Triple Whale vs Northbeam vs Nexus (2026): Attribution Compared, and What Comes Next
Triple Whale is the faster, all-in-one Shopify-native dashboard with pixel-based multi-touch attribution. It is best for teams that want blended ROAS and daily performance in one place. Northbeam is the deeper measurement engine, using multi-touch attribution plus marketing mix modeling. It is best for higher-spend, multi-channel teams with analytical resources. Both answer where a sale came from. Neither answers which customer segment deserves the next dollar, or what to do about it. That is the layer Nexus by Omniconvert adds on top.
- Pick by monthly ad spend. Below roughly $100K a month Triple Whale's speed and price usually win; above $250K a month across several channels Northbeam's MTA-plus-MMM approach earns its higher fee.
- Triple Whale runs pixel-based multi-touch attribution across seven models. It degrades when consent is refused, blockers fire, or the journey crosses devices, because a pixel can only credit what it observed.
- Northbeam adds marketing mix modeling on Bayesian and time-series methods, so it survives tracking loss. The trade is that it smooths: it is directional, it needs history, and it needs someone who can read a confidence interval.
- Your two dashboards will disagree, often by enough to change a budget decision. That is the honest state of post-privacy measurement, and a holdout test settles it faster than a third attribution tool.
- Both tools stop at the conversion. Nexus by Omniconvert consumes attribution as an input, then ranks the next experiment by profit impact, generates the creative, and reports True Profit after COGS, shipping, returns and fees.
Most brands shortlist these two after the same experience: three ad platforms reporting three different numbers, none of which match Shopify. Triple Whale and Northbeam both fix that, but they fix it at different depths and different price points, and the right pick is largely decided by your monthly media spend. This page compares them on attribution method, cost, and fit, explains why their numbers will still disagree with each other, and then covers the question neither tool was built to answer.
What is Triple Whale, and what is it actually good at?
Triple Whale is a Shopify-native attribution and analytics platform. It runs pixel-based multi-touch attribution with seven attribution models, blended ROAS reporting, an all-in-one real-time dashboard, and the Moby AI assistant. Tiered pricing runs from roughly $129 to $500-plus a month by revenue. It is used by tens of thousands of DTC brands and holds a 4.5 out of 5 rating on G2. [G2, 2026]
Triple Whale became the default for Shopify brands for a simple reason. After the iOS privacy changes, platform-reported conversions stopped agreeing with each other and with Shopify. Media buyers needed one number they could defend in a budget meeting, and Triple Whale gave them one quickly.
The product's centre of gravity is the daily allocation decision. Spend, orders, revenue, and blended ROAS sit on one screen, refreshed during the day rather than the next morning. The pixel is well built, and the Shopify integration needs no engineering work.
The breadth is part of the appeal too. Attribution, summary dashboards, creative reporting, and an AI assistant arrive as one purchase, which suits a small team that does not want three tools.
Multi-touch attribution assigns credit for a conversion across the marketing touchpoints that preceded it, using tracked user-level events. It is precise when the tracking holds and it degrades when it does not, because consent refusals, blockers, and cross-device journeys remove touchpoints from the path.
Where Triple Whale is strong
- Shopify-native setup: installed and reporting the same day, with no data team involved.
- All-in-one surface: attribution, dashboards, and creative reporting in one place.
- Seven attribution models: first click through to data-driven, switchable per view.
- Real-time reporting: intraday spend and revenue for same-day budget calls.
- Accessible pricing: roughly $129 to $500-plus a month, tiered by revenue.
What is Northbeam, and what is it actually good at?
Northbeam is a platform-agnostic measurement engine. It combines multi-touch attribution with marketing mix modeling, using Bayesian and time-series methods that stay usable when user-level tracking is lost. It is built for teams spending upwards of $250K a month, published pricing runs roughly $1,000 to $2,500-plus a month, and it serves 1,000-plus enterprise brands. [Northbeam, 2026]
Northbeam answers the same question with more machinery. Where a pixel-only model breaks when touchpoints disappear, a mix model works from aggregate spend and outcome patterns over time, so it keeps producing a defensible answer under privacy loss.
The trade is rigour against effort. Mix models need history, they need care in setup, and they reward someone on the team who can read a confidence interval without flinching. That is why Northbeam's fit starts where analytical resources exist.
Being platform-agnostic matters at that spend level too. Brands running Amazon, retail, connected TV, and offline alongside Meta and Google need a measurement layer that does not assume Shopify is the whole business.
Marketing mix modeling estimates the contribution of each channel by fitting a statistical model to aggregate spend and outcome data over time. It needs no user-level tracking, so it survives privacy restrictions. It is directional rather than exact, and it needs enough history to separate signal from seasonality.
Where Northbeam is strong
- MTA plus MMM together: two methods cross-checking one another rather than one fragile model.
- Resilient to tracking loss: Bayesian and time-series modeling that survives iOS-era signal decay.
- Platform-agnostic: built for multi-channel brands, not Shopify alone.
- Built for scale: designed around teams spending upwards of $250K a month.
- Analyst-grade output: incrementality framing rather than a single headline ROAS.
Both competitor columns on this page reflect publicly available product documentation as of August 2026.
Triple Whale vs Northbeam vs Nexus: the capability comparison
Pick by ad spend first. Below roughly $100K a month, Triple Whale's speed and price usually win. Above $250K a month across several channels, Northbeam's MTA-plus-MMM approach earns its higher fee. The third column is not a third attribution tool. It is what happens after the attribution report is read.
| Capability | Triple Whale | Northbeam | Nexus by Omniconvert |
|---|---|---|---|
| Core job | All-in-one dashboard and attribution | Deep multi-touch plus MMM attribution | Growth engine that acts on attribution |
| Attribution method | Pixel-based MTA: seven models | MTA plus MMM: Bayesian and time-series | Consumes both: as input signals |
| Best-fit ad spend | Lower to mid | $250K a month and up | Any: sits above the attribution layer |
| Pricing | About $129 to $500-plus a month | About $1,000 to $2,500-plus a month | Subscription, founding-brand terms |
| Platform scope | Shopify-native | Platform-agnostic | Shopify-native: with paid channel activation |
| Customer intelligence (RFM, CLV, churn) | Partial CLV view | Not the focus | Yes: native Customer Intelligence layer |
| Turns insight into a brief | No | No | Yes: CLV to RFM to named segment to brief |
| Generates and launches creative | No | No | Yes: human-approved before launch |
| Builds ad audiences from RFM | No | No | Yes: pushed to Meta and Google |
| Experiment prioritization | No | No | Yes: ranked by profit impact |
| True Profit after COGS, shipping, returns, fees | ROAS and blended reporting | Measurement, not profit action | Yes: CLV-weighted, per campaign |
| Data heritage | Attribution dataset | Attribution dataset | 13 years, 7,000+ websites, 70,000 experiments |
| User rating | No public G2 rating | No public G2 rating | 5.0 out of 5 (Shopify App Store, 60 reviews, as of September 2026) |
Why your Triple Whale and Northbeam numbers will not match
The two tools disagree because they measure differently, not because one is broken. Triple Whale reads tracked user-level paths through its own pixel. Northbeam blends that with a model fitted to aggregate spend and outcomes. Different lookback windows and different credit rules produce different answers from the same week.
Teams that run both in parallel during an evaluation almost always find a gap, and it is often large enough to change a budget decision. That is uncomfortable, but it is the honest state of measurement after the privacy changes.
A pixel model can only credit what it observed. When consent is refused or the journey crosses devices, the touchpoint is missing and the credit lands somewhere else, usually on the last channel that was visible.
A mix model has the opposite failure mode. It never loses a channel, because it works from spend and outcome patterns, but it smooths. It is directional, it needs history, and it will not tell you which specific ad set drove Tuesday.
Use the pixel view for same-day decisions inside a channel, and the model view for quarterly allocation across channels. When the two diverge sharply on one channel, treat that channel as the thing to test rather than the thing to trust. A holdout test settles the argument faster than a third tool will.
Treat neither attributed-revenue figure as revenue. Use the pixel view inside a channel and the model view across channels, and reconcile both against Shopify's own order total.
What Triple Whale and Northbeam cannot do
Triple Whale and Northbeam are both in the measurement business. They tell you what happened, with different levels of rigour. Neither decides which segment to acquire, writes the brief, generates the creative, launches the campaign, or measures the result in True Profit. Keep whichever attribution tool fits your spend. Nexus by Omniconvert is the action layer above it.
Attribution ends at the conversion. That is not a criticism, it is the definition. Whichever model you pick, the output is a credit assignment for a sale that already happened.
The question that decides next quarter sits one level up: which customers are worth acquiring, and what should we run to get more of them? Answering it needs repeat-purchase behaviour, CLV by cohort and source, RFM position, and churn signal. None of that lives in an attribution model, because none of it is a touchpoint.
The measurement gap follows the same line. A campaign can post a strong ROAS in either tool and still lose money once COGS, shipping, returns, and payment fees are counted, and lose more if the customers it brought in never return.
True Profit is revenue minus COGS, shipping, returns, and payment fees, attributed per campaign, per ad, and per product, then weighted by the lifetime value of the customers acquired. Attribution answers where the sale came from. True Profit answers whether it was worth having.
- Which customers are worth acquiring. Both tools credit a sale that already happened. Neither ranks customers by lifetime value, cohort, or churn risk, because none of those is a touchpoint.
- What to run next. Attribution ends at the conversion. Neither produces a prioritised queue of experiments ordered by expected profit.
- Whether the campaign was worth having. A strong ROAS in either tool can still be a loss once COGS, shipping, returns, and payment fees land, and a bigger loss if those customers never return.
- Which of the two views to believe. Neither sits above the other, so reconciling a pixel model against a mix model is left to a person and a holdout test.
- How to turn the answer into launched work. Neither builds an audience, writes a brief, generates creative, or launches anything.
What Nexus adds on top of either tool
- Customer intelligence: CLV, RFM segmentation, cohorts, churn risk, and NPS, maintained continuously.
- Attribution as an input: your existing measurement feeds the decision rather than ending it.
- Segment to brief to creative: a named segment becomes a brief, then ad and email variants for approval.
- Audience activation: RFM segments pushed to Meta and Google as custom and lookalike audiences.
- Ranked experiments: a queue ordered by expected profit impact, drawn from 70,000 experiments.
- True Profit reporting: CLV-weighted margin per campaign, ad, and product.
Which tool is right for you?
Pick by monthly ad spend first, then by whether anyone on the team owns analytics. Nexus by Omniconvert is not the third option in that decision. It is the layer you add once the attribution question is settled.
- Choose Triple Whale if you are Shopify-native, spending under roughly $100K a month, and nobody on the team owns analytics. Speed of setup and price are the deciding factors, and a mix model has little history to work with at that volume.
- Choose Northbeam if you are spending upwards of $250K a month across several channels, including places a pixel cannot see, and someone on the team can read a confidence interval. The higher fee is repaid by avoiding a few points of misallocation.
- Choose Nexus by Omniconvert if the attribution report is already on the screen and nothing happens next. Nexus takes CLV, RFM, cohorts, churn risk and NPS, ranks the next experiment by profit impact, generates the creative, and reports True Profit after costs.
- Run attribution plus Nexus if you want the measurement you trust to feed a decision rather than end one. Nexus consumes attribution as an input and does not replace it.
Deciding by monthly ad spend
| Monthly ad spend | Usual answer |
|---|---|
| Under $50K | Triple Whale. Northbeam's fee and setup effort are hard to justify, and a mix model has little to work with at this volume. |
| $50K to $250K | Either, decided by team rather than by tool. Triple Whale if nobody owns analytics. Northbeam if someone does and the channel mix is widening. |
| Above $250K | Northbeam. At this spend a few points of misallocation cost more than the price difference, and MMM handles the channels a pixel cannot see. |
What each tool cannot do, honestly
Every tool on this page has a real boundary, including ours. Buying the wrong one for the wrong job is the expensive mistake, so here is where each one stops.
- Triple Whale degrades with the tracking. A pixel model can only credit what it observed. Consent refusals, blockers, and cross-device journeys remove touchpoints from the path, and the credit lands on the last channel that was still visible.
- Triple Whale is Shopify-shaped. That is why setup is fast, and it is also why brands running Amazon, retail, connected TV, or offline outgrow it.
- Northbeam smooths. A mix model never loses a channel, but it is directional rather than exact. It needs history, it needs care in setup, and it will not tell you which specific ad set drove Tuesday.
- Northbeam has a floor. The fee and the setup effort are hard to justify below roughly $250K a month in spend, and below $50K there is not enough signal for the model to separate from seasonality.
- Neither one executes. Both are measurement products. Neither builds an audience, writes a brief, generates creative, or launches a campaign, and neither claims to.
- Nexus by Omniconvert is not an attribution tool. It does not run multi-touch modelling or marketing mix modelling, so it does not replace either product on this page. It consumes their output as an input signal.
- Nexus does not launch without you. Creative is generated and campaigns are queued, but a human approves before anything goes live.
This is deliberately complementary. Brands running paid budgets should keep the attribution tool that fits their spend. For the two-way view, see Triple Whale vs Nexus, or read the wider argument in what an AI eCommerce growth engine actually does.
Nexus is now onboarding founding brands. See current plans on the Nexus pricing page.
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Which should you choose?
Triple Whale is best for fast, all-in-one Shopify attribution at lower to mid spend. Northbeam is best for rigorous multi-channel measurement at high spend. Nexus by Omniconvert is the growth engine that turns either one's output into CLV-weighted, profit-measured action.
Both tools are worth their price to the brand that fits them, and the choice between them is mostly arithmetic: below roughly $100K a month of media, Triple Whale; above roughly $250K across several channels, Northbeam; in between, decided by whether anyone on the team owns analytics.
What neither purchase changes is the week after. The report still has to become a decision about which customers to chase, a brief, a set of assets, a launch, and a margin number. That work is where growth compounds or stalls, and it is the reason attribution and action are two different layers rather than two versions of the same tool.
Attribution ends at the sale.
Growth starts after it.
Nexus unifies your entire eCommerce data layer, ranks the next action by profit impact, generates the creative, and reports True Profit after COGS, shipping, returns and fees, so the attribution report becomes a decision instead of a dashboard.
5.0 out of 5 across 60 reviews, Shopify App Store , as of September 2026