Analyze campaign performance to distill the why behind the what—cohorts, lift, incrementality signals, creative/offer splits, geo or branch patterns, time trends, and more.
Build the story: draft the executive “headline,” structure the narrative, and create speaker notes for AEs/Client Strategists.
Visualize with Tableau: produce clean, reusable dashboards and export-ready visuals.
Own readout assets: monthly performance summaries, QBR slide sections, one-pagers, win/loss insight briefs, and a living “pattern library” of best-practice visuals.
Partner tightly with AEs & Client Strategists to align on hypotheses and the decisions a readout must enable.
Uphold SLAs, QA your work, and maintain a small component library to speed future builds.
Use AI for exploratory analysis, rapid storyboard drafts, code review/snippets, narrative polishing, and outlier detection—responsibly and transparently.

2–4 years in data analysis, marketing analytics, or BI.
Tableau (hands-on) with calculated fields, LODs, parameter controls, level-appropriate performance tuning, export quality.
SQL (Required) – joins, windows, aggregations; comfort profiling messy matchback files and campaign tables.
Statistics & testing basics – confidence intervals, practical significance, A/B testing pitfalls, cohort analysis.
Communication – tight executive writing, structured narratives, clear speaker notes.
AI – hands-on with AI for EDA/storyboarding/visual drafts or strong appetite to learn quickly.
Nice to Have: Python or R for quick EDA (pandas/dplyr), tidy data, and chart exports; regex & data cleaning.
Experience with marketing performance data (direct mail, paid social, display, online video), attribution trade-offs, and incrementality concepts

Associate Campaign Insights Analyst

Key skills