Benchmarks built on real outcomes.
Most published benchmarks are vendor surveys, self-reported and averaged. Ours are computed from real, reconciled outcomes across the brands and operators we run, so when you compare yourself, you are comparing against what actually happened, not what someone claimed.
Real N, stated
Every figure carries its actual sample size: orders, customers, accounts or deals. No undisclosed panels, no projected universes.
Medians, not means
We report the median and the spread, so one outlier brand can't flatter the number you measure yourself against.
Anonymised cohorts
Outcomes are aggregated and de-identified before they enter a study. No single brand is identifiable from a benchmark.
Minimum cohort
A segment is only published once it clears a minimum cohort size. Thin cells are withheld rather than guessed.
How to read these. Each study shows the math behind the number, segments by the dimensions that move it, and marks which figures are computed end-to-end versus estimated. Gated studies require a work email; the headline result is always visible first.
Five benchmarks, by what they measure.
Margin, demand, attribution, retention and pipeline, each computed from the outcomes we run.
The Weather Demand Index
Weather is the largest demand driver that almost no analytics platform measures. It moves roughly a third of economic activity and influences 62% of what consumers buy, yet most operators still treat a cold snap or a heatwave as noise in the numbers. This study quantifies how much demand moves, by event, by vertical and by Australian region, and shows the baseline math to forecast it.
The Margin-True Benchmark
Most ecommerce benchmarks stop at revenue and gross margin. The number that decides whether a brand survives is contribution margin. This study segments contribution margin, CAC payback and returns by category and brand size, shows the math behind each metric, and explains why the median DTC brand earns far less than its top line suggests.
The Lead & Pipeline Economics Benchmark
A lead is not a cost. It is a priced option on a future customer. This study sets the 2026 reference points for what that option costs, how often it pays off, and how fast it turns into revenue, segmented by vertical and deal size.
The Retention & Lifecycle Marketing Benchmark
Across a primary dataset of 156,110 direct-to-consumer customers, the repeat-purchase rate is 18.8%. This study takes that one number apart, then shows the owned-channel lifecycle math that moves it, and what each point of repeat-rate is worth in durable profit.
More studies are in production. The next release segments contribution margin by acquisition channel once our own attribution engine clears validation, the one number a Shopify dashboard can never give you honestly.
The thinking behind the numbers.
Each benchmark sits on a longer guide and a body of field notes. Start where your question is.
Stop benchmarking against claims. Benchmark against outcomes.
Connect your stack and we reconcile your numbers to true contribution margin, then place you against the same cohorts these studies are built on.