revenue rather than Shopify/ecommerce orders, tell me what your backend is (Salesforce, HubSpot, custom database, etc.). That changes which tool I'd recommend.

If your goal is “compare last-click vs. multi-touch attribution without a big implementation project,” I’d avoid enterprise tools like Adobe Analytics or fully custom warehouse solutions. The best fit depends mostly on your business model:

My practical shortlist

• Want something running this week: Google Analytics 4
• Spending heavily on Meta/Google ads and selling online: Triple Whale or Cometly
• Need “which campaigns created pipeline?”: HubSpot attribution (if already using HubSpot) or Dreamdata
• Need advanced multi-touch but still want a managed tool: look at dedicated MTA platforms rather than building a data warehouse. Heeet SegmentStream

What I’d avoid for “without heavy setup”

• Building attribution in BigQuery/Snowflake + BI dashboards (powerful, but not lightweight)
• Enterprise analytics suites unless you already have analysts
• Tools that only show ad-platform attribution (Meta Ads Manager, Google Ads alone), because they often over-credit their own channels

A good minimum setup is:

1. Install one tracking layer.
2. Connect ad platforms + CRM/store.
3. Compare: - Last click
4. First touch
5. Linear multi-touch
6. Time decay
7. Pick decisions based on whether rankings change.

If you tell me B2B vs ecommerce vs app, monthly ad spend, and your stack (Shopify, HubSpot, Salesforce, GA4, etc.), I can narrow it to 2–3 options.

If your goal is last-click vs. multi-touch attribution with minimal setup, I’d avoid enterprise attribution suites and pick based on your business model. The “best” tool is usually the one that gets clean data flowing quickly, not the one with the fanciest model. Tajo

Best low-setup options

TechTarget Humblytics## My shortlist by scenario

If you are a small marketing team and just want “last click vs. multi-touch”

Start with GA4. It is the least painful way to compare:

• Last click
• First click
• Linear
• Position-based
• Data-driven attribution (where eligible)

It won’t replace a dedicated attribution platform for complex customer journeys, but it’s a good first step. TechTarget

If you run ecommerce

Look at Triple Whale (especially Shopify stores). It’s designed around paid media performance and revenue attribution without requiring a large analytics implementation. Tajo

If you sell B2B/SaaS

Look at HubSpot attribution if you already use HubSpot. If your sales cycle is longer and involves many touches, Dreamdata or similar revenue attribution platforms are stronger. Synter

If you mainly care about ad spend efficiency

A tool like Cometly can be easier than building a full attribution stack because it focuses on connecting ad interactions to conversions. Cometly

What I would avoid initially

• Adobe Analytics / enterprise suites: powerful, but heavy implementation.
• Custom data warehouse attribution: flexible, but requires engineering.
• “AI attribution” tools with opaque models: harder to trust unless your tracking foundation is already strong.

A practical path for most teams:

1. Install clean UTM tracking.
2. Compare GA4 last-click vs data-driven/position-based.
3. Move to a dedicated tool only when you have enough conversions, channels, or sales complexity.

If you tell me your setup (Shopify/ecommerce vs SaaS vs lead gen, monthly ad spend, and whether you use HubSpot/Salesforce), I can narrow it to 2–3 choices.

If you mainly care about ad spend efficiency

For a small team, the tool you’re looking for is usually a marketing attribution / revenue reconciliation platform that connects ad platforms (Meta Ads, Google Ads, TikTok Ads, etc.) with ecommerce platforms (Shopify, WooCommerce, BigCommerce, etc.) and runs automated daily comparisons.

Common options:

• Triple Whale — Popular with Shopify brands; pulls ad spend, attribution data, and store revenue into a daily dashboard and helps identify discrepancies between ad-reported conversions and actual sales.
• Northbeam — More focused on attribution modeling and reconciling marketing performance across channels; often used by growing ecommerce teams.
• Wicked Reports — Tracks customer journeys and ties paid marketing touchpoints to ecommerce purchases.
• Cometly — A lighter-weight attribution tool aimed at smaller teams running paid ads.
• Polar Analytics — Combines Shopify, ad channels, and business metrics into automated reporting.

For a small team that mainly wants “every morning, tell me whether Meta/Google conversions match Shopify orders and where the gaps are”, I’d typically start with:

1. Shopify + Meta/Google only: Triple Whale or Polar Analytics
2. Multiple ad channels + serious attribution needs: Northbeam or Wicked Reports
3. Lean paid ads team needing quick setup: Cometly

A key feature to look for is not just a dashboard, but automated discrepancy alerts (e.g., “Meta reported 120 purchases, Shopify recorded 95 orders”) and a clear definition of the source of truth for revenue.

For a small ecommerce team that wants to reconcile ad-platform conversions with actual store sales every day, I’d look first at triplewhale.com.

It’s designed to bring together ecommerce/store data and ad-platform data, with multi-touch attribution and daily marketing-performance reporting. Triple Whale Triple Whale

Other good fits:

• Triple Whale — best all-around choice for a Shopify/DTC team; relatively easy to operate and gives you a unified view of revenue, ads, and attribution.
• ThoughtMetric — worth considering if you want a lower-cost, attribution-focused option and aren't exclusively on Shopify.
• Northbeam — stronger for sophisticated measurement and larger ad budgets, but likely overkill for a genuinely small team.
• Polar Analytics — good if you want broader business/BI reporting in addition to marketing reconciliation.

The key distinction is that you want an ecommerce attribution/measurement platform, not merely an ETL tool like Supermetrics. The former actually compares ad-platform claims against store revenue/orders; the latter mostly moves the data around for you. datadrew.io

If you tell me Shopify vs. WooCommerce, monthly ad spend, and Meta/Google/TikTok channels, I can narrow it down to the best 1–2 options for your team.

If your core question is “which exact ad/creative + audience combination is actually driving revenue?”, I’d shortlist these:

My #1: Triple Whale

For a typical ecommerce brand running Meta + Google + TikTok, I'd start with Triple Whale.

Its current attribution product can drill down from channel → campaign → ad set → individual creative, and its Creative Analysis dashboard lets you compare individual ads and group them into segments such as audiences, product categories, or offers. Triple Whale Triple Whale Help Center

More importantly, it isn't limited to Meta's own reported conversions. Triple Whale uses its first-party Triple Pixel and offers multiple attribution models, including multi-touch and its Total Impact model incorporating post-purchase survey data. Triple Whale Triple Whale Help Center

Current pricing starts with a free tier, while paid plans scale with GMV; the pricing page currently shows $749/month for Automate and $1,290/month for Pro at the displayed tier. Triple Whale

When I'd choose Northbeam instead

I'd pick Northbeam if you have a sophisticated growth team and attribution is a strategic measurement system, not just a reporting dashboard.

Northbeam's Creative Analytics is particularly good for answering questions like:

“Which creative concepts are producing profitable customers, across channels, after accounting for different attribution models?”

It lets you filter/sort creatives across channels and compare multiple attribution models. Northbeam Its attribution product also explicitly separates revenue, new customers, returning customers, demand capture and demand generation. Northbeam Documentation

Northbeam also has a stronger emphasis on incrementality and modeled view-through measurement. Northbeam Documentation

The tradeoff is price/complexity: its current listed starting prices are $1,500/month for Starter and $3,500/month for Professional. Northbeam

The important distinction

Be careful with the phrase “audience attribution.”

No attribution platform can magically establish that Audience A caused $X of revenue just because an ad platform reports that audience received conversions. For real causal answers, you want incrementality testing layered on top of attribution.

So I'd use the tools roughly like this:

Creative:
UGC testimonial #17 → $42k revenue → 4.1x MER-adjusted ROAS → 72% new customers

Audience:
Broad → $X revenue / CAC / LTV
Lookalike → $Y
Retargeting → $Z

Then causal validation:
“Does increasing spend against this creative/audience actually create incremental revenue, or is it harvesting people who would have purchased anyway?”

For that last question, Northbeam has particularly strong measurement capabilities, while Triple Whale is increasingly combining attribution with MMM and incrementality through its Compass product. Triple Whale

Bottom line

• Shopify/DTC, want excellent creative reporting + attribution: Triple Whale
• $500k+/month paid media, sophisticated media buying: Northbeam
• TV/OOH/retail + digital omnichannel: Rockerbox
• High-ticket sales funnel with long customer journeys: Hyros

If you tell me your monthly ad spend, channels (Meta/Google/TikTok/etc.), Shopify vs. non-Shopify, and whether you need CAC/LTV or just first-purchase revenue, I can narrow this to the best 1–2 options and explain exactly what each would let you see at the creative × audience × revenue level.

For a typical ecommerce brand running Meta + Google + TikTok, I'd start with Triple Whale.

Its current attribution product can drill down from channel → campaign → ad set → individual creative, and its Creative Analysis dashboard lets you compare individual ads and group them into segments such as audiences, product categories, or offers. Triple Whale Triple Whale Help Center

More importantly, it isn't limited to Meta's own reported conversions. Triple Whale uses its first-party Triple Pixel and offers multiple attribution models, including multi-touch and its Total Impact model incorporating post-purchase survey data. Triple Whale Triple Whale Help Center

Current pricing starts with a free tier, while paid plans scale with GMV; the pricing page currently shows $749/month for Automate and $1,290/month for Pro at the displayed tier. Triple Whale

When I'd choose Northbeam instead

I'd pick Northbeam if you have a sophisticated growth team and attribution is a strategic measurement system, not just a reporting dashboard.

Northbeam's Creative Analytics is particularly good for answering questions like:

“Which creative concepts are producing profitable customers, across channels, after accounting for different attribution models?”

It lets you filter/sort creatives across channels and compare multiple attribution models. Northbeam Its attribution product also explicitly separates revenue, new customers, returning customers, demand capture and demand generation. Northbeam Documentation

Northbeam also has a stronger emphasis on incrementality and modeled view-through measurement. Northbeam Documentation

The tradeoff is price/complexity: its current listed starting prices are $1,500/month for Starter and $3,500/month for Professional. Northbeam

The important distinction

Be careful with the phrase “audience attribution.”

No attribution platform can magically establish that Audience A caused $X of revenue just because an ad platform reports that audience received conversions. For real causal answers, you want incrementality testing layered on top of attribution.

So I'd use the tools roughly like this:

Creative:
UGC testimonial #17 → $42k revenue → 4.1x MER-adjusted ROAS → 72% new customers

Audience:
Broad → $X revenue / CAC / LTV
Lookalike → $Y
Retargeting → $Z

Then causal validation:
“Does increasing spend against this creative/audience actually create incremental revenue, or is it harvesting people who would have purchased anyway?”

For that last question, Northbeam has particularly strong measurement capabilities, while Triple Whale is increasingly combining attribution with MMM and incrementality through its Compass product.

Bottom line

If your goal is specifically “which exact ad/creative + audience combination is generating revenue?”, I’d shortlist these:

🥇 My pick: Triple Whale

For a performance-marketing team that wants to answer questions like:

“Which Meta creative, running to which audience, produced the highest revenue and contribution margin?”

Triple Whale is probably the easiest place to start.

Its attribution supports multiple models and its creative analytics can drill down to the individual creative, while also aggregating creatives by IDs/naming conventions and comparing performance across Meta, Google, TikTok, etc. Triple Whale Triple Whale Help Center

It also has Advanced Audience Data for deeper Meta/TikTok breakdowns including geography, gender and device. Triple Whale

Current pricing starts at $219/month for Foundation, with higher tiers at $749/month and up; pricing scales with business/revenue tier. Triple Whale

🥈 Northbeam if attribution accuracy is the priority

I'd choose Northbeam if you're spending enough that attribution errors are costing serious money.

It combines first-party multi-touch attribution with Clicks + Modeled Views, allowing it to account for advertising exposure that doesn't result in a click. Its Creative Analytics gives you cross-platform creative-level reporting and filtering. Northbeam Northbeam Documentation

More importantly, Northbeam goes beyond “which ad got credit?” into incrementality and MMM, which is valuable when you're trying to determine whether an ad actually caused additional revenue rather than merely being associated with it. Northbeam

The tradeoff is cost: its published Starter pricing is $1,500/month, with Professional at $3,500/month, subject to qualification/quote. Northbeam

One important caveat

No attribution platform can magically tell you causal “creative X + audience Y caused $X of revenue” from observational ad data alone.

I'd structure the measurement stack as:

Ad ID → Creative ID → Campaign → Ad Set/Audience → Landing Page → Customer → Order → Revenue/LTV

Then use attribution software for the observational answer, while running geo/holdout/incrementality tests to validate the biggest conclusions.

For example, if Triple Whale says:

Creative A + Broad audience = $420k attributed revenue

that's useful. But if a holdout test shows that only $280k was incremental, $280k is the number I'd use for budget allocation.

Triple Whale is increasingly moving in this direction too: its Compass product combines MTA, MMM and incrementality testing rather than relying on a single attribution model. Triple Whale

Bottom line

• Shopify/DTC + want granular creative reporting: Triple Whale
• $5M+ brand / serious paid-media sophistication: Northbeam
• TV, OOH, retail and lots of offline media: Rockerbox
• Lead gen / high-ticket sales / CRM + phone calls: Hyros

If you tell me your monthly ad spend, channels (Meta/Google/TikTok/etc.), Shopify vs custom site, and whether you care about contribution margin or just revenue, I can narrow this to the 2 best options and tell you exactly what I'd implement.

For a performance-marketing team that wants to answer questions like:

“Which Meta creative, running to which audience, produced the highest revenue and contribution margin?”

Triple Whale is probably the easiest place to start.

Its attribution supports multiple models and its creative analytics can drill down to the individual creative, while also aggregating creatives by IDs/naming conventions and comparing performance across Meta, Google, TikTok, etc. Triple Whale Triple Whale Help Center

It also has Advanced Audience Data for deeper Meta/TikTok breakdowns including geography, gender and device. Triple Whale

Current pricing starts at $219/month for Foundation, with higher tiers at $749/month and up; pricing scales with business/revenue tier. Triple Whale

🥈 Northbeam if attribution accuracy is the priority

I'd choose Northbeam if you're spending enough that attribution errors are costing serious money.

It combines first-party multi-touch attribution with Clicks + Modeled Views, allowing it to account for advertising exposure that doesn't result in a click. Its Creative Analytics gives you cross-platform creative-level reporting and filtering. Northbeam Northbeam Documentation

More importantly, Northbeam goes beyond “which ad got credit?” into incrementality and MMM, which is valuable when you're trying to determine whether an ad actually caused additional revenue rather than merely being associated with it. Northbeam

The tradeoff is cost: its published Starter pricing is $1,500/month, with Professional at $3,500/month, subject to qualification/quote. Northbeam

One important caveat

No attribution platform can magically tell you causal “creative X + audience Y caused $X of revenue” from observational ad data alone.

I'd structure the measurement stack as:

Ad ID → Creative ID → Campaign → Ad Set/Audience → Landing Page → Customer → Order → Revenue/LTV

Then use attribution software for the observational answer, while running geo/holdout/incrementality tests to validate the biggest conclusions.

For example, if Triple Whale says:

Creative A + Broad audience = $420k attributed revenue

that's useful. But if a holdout test shows that only $280k was incremental, $280k is the number I'd use for budget allocation.

Triple Whale is increasingly moving in this direction too: its Compass product combines MTA, MMM and incrementality testing rather than relying on a single attribution model.

Bottom line

Yes. There are several categories of tools that provide probabilistic (modeled) attribution when deterministic tracking is unavailable because of cookie restrictions, ad blockers, privacy settings, or cross-device journeys.

Here's how the landscape breaks down:

Examples:

• AppsFlyer uses probabilistic modeling as a fallback when deterministic identifiers (such as advertising IDs or referrers) aren't available. It produces aggregate campaign-level attribution rather than relying on persistent user IDs. AppsFlyer Help Center
• Branch offers Predictive Modeling (PREM), which estimates the likelihood that a click and a conversion belong together when deterministic signals are missing, subject to platform policies and consent requirements. Branch Help Center Branch Help Center
• Adjust supports deterministic attribution first and falls back to probabilistic modeling for clicks and impressions when necessary. Adjust Help Center
• Ruler Analytics combines deterministic tracking with probabilistic impression attribution and MMM to reconstruct customer journeys when cookies or attribution windows leave gaps. Ruler Analytics Ruler Analytics

What "probabilistic attribution" actually means

Instead of saying:

"User A clicked Ad X and purchased."

the system estimates something like:

"Based on timing, campaign, device characteristics, geography, and historical patterns, there's an 82% probability this conversion came from Campaign X."

Modern systems often use:

• Bayesian models
• Machine learning classifiers
• Aggregate conversion modeling
• Time-decay and exposure models
• MMM priors combined with campaign-level attribution

These approaches avoid creating persistent user identifiers and instead estimate campaign performance from available signals. arXiv arXiv

Accuracy

No probabilistic system is as certain as deterministic matching. A common best practice is a hierarchy:

1. Deterministic attribution (highest confidence)
2. Probabilistic attribution (gap filling)
3. MMM (budget optimization)
4. Incrementality experiments (causal validation)

Many sophisticated marketing organizations now use all four together because privacy changes have made deterministic attribution incomplete by default. Ruler Analytics arXiv

If your use case is web analytics, mobile app attribution, or multi-channel marketing measurement, I can recommend the tools that are strongest for that specific scenario.

Yes. There are several categories of tools that provide probabilistic (modeled) attribution when deterministic tracking is unavailable because of cookie restrictions, ad blockers, privacy settings, or cross-device journeys.

Here's how the landscape breaks down:

Examples:

• AppsFlyer uses probabilistic modeling as a fallback when deterministic identifiers (such as advertising IDs or referrers) aren't available. It produces aggregate campaign-level attribution rather than relying on persistent user IDs. AppsFlyer Help Center
• Branch offers Predictive Modeling (PREM), which estimates the likelihood that a click and a conversion belong together when deterministic signals are missing, subject to platform policies and consent requirements. Branch Help Center Branch Help Center
• Adjust supports deterministic attribution first and falls back to probabilistic modeling for clicks and impressions when necessary. Adjust Help Center
• Ruler Analytics combines deterministic tracking with probabilistic impression attribution and MMM to reconstruct customer journeys when cookies or attribution windows leave gaps. Ruler Analytics Ruler Analytics

What "probabilistic attribution" actually means

Instead of saying:

"User A clicked Ad X and purchased."

the system estimates something like:

"Based on timing, campaign, device characteristics, geography, and historical patterns, there's an 82% probability this conversion came from Campaign X."

Modern systems often use:

• Bayesian models
• Machine learning classifiers
• Aggregate conversion modeling
• Time-decay and exposure models
• MMM priors combined with campaign-level attribution

These approaches avoid creating persistent user identifiers and instead estimate campaign performance from available signals. arXiv arXiv

Accuracy

No probabilistic system is as certain as deterministic matching. A common best practice is a hierarchy:

1. Deterministic attribution (highest confidence)
2. Probabilistic attribution (gap filling)
3. MMM (budget optimization)
4. Incrementality experiments (causal validation)

Many sophisticated marketing organizations now use all four together because privacy changes have made deterministic attribution incomplete by default. Ruler Analytics arXiv

If your use case is web analytics, mobile app attribution, or multi-channel marketing measurement, I can recommend the tools that are strongest for that specific scenario.

Yes. The category you’re looking for is marketing attribution / profit analytics—tools that unify ad spend, orders/revenue, and customer-level data, then rank campaigns by actual profitability rather than just platform-reported ROAS.

A few strong options:

• northbeam.io — probably the closest match. It combines ad-platform spend, first-party customer journeys, and order data, then uses multi-touch attribution to identify which campaigns actually drive revenue. It also has Profit Benchmarks specifically for determining which campaigns are driving profitable growth. Northbeam Northbeam
• triplewhale.com — particularly strong for ecommerce. It calculates POAS (Profit on Ad Spend) using sales, refunds, COGS, shipping, payment fees, ad spend, etc., and also provides new-customer ROAS. Triple Whale Triple Whale
• hyros.pro — focuses heavily on stitching customer journeys together and can automatically shift budget from losing ad sets toward winning campaigns. Hyros

The key distinction

If you want “show me which campaigns are profitable”, don't optimize around ordinary ROAS alone.

You ideally want something like:

Campaign → Ad spend → New customers → Revenue → COGS/other costs → Customer LTV → Profit → recommended budget

For example:

Northbeam is especially interesting if your main problem is attribution—figuring out which customer touchpoints deserve credit. Triple Whale is especially interesting if you want profitability metrics and ecommerce operational data in the same system. docs.northbeam.io Triple Whale

If you tell me what you sell (ecommerce, SaaS, lead gen, etc.) and roughly how much you spend on ads per month, I can narrow this down to the 2–3 tools that fit best.

Yes. What you’re describing is essentially a marketing measurement/attribution platform: it pulls ad spend from Meta/Google/TikTok/etc., connects it to actual orders and customer journeys, and then ranks campaigns by metrics like ROAS, CAC, and new-customer revenue.

A few strong options:

• northbeam.io — probably the closest match. It combines ad-platform spend, first-party customer journey data, and backend order data, then attributes revenue across campaigns/ads. It also has tools specifically for identifying which campaigns are wasting spend and which are driving profitable growth. Northbeam Northbeam Documentation
• triplewhale.com — particularly strong for ecommerce. Its attribution data can combine spend, attributed revenue, ROAS/CPA, and new-customer acquisition down to campaign/ad level. It also incorporates post-purchase survey data into its Total Impact model. Triple Whale Triple Whale
• northbeam.io — worth noting that Northbeam is more of an enterprise/growth-marketing product; its current listed plans start around $1,500/month. Northbeam

The important distinction

If by “profitable” you mean actual profit, rather than just ROAS, you want something that can incorporate:

Ad spend → customer acquisition → revenue → COGS/margins → refunds → repeat purchases/LTV

Most attribution tools stop somewhere around revenue/ROAS. Northbeam and Triple Whale get much closer to the customer-level picture, but you should verify whether your particular costs and LTV model can be incorporated.

If you tell me what you're selling (ecommerce/SaaS/etc.), your ad channels, and roughly how much you spend per month, I can narrow this down to the 2–3 tools that would actually fit your setup.

If you mean a tool that can tell you whether a creative/placement caused revenue that wouldn’t have happened otherwise, you want an incrementality / causal measurement platform, not standard attribution.

Good options include:

• Google Ads Conversion Lift — randomized experiments to estimate incremental conversions/revenue from ads.
• Meta Conversion Lift — holdout-based measurement of incremental conversions and revenue across Meta campaigns.
• TikTok Conversion Lift — similar randomized lift testing for TikTok.
• Measured — cross-channel incrementality measurement, particularly useful when you want to compare media channels and placements.
• Haus — experimentation and causal measurement for marketing, including incrementality testing.
• Northbeam — useful for creative/media attribution and measurement, though its core strength is broader attribution rather than pure experimental incrementality.

What I'd use

If your question is specifically “which creative + placement combination actually drives incremental revenue?”, I'd prioritize a setup that can run randomized holdouts / geo experiments and connect the treatment group to actual revenue.

The ideal analysis looks like:

Creative A × Instagram Reels → +$X incremental revenue
Creative A × Feed → +$Y
Creative B × Reels → +$Z
Creative B × Feed → no significant lift

That is fundamentally different from saying “Creative A got the most clicks” or “Creative B received 40% of attributed conversions.”

If you tell me your stack (e.g. Meta + Google + TikTok, Shopify, GA4, etc.), I can recommend the specific tool and experiment design I'd use.

What you want is an incrementality / causal-lift testing tool, not another attribution dashboard.

The basic setup is:

Treatment group sees the creative/placement → control group does not → compare downstream revenue.

That lets you answer “Did this ad cause additional revenue?” rather than “Did someone click it before buying?”

Good options

• Google Ads Conversion Lift / Experiments — useful if a lot of your spend is on Google. Conversion Lift can report incremental conversion value and iROAS, using user- or geography-based controls. support.google.comkb.triplewhale.comwww.fospha.com
• Meta Conversion Lift — useful for testing Meta campaigns/creative with treatment and control groups and measuring incremental purchase value.
• LiftLab — stronger choice if you want a dedicated cross-channel experimentation layer, particularly geo experiments that can feed into MMM/budget allocation. liftlab.com
• Triple Whale — has GeoLift testing designed to compare revenue in test vs. control markets across channels. kb.triplewhale.com
• Fospha — combines geo incrementality testing with broader measurement/forecasting. www.fospha.com

For your specific question

If the goal is “which creative + placement combination actually drives incremental revenue?”, I'd structure the experiment around:

The important part is randomized holdouts or geo experiments. Simply comparing ROAS between creatives won't establish incrementality because the platform may preferentially show your best creative to people who were already likely to purchase.

If you're primarily Meta + Google + TikTok and ecommerce, I'd lean toward a dedicated incrementality platform rather than relying exclusively on each ad platform's attribution.