Quarterly research
State of Incremental Marketing
Causal attribution applied to paid, organic, email, brand, and retention, across the Causality Engine customer base. Quarterly. Methodology open. Numbers honest enough to carry confidence intervals.
Why this exists
Last-click attribution dashboards have been telling marketers the same flattering story for a decade. The story does not survive a causal read. Reported ROAS overstates incremental impact. Channels claim conversions other channels also caused. Organic and email get under-credited; retargeting and branded search get over-credited; brand investment shows up as a cost line item with no measurable return.
Causality Engine runs causal attribution on Shopify and GA4 data for hundreds of DTC brands. This report aggregates the incremental impact numbers (anonymized, with consent, by cohort) into the benchmark dataset the industry has never had. Updated quarterly. Free to read. Citable.
What "incremental marketing" actually means here
Five surfaces. Each measured against the same counterfactual question: what would have happened without this?
Paid channels
Meta, Google, TikTok, Pinterest, programmatic. The piece most teams already measure (badly). Incremental ROAS per channel with confidence intervals.
Organic search
SEO traffic that converts. Most last-click models give organic the residual after paid takes its claimed credit. Causal modeling reads the underlying demand and reports the real incremental contribution.
Email and lifecycle
Flows, broadcasts, retention campaigns. Captures existing intent at the bottom of the funnel - which is why last-click email ROAS is the most overstated number in DTC.
Brand investment
Sponsorship, influencer, content, podcast ads. The piece that breaks last-click entirely - and where causal modeling has the most to add.
Retention and LTV
Incremental customer lifetime value from retention activity. Lifetime-value impact, not just first-order ROAS.
Methodology
Each benchmark is the cohort-average incremental impact estimated by Causality Engine on the relevant subset of consenting customers. Incremental impact is estimated causally from each brand's Shopify and GA4 history using counterfactual modeling, not by allocating credit through last-click or multi-touch rules.
Cohorts: industry vertical, monthly revenue band, ad-spend band. Minimum sample size per cohort is enforced before publication. Numbers below the minimum are reported as “insufficient data” rather than estimated from noise.
Consent: customer participation is opt-in. Every brand-level identifier is removed before aggregation; only cohort-level summaries are published. Our full methodology document covers assumptions, robustness checks, and known limitations and is available on request to any researcher.
Q2 2026 results
Numbers shipping with next refresh
The first benchmark release ships with the 2026-09-13 refresh, once the Q2 sample size clears the minimum for each cohort. Want to know when it drops? Subscribe and we will email the report on publication.
Want your brand's anonymized data included in the next quarterly refresh, and to see your own numbers benchmarked against cohort averages? Run a causal attribution check (€99) and opt in during checkout.
Frequently asked questions
How are these benchmarks calculated?
+
Each number is the average incremental contribution across a sample of consenting Causality Engine customers in the relevant cohort. Incremental contribution is estimated causally from each brand's Shopify + GA4 history using counterfactual modeling, not last-click rules. Sample sizes are reported alongside each metric and minimums are enforced before publication.
Why publish incremental marketing benchmarks instead of ROAS?
+
ROAS is one slice of incremental marketing - the paid-channel slice. Organic search creates demand, email captures it, brand recognition shortens consideration, retention defends LTV. All of those have an incremental component that a paid-ROAS report misses. Holistic incremental marketing measurement is the brief.
How are customer datasets anonymized?
+
Every brand-level identifier is removed before aggregation. Numbers are reported as cohort averages (industry vertical, monthly revenue band) with sample-size minimums that prevent re-identification. Customer consent is opt-in.
How often is this report updated?
+
Quarterly. Each release covers the most recent completed quarter and a rolling year-over-year comparison. Sample size grows over time; numbers stabilize.
Causal attribution check
Find your wasted ad spend
in 2 minutes.
Upload 90 days of Shopify and GA4. Get incremental ROAS with confidence intervals. No pixel, no SDK, no integration project. €99 per run.
The math behind your marketing.
Product
Causal AttributionIncrementality TestingMarketing Mix ModelingHow It WorksPricingCompare PlansIntegrationsCase StudiesResourcesAttribution GuideDTC PlaybookAd Spend CalculatorHave an idea?
© Copyright 2026, Causality Engine
Based in the Netherlands
|KVK: 92226892
|VAT: NL865944039B01