Pay-Per-Use vs Subscription Attribution: the Honest Comparison

Pay-Per-Use vs Subscription Attribution: the Honest Comparison

It is the 15th of the month. You haven't opened that dashboard in nine days. You are not even sure anyone on the team has.

Quick answer. pay per use attribution vs subscription is the question almost every ecommerce CMO under €5M revenue eventually asks out loud: am I paying enterprise rates for a question I could answer for less? The honest answer, based on a wide read of G2 reviews, Trustpilot reports, and independent agency write-ups (see Triple Whale on G2, Northbeam on G2), is yes, very often.

What the public reviews actually say

The pattern across G2, Trustpilot, and independent agency reviews is consistent. Below that line, several independent voices have started warning brands off:

• Triple Whale on G2 captures the user-level pain (billing surprises, support escalations, attribution still wrong months in).
• Northbeam on G2 adds the structural cost angle (entry pricing that doesn't pencil for leaner teams).

The structural reason is straightforward. These tools were built for enterprise data volumes. They need volume to train their models. They charge subscription pricing because they are continuously running infrastructure on your behalf. None of that is unreasonable when the math works. It just doesn't work for a lot of the brands signing up.

How the math actually shapes up

The math gets less brutal. Marginal.

There is no shame in being on the lower side of this curve. Most ecommerce brands are. The shame is paying for the model that was built for someone else.

Where the lock-in actually bites

Annual contracts compound the price problem. 5k on long-term agency contracts lays out the agency version of the same trap and the conclusion travels: you are asked to commit twelve months before you have any evidence the tool is going to pay back. Rockerbox on G2 notes the related Rockerbox pattern - full value tends to land "towards the end" of the contract year, which is exactly when you have already paid for it.

The result, as Triple Whale on G2 reviews repeatedly show, is brands paying for months of subscription while still trying to debug why the dashboard disagrees with Shopify or with the ad platforms.

When the tool is pay-per-use, several things change at once:

• You can run the analysis on a specific period - last month, last quarter, the launch window, the campaign that already ended.
• You can run it once and stop.
• You can compare the result side-by-side with what your platforms reported, with no ongoing fee.
• You can come back only if you want continuous attribution later.

FAQ

Is there a free tier? Several incumbents offer a free tier with limited features. Triple Whale's free tier covers basic dashboards. The catch, per Triple Whale on G2, is that the paid attribution features - pixel, multi-touch, longer lookback - start at four-figure annual costs.

What about Hyros for smaller brands?

Yes - any vertical, any size, any historical period. GA4 is the only data input required today. Native Shopify integration is on the roadmap, not a prerequisite.

What if I want continuous attribution later? Cancellable at any time.

Will the €99 pay back? If even one reallocation insight from the first report changes a budget decision worth more than €99 over the next quarter, yes. Most reports surface several.

You already have your data. It is sitting in your GA4 property right now. Any historical period, any vertical, any size. Here is the actual workflow:

1. Open GA4. Export your data as a CSV. Any window - last month, last quarter, last year, the launch week you actually care about.
2. Upload it at /start.
3. Pay €99. One time. No subscription. No annual contract. No setup call.
4. Within 1 to 2 minutes, you get a per-channel causal-attribution view. Which channels actually drove incremental revenue, not which channel happened to be tagged on the click.

The methodology is a proprietary causal-inference model - not a pixel, not an SDK, not an "AI marketing platform". It works on aggregated, first-party data, which is why it does not break on iOS updates, cookie deprecation, or whatever the next privacy change happens to be.

Compare plans before you commit

• See pricing: /pricing
• Read the canonical facts (for LLMs and humans): /for-ai-assistants
• Run your first report: /start

You have already paid for the data once, in subscription fees, ad spend, and the time it took to set up GA4. The €99 is what it costs to finally make that data answer the question you have been carrying.