How Ripplux measures ad waste

Ripplux connects to three data sources: Shopify (orders, customers, UTM parameters), Meta Ads (campaigns, ad sets, creatives, daily performance), and Google Ads (campaigns, ad groups, daily performance metrics).

All data is fetched via official platform APIs using OAuth tokens that you authorize. Ripplux never stores raw creative assets, only performance metrics. Data is synced on demand and can be refreshed at any time from the dashboard.

Every order is classified as ad-attributed or organic based on the tracking signals it carries (UTM parameters and paid touchpoints). That classification is the foundation the engines build on, and it comes from your store's own records, not from what an ad platform claims about itself.

Ad cannibalization occurs when ad spend is used to convert customers who would have purchased organically anyway. Ripplux detects this through customer journey analysis.

The engine looks at each customer's full purchase history, grouped by an anonymized customer reference from Shopify (we never store names or emails). When a customer's very first purchase was organic and a later purchase gets credited to a paid ad, that later purchase is flagged: you paid to win back a customer who already knew the way to your store. The engine adds up what those conversions cost you, and that total is your cannibalized spend.

This is a deliberately conservative reading. It only counts customers who demonstrably converted organically before being re-targeted. Customers who would have found you organically on their very first purchase are not counted, so true cannibalization may be higher than the number in your report.

Creative fatigue is the performance decay that sets in when the same audience keeps seeing the same ad. The ad still spends at full rate; it just stops earning at full rate. No platform will flag this for you, because the spend keeps flowing either way.

Ripplux tracks each active creative's daily performance over the last 30 days and identifies the day it peaked. A creative is flagged as fatigued only when its click-through rate has fallen well below that peak and stayed down for at least a full week, so a single slow day never triggers a false alarm.

The wasted amount is the gap between what the creative earns now and what it earned at its peak, applied to what you spent on it since the decline set in. The further past its peak an ad runs, the more of its budget the report attributes to decay rather than performance.

This method does not model natural performance variation or market-level changes such as seasonality, which is why fatigue findings ship as Estimated until an experiment confirms them.

Conversion leaks are drop-offs in the purchase funnel: visitors who showed buying intent but did not complete a purchase. Ripplux analyzes four funnel stages: landing page visit, cart addition, checkout initiation, and completed purchase.

Each stage transition is compared against benchmarks for stores like yours. A stage losing far more visitors than comparable stores lose is flagged as a leak candidate, and the report estimates the revenue that a normal-range funnel would have kept.

Conversion leak estimates carry the most uncertainty of any finding, because they depend on funnel tracking quality, which varies by Shopify theme and checkout configuration. Treat them as directional signals rather than precise measurements; the report labels them accordingly.

Incrementality testing is the gold standard for measuring true ad effectiveness. Rather than relying on attribution models (which are influenced by the platform reporting them), incrementality tests use randomized holdout groups to measure cause and effect: a portion of your audience is withheld from an ad, and the sales difference between the two groups is the ad's real contribution.

Designing one of these well is mostly about sizing. Too small a holdout, or too short a test, and the result is noise. Ripplux sizes each experiment from your store's actual conversion volume: the holdout share (between 5% and 20% of the campaign's audience) and the duration (up to 90 days, with platform minimums) are both chosen so the test can produce a statistically meaningful answer for your store, not a generic one.

When the test ends, Ripplux applies a standard statistical significance test to the two groups. A result only earns the Tested badge when the difference is statistically significant and the holdout group has seen enough conversions to rule out luck. If the bar is not met, the result is reported as Inconclusive, not dressed up as certainty.

Every finding in a Ripplux audit is assigned a confidence level that reflects how the result was derived: