Ripplux vs the alternatives
Honest comparisons, including where the other tool is the better choice. Each page names what the tools measure differently and who each is built for.
Hyros vs Ripplux
Hyros tracks harder to recover conversions platforms miss. Ripplux tests instead of tracking. Here is why better tracking still cannot prove causation.
Lifetimely vs Ripplux
Lifetimely answers whether your customers are profitable. Ripplux answers whether your ads caused them. Same price, different question, often both.
Northbeam vs Ripplux
Northbeam is enterprise measurement priced from $1,500 a month. Ripplux is $149. Here is what the gap buys, and the spend level where it starts paying off.
Polar Analytics vs Ripplux
Polar sells a full data stack and incrementality as a service with data scientists. Ripplux sells one experiment engine as software. Which fits your team.
Triple Whale vs Ripplux
Triple Whale models attribution with a pixel. Ripplux measures it with holdout experiments. Here is what each one proves, what each costs, and who each fits.
How these tools actually differ
Almost every tool on this page exists because platform-reported ROAS is not trustworthy. They split into two camps by method, and the camp decides what the output can and cannot prove.
Attribution tools observe as much of the customer journey as they can and divide credit across the touches they see. Triple Whale, Northbeam, and Hyros are in this camp. Better tracking produces a more complete record of what happened.
Experiment tools stop trying to observe the journey. They withhold an ad from a randomised slice of the audience and measure the difference in orders. Ripplux is in this camp, and Polar Analytics offers it as a separately priced service.
The distinction matters because a more complete record still cannot tell you what would have happened otherwise. Someone who already decided to buy, then searches your brand and clicks the ad above your own organic listing, is counted by every attribution system on the market. Withhold that ad and most of those buyers click the organic link and purchase anyway. Field experiments on branded search have found the incremental effect close to zero, which is why the eBay and Econometrica study remains the reference point.
Where each tool sits
| Tool | Primary method | Built for | Published entry price |
|---|---|---|---|
| Ripplux | Randomised holdout experiments | Solo Shopify operators | $149 per month |
| Triple Whale | Pixel-based multi-touch attribution | DTC teams wanting a daily dashboard | Free tier, then from $219 per month |
| Northbeam | Attribution with view-through and optional MMM | Brands with a data team | From $1,500 per month |
| Hyros | Attribution with conversion recovery | Long-window and call-driven funnels | Not published, demo required |
| Polar Analytics | BI stack plus incrementality as a service | Teams that need a full data layer | Not published, scales with GMV |
| Lifetimely | Profit, P&L, and cohort LTV reporting | Merchants sizing margin and payback | Free tier, then from $79 per month |
Competitor prices reflect published pricing pages as of 2026-07-28 and are starting points rather than quotes. Several vendors scale price with revenue, ad spend, or data volume, so the figure you are quoted will differ. Where a vendor does not publish pricing, this table says so instead of guessing.
How a holdout experiment works
A holdout splits your audience at random. One group is eligible to see the campaign. The other is not. Because assignment is random, the two groups are alike in every respect except exposure, so the difference in orders between them is the campaign's causal effect. This is the logic of a clinical trial applied to ad spend, and it is the only method here that manipulates anything rather than observing it.
The cost of that rigour is volume. An effect has to be large enough to separate from ordinary week-to-week variance, which is why Ripplux requires roughly $5,000 in monthly spend on the tested platform and about 50 conversions per month. Below those thresholds Ripplux declines to run the test rather than returning a confident-looking number with an interval too wide to act on.
One asymmetry is worth knowing before you approve anything: pausing a campaign and restoring it later restores the setting, not the auction position or the learning state. Ripplux discloses that before you approve a change, not after.
Which one should you buy?
The deciding question is what you will do with the output. If you will look at it every morning, buy a dashboard: Triple Whale or Polar Analytics. If you need to know whether your customers are profitable before you optimise anything, buy Lifetimely. If you have a data team and six-figure monthly spend, look at Northbeam. If you want to know whether a given campaign is causing sales and you spend between $5,000 and $50,000 a month, that is the question Ripplux was built for.
If you spend less than $5,000 a month on ads, none of these tools will repay their subscription yet, including ours. That is a real answer and it costs nothing.
Frequently asked
- What is the difference between attribution and incrementality?
- Attribution divides credit for an order among the ads a buyer was observed to touch. Incrementality measures whether the ad caused the order at all, by withholding it from a randomised comparison group. An ad can receive full attribution credit and have close to zero incremental effect, which is the usual explanation for a reported ROAS that does not match bank deposits.
- Why does my reported ROAS not match my actual revenue?
- Three effects account for most of the gap. Brand cannibalization pays for buyers who were already coming to you. Creative fatigue means spend keeps flowing to creatives whose efficiency has decayed. Channel overlap means Meta and Google both claim the same order. None of these are reporting errors: each platform is correctly reporting its own view, and the views sum to more than the truth.
- How much ad spend do I need before incrementality testing works?
- A holdout experiment needs enough volume to detect an effect against normal variance. Ripplux requires roughly $5,000 in monthly spend on the platform being tested and about 50 conversions per month. Below that the confidence interval is too wide to support a decision, and Ripplux says so rather than reporting a number that looks precise and is not.
- Does Ripplux require a tracking pixel?
- No. Ripplux reads Shopify orders and ad-platform spend through official APIs and runs experiments on the ad platforms themselves. There is no script to add to your theme, no identity graph, and no per-user tracking.