Fiera Incrementality

Measure whether your ads drive results that would not have happened anyway. Fiera Incrementality helps paid media teams choose the right test, design it, and read it: - Planner: turns a question (is brand search incremental? should we cut Meta prospecting?) into a test plan. Recommends the platform's own lift study when one is available, a geo experiment when channels must be compared on business data, and a switchback or a directional before/after read when nothing else is possible. - Geo test design: from a CSV of KPI by region and day, picks treated regions by stratified randomization, estimates the minimum detectable effect on held-out history, the test length and the cost, and writes a plan to approve before launch. - Geo test readout: estimates the effect with two methods (time-based regression and synthetic control), intervals from placebo tests, incremental CPA and ROAS, and robustness checks. - Quick incrementality: a directional read on a pause or budget change, compared with several baselines and their normal noise, plus switchback analysis for single markets. - Lift result review: an independent check of a lift study, vendor test or internal claim. Results feed attribution (incrementality factors) and marketing mix models (Meridian, Robyn, PyMC-Marketing) as calibration. Methods follow the published work behind Google's TBR and Meridian GeoX, Meta's GeoLift and the synthetic control literature, with sources cited in the skills. The analysis runs in a bundled Python script on the data you upload. It is calibrated on simulated panels: false positive rate in A/A tests, coverage of the true effect, and power at the predicted detectable effect. Intended for performance marketing, growth and analytics teams. Limits: results are as good as the KPI data you provide; directional methods are labeled as such and do not prove causation; platform lift studies are run in the ad platform, not by this plugin.