Segment by eligibility and risk, then randomize communications, incentives, or surfaces. Use pre-registered analysis plans and power calculations to avoid p-hacking. When true randomization is impossible, apply matched cohorts or difference-in-differences, explaining tradeoffs transparently so stakeholders accept directional learning while roadmaps keep moving.
Adopt attribution that reflects reality: first-touch for discovery, position-based for nurture, and time-decay for late-stage influence. Blend these through ensemble weighting. Validate with lift tests around major launches to calibrate the shares, avoiding exaggerated claims that erode credibility with experienced revenue and finance partners.
Executives buy impact, not correlation. Build counterfactuals through holdouts, delayed exposure, or propensity scoring. Report uplift with confidence intervals and sample sizes, pairing charts with one member story that illustrates the mechanism. This combination makes decisions faster and protects budgets under tough scrutiny.