Shopify Attribution Tools,
Compared.

Elevar, Triple Whale, Northbeam and Analyzify each price on a different axis: order volume times destinations, store GMV, traffic volume, and a flat annual fee. The same Shopify store therefore receives quotes an order of magnitude apart. Which tool is cheapest depends on which axis your store happens to sit high on.

Almost every comparison of these four tools is a feature grid. Feature grids are close to useless here, because all four will happily tell you they do server-side tracking, multi-touch attribution and Meta Conversions API delivery. What actually separates them — and what determines whether you pay a few hundred dollars a year or twenty thousand — is the unit each one meters.

Four Tools, Four Different Pricing Axes

This is the single most important thing to understand before you request a quote from any of them. The four tools do not merely charge different amounts. They charge for different things. One meters orders, one meters revenue, one meters traffic, and one meters nothing month to month and simply invoices once a year.

Entry points above are third-party reported and pending verification against each vendor's own pricing page.

The consequence is the useful part. Two stores with identical ad spend can receive quotes an order of magnitude apart, purely because of which axis they happen to sit high on. A high-traffic, low-average-order-value store — think a fast-moving consumables brand with a lot of browsing and a small basket — is punished hard by traffic-based pricing, because it generates enormous event volume for modest revenue. Flip it around: a low-traffic, high-average-order-value store, the sort selling a small number of expensive items to a narrow audience, is punished by GMV-based pricing, because it books a lot of revenue on very few sessions. And a store that sends its events to six or seven ad platforms is punished by destination-count pricing regardless of how many orders it takes, because the destination list is a second meter running alongside the first.

None of this shows up on a feature comparison. It only shows up when the quotes arrive and they are four figures apart for no reason anyone can immediately explain.

One Store, Four Very Different Quotes

Take a single hypothetical store and price it four ways. Assume 5,000 orders a month and roughly $500,000 in monthly GMV — an average order value around $100, which is an ordinary shape for a mid-sized direct-to-consumer brand. It is one store. Here is what it costs, using the reported figures:

All four figures in this table are third-party reported and pending verification. They are illustrative of the shape of the difference, not quotes.

The spread across that table is roughly twenty-four to one, top to bottom, for one store on one day. That is not a quality gradient. It is four companies metering four different quantities and one store that happens to sit differently on each meter. Before you compare features, work out which meter you are expensive on — it will tell you more about your eventual bill than any capability list will.

Three Open Price Conflicts

Three of the figures used on this page are contradicted by another source. Rather than pick the number that reads best and present it as fact, all three are set out here so you know precisely where the ground is soft. Each is pending resolution against the vendor's own pricing page.

1. Elevar's plan structure — two incompatible descriptions. One source reports a ladder of named tiers priced on orders and destinations. A separate source, published three months earlier, reports an entirely different structure: $200 at 1,000 orders, $450 at 10,000 and $950 at 50,000, with per-order overages of $0.15, $0.04 and $0.03 respectively. These are not two readings of the same price list; they are two different price lists. Only one can be current.
2. Northbeam's floor — $1,500 or $1,000. The tracked record on this site puts the floor at the higher of the two, verified against the vendor's own pricing page. A third-party source puts it a third lower. That gap is large enough to change whether the tool is even in consideration for a store at the margin.
3. Analyzify's billing basis — annual or monthly. This is the messiest of the three. A reported annual fee and the monthly figure carried in this site's own app records do not reconcile as the same plan. Both may well be true — vendors routinely sell a monthly plan and a discounted annual plan side by side — but until it is confirmed, any comparison that mixes the two is comparing different products. Wherever this page quotes a figure for that vendor, it states the billing basis explicitly.

Elevar — The Tracking Pipeline

First, a corporate note that matters. Elevar has been sold through Audiense since July 2025, and the Shopify App Store listing now reads "Elevar by Audiense". If you are searching for documentation, pricing or support and finding two brand names, that is why. The product name has been retained as a sub-brand rather than retired, so both names appear across the vendor's own material. Anyone renewing a contract should confirm which entity they are contracting with.

How the pricing works. Two meters run at once: how many orders you process, and how many destinations you send events to. Destinations means ad platforms and analytics endpoints — Meta, Google, TikTok, Pinterest, a warehouse, and so on. Adding a channel can move you up a tier even if your order count has not moved an inch. This is unusual, and it is the single most common way people are caught out, because nobody expects switching on one more ad platform to change their subscription price.

Ladder as third-party reported, pending verification — and directly contradicted by a second source, as set out in the conflicts section above. The entry price tracked in this site's app record was verified against the vendor's own pricing page and carries a source link.

What only this tool does

Session Enrichment. This is the genuine differentiator, and none of the other three offer an equivalent. It stitches events, sessions and channel attribution together so that a returning anonymous visitor can be recognised across separate visits, and their behaviour connected into a single thread rather than three unrelated ones. For a store with a long consideration cycle — where somebody browses on Tuesday, reads reviews on Thursday and buys the following week — that stitching is the difference between three orphaned sessions and one attributable journey.

Two supporting capabilities are worth naming. The first is a managed server-side GTM container: the tagging infrastructure is provisioned and maintained as part of the product rather than left as an exercise for you. The second is a Chrome-extension event builder, which lets you define custom events by clicking elements on your storefront instead of editing theme code — genuinely useful if the person defining events is a marketer rather than a developer.

On positioning: it is a Shopify preferred partner for checkout extensibility, is reported to power tracking for over 6,500 direct-to-consumer brands, and holds a 4.6 rating from 138 App Store reviews. That is a real install base, not a startup.

Where it concretely falls short

• There is infrastructure to run. Because it is built on server-side GTM, there is a Google Cloud tagging server in your stack to provision, monitor and pay for. That is a real operational surface, and it is the only one of these four that adds one.
• Advanced configuration needs real GTM knowledge. The out-of-the-box container covers standard events well. Anything bespoke requires someone who genuinely understands tag manager, or paying for setup services on top of the subscription.
• Destination count is a pricing lever. Worth repeating because it is so unusual: adding an ad platform can raise your bill. Budget for the destinations you will want in twelve months, not the ones you have now.
• Communication around breaking changes. There are reported gaps in advance notice when tracking behaviour changes — which, for a component sitting in the path of your revenue data, is a meaningful risk to plan around.

Who it genuinely suits: stores where the tracking pipeline itself is the problem — events arriving late, incompletely or not at all — with in-house or agency GTM capability to exploit it, and roughly $5,000 a month or more in ad spend to justify the line item. If your problem is that you cannot read your data, this is the wrong tool; it moves data, it does not interpret it.

Triple Whale — The Operator Dashboard

How the pricing works. Tiers are set by store GMV, so the bill tracks revenue. The reported entry tier begins around $129 a month, and a separate source cites a figure closer to $179 a month on annual billing for the dashboard tier — a minor discrepancy, but note it. The tier that matters is the Professional plan, reported at $749 a month, which is where full media mix modelling and the advanced BI features unlock. No figure in this paragraph has yet been verified against the vendor's own page.

The single most useful warning on this page: the entry tier excludes creative analytics, customer journey reporting and the survey-based features. Those are, for most buyers, the actual reasons to buy the product. It is entirely possible to sign up at the advertised entry price, discover that none of the things you wanted are included, and end up on a plan roughly six times more expensive. Price the tier that contains the features you came for, not the tier on the pricing page headline.

What only this tool does

A Shopify-native first-party pixel combined with post-purchase surveys. The surveys are the distinctive part: at checkout, the customer is asked directly where they heard about you, and that self-reported answer is blended with the pixel data. It is the only one of the four that collects a signal the ad platforms cannot see at all, because it comes from the customer's mouth rather than from a cookie. For channels that are structurally invisible to click-based attribution — podcast reads, influencer mentions, word of mouth — it is often the only evidence you will ever get.

The right mental model: this is an ecommerce operating dashboard with attribution inside it, not a tracking pipeline. People open it every morning. That is a different product category from the other three, and it is why comparing it feature-for-feature against a data-delivery tool produces nonsense.

Where it concretely falls short

• The entry tier is hollowed out. As above — creative analytics, journey reporting and surveys all sit above it. This is the most consequential thing to know before buying.
• The "Total Impact" model has been criticised for over-counting. A customer who clicks a Meta ad and then a Google search ad can have both channels credited in certain views. The result is a report where the channel contributions sum to more than the revenue actually earned, which produces confidence that is not warranted by the data.
• Blended CAC, not per-channel CAC. You get a customer acquisition cost for the business, not a defensible one per channel. If your question is "should I move budget from Meta to TikTok", a blended number cannot answer it. This is a real and specific limitation against Northbeam.

Who it genuinely suits: Shopify-first direct-to-consumer operators who want one dashboard to open each morning and a number to run the day from. Below roughly $30,000 a month in paid media, the honest recommendation is the free plan — the paid tiers are priced for stores whose media decisions are large enough that a percentage point of improvement covers the subscription.

Northbeam — The Measurement Layer

How the pricing works. This is the one that is priced on traffic and data volume rather than on revenue, which catches people out in the opposite direction from everything else here. Two stores earning identical revenue can be quoted very differently if one of them generates three times the pageviews. Contracts are annual. The reported starter floor sits around $1,500 a month, scaling to roughly $2,500 for the starter band, and the vendor generally does not sell below approximately $500,000 in monthly GMV. As flagged earlier, one source disputes that floor and puts it a third lower.

What only this tool does

The Clicks + Deterministic Views model. Server-side ingestion feeds a multi-touch attribution engine that credits view-through conversions deterministically rather than inferring them — which is the substantive distinction, because view-through is where most attribution tooling quietly resorts to modelling and hopes nobody asks. Media mix modelling is available on the upper tiers for the channels that have no click at all.

It also reports per-channel customer acquisition cost. That sounds mundane until you try to make a budget reallocation decision with a blended figure and find you cannot. Per-channel CAC is precisely what Triple Whale does not give you, and it is the clearest functional line between the two.

Where it concretely falls short

• The price floor excludes most Shopify stores outright. This is not a criticism of the product so much as a statement of who it is for. For the large majority of stores, the conversation ends at the first number.
• It is analyst-led. The models need somebody whose actual job is to use them. Bought by a lean team with no analyst, the depth is dead weight — an expensive dashboard nobody has time to interrogate.
• Annual contracts, no monthly escape. If it turns out to be wrong for you in month three, you are still paying in month eleven.
• It does not work as a Shopify-only stack. The other three are comfortable being the whole of a Shopify store's tracking setup. This one assumes a multi-channel media mix around it, and delivers proportionally less value without one.

Who it genuinely suits: brands north of $10 million in annual revenue running multi-channel mixes that include TV, podcast or influencer spend, with an analyst on staff. If you buy media across channels that do not produce clicks, this is the category of tool built for that problem.

Analyzify — GA4, Done For You

How the pricing works. Uniquely among the four, the headline figure is annual rather than monthly, reported at $749 to $945 per year with caps set by order volume; the top reported tier covers up to 10,000 orders a month. Spread across twelve months that is roughly $62 to $79 — an order of magnitude below everything else on this page. Note the conflict flagged earlier: this site's own app record carries a monthly figure that does not reconcile with the annual one, and until that is resolved you should confirm the billing basis before comparing it to anything.

What only this tool does

Done-for-you setup, included at no extra cost. Managed onboarding, migration and professional implementation are bundled into the fee rather than sold as a services add-on. That is the actual product. It is a service wrapped in an app, and the fee is best understood as buying an implementation, not a subscription. Every other tool here sells you software and leaves the configuration to you or your agency.

Technically, it adds more than ten events and parameters that GA4 does not capture natively on Shopify — collection views, coupon codes, variant IDs — which are exactly the dimensions you find yourself missing the first time you try to answer a real merchandising question in GA4.

Where it concretely falls short

The 99% purchase-tracking accuracy claim measures capture rate, not data quality. This deserves unpacking, because it is the most quietly misleading number in this whole category. The claim is that 99% of purchase events are captured. That is a statement about delivery. It says nothing whatsoever about what those events contain. Bot purchases are captured at 99% accuracy. Synthetic sessions are captured at 99% accuracy. Proxy traffic is captured at 99% accuracy. The figure is entirely accurate about what it measures, and entirely misleading about what most merchants assume it means — which is "99% of my analytics data is correct". A high capture rate on dirty input produces a high-fidelity record of dirty input.

• It is GA4-centric. The value proposition is a correctly configured GA4. If GA4 is not your reporting layer — if you live in a BI tool or in the ad platforms — most of that value evaporates.
• The true cost is often higher than the fee. It is commonly paired with Stape hosting for the server-side container, which can push genuine annual cost past $3,000. The headline annual figure is the software, not the setup.
• The reviewer base skews small-business. Worth weighing when reading ratings: the population rating it is not the population running complex multi-channel measurement.

Who it genuinely suits: teams with no in-house analytics capability who want GA4 configured properly once and then left alone. If the honest description of your situation is "we know our tracking is wrong and nobody here can fix it", the bundled implementation is worth more than any feature on the list.

The Four Side By Side

Entry row: third-party reported, pending verification. Three of these vendors have a verified entry price recorded in the app pricing index, each with its own source link and date.

When the Free CAPI Shield Route Is Better

The honest framing is that three of these four are not really competing with CAPI Shield at all, and pretending otherwise would be the easiest way to make this page untrustworthy.

Northbeam and Triple Whale are measurement and reporting layers. They exist to tell you what worked — to model, attribute and display. A free event-delivery pipeline does not do that and never will. If what you need is a daily operating dashboard, buy the dashboard. If what you need is a media mix model with per-channel CAC and deterministic view-through, buy the measurement platform. Neither of those problems is solved by getting events to Meta more reliably, and anyone telling you otherwise is selling something.

The overlap is with the other two. Elevar and Analyzify are both, at bottom, about getting events reliably to Meta Conversions API, GA4 and the rest of the destination list. That is exactly what CAPI Shield does, at $0 a month, using Make.com's free tier and no code. The platform endpoints themselves — Meta Conversions API, Google Enhanced Conversions, the TikTok Events API — are free to call. Nobody sells privileged access to them. What the paid tools sell around those endpoints is the configuration interface, the monitoring, the onboarding and somebody to call.

So the trade is specific and worth stating plainly. The free route costs you setup time and ongoing ownership: you build the connection, you watch it, and when a payload shape changes you are the one who notices. The paid route costs money and buys convenience, monitoring and support — plus, in Elevar's case, Session Enrichment, which the free route genuinely does not replicate, and in Analyzify's case, somebody else doing the implementation.

A reasonable decision rule: if your events are not arriving and you have the capacity to own a small integration, start free and see whether the delivery problem was the whole problem. If it was, you have solved it for nothing. If it was not — if the real problem turns out to be that you cannot tell which channel earned the sale — then you were shopping in the wrong category anyway, and Northbeam or Triple Whale is where that conversation belongs.

• → CAPI Shield — free Meta and Google server-side tracking via Make.com, no code.
• → Attribution gap calculator — size the discrepancy before you buy anything to fix it.
• → Meta EMQ score estimator — check event match quality first; poor matching is often the real fault.
• → App pricing index — the tracked price record for each vendor, with source and date.

Common Questions

Verification status: figures on this page marked reported come from third-party comparison sources and have not yet been confirmed against the vendors' own pricing pages. They are published as reported claims, not as fact. Three entry prices — recorded in the app pricing index with a verification date and a source link — were read from the vendor's own page and are the only figures on this page carried into structured data. Three price conflicts remain open and are set out above rather than resolved silently. Our sourcing standard is described in how we test. Vendors change prices without notice — re-check before making a purchasing decision.

Written by Luke Sandelands Verified Author

Founder, Stack Architect · Shopify Automation Specialist

Developer of StockLog and author of the open-source shopify-capi-validator npm package. Certified in Shopify server-side tracking, Meta CAPI, and Google Apps Script engineering.