Skills for digital marketing teams.

Investigate an unexpected spend, outcome, CPA, or ROAS shift; rank falsifiable causes without treating coincident changes as proof.

Compare ad campaign location and device performance from aligned exports while preserving unknown buckets, separate dimensions, and supported targeting controls.

Review Google Ads impression-share losses and Auction Insights overlap without conflating denominators or forecasting competitor spend and profit.

Review marketing and ad campaign period changes and diagnose evidence-backed drivers from supplied comparable exports; use the summarizer for a short stakeholder update.

Write a brief stakeholder update from supplied weekly marketing and ad campaign results, preserving weighted totals and caveats; use the performance review for deeper diagnosis.

Audit supplied ad account and campaign structure, naming, budget ownership, and settings; distinguish operational risks from unproven performance effects.

Find query-backed Google Ads keyword test candidates and verify existing coverage; serving history does not establish incremental demand.

Review destination-specific Merchant Center diagnostics and supplied feed-versus-site evidence to prioritize eligibility, price, stock, and data-quality repairs.

Review Meta ad-set delivery, audience context, reporting status, and mature outcome trends to identify supported constraints and bounded tests.

Review Google Ads placement suitability and observable efficiency, then propose narrow supported exclusions without inventing spend from impressions.

Review Google Ads Performance Max (PMax) asset groups, destinations, themes, and Search overlap; distinguish optimization signals from targeting and causal evidence.

Prioritize Google Ads Search Quality Score component checks by business exposure; treat the score as a keyword diagnostic.

Review supplied Google Ads search terms to separate irrelevant spend from relevant demand and prepare scoped, risk-aware negative keyword proposals.

Assess ad creative fatigue hypotheses from mature comparable trends, delivery age, and reach context; propose a bounded refresh test.

Compare ad creative results for the business objective and plan the next test; optimized delivery does not establish an A/B winner.

Build production-ready ad creative test concepts from supplied offer, audience evidence, brand facts, and assets, with claim sourcing and a measurable hypothesis.

Review Google Ads responsive search ad (RSA) assets and approved claims for keep, replace, pin, or copy-test proposals; preserve overlapping asset metrics.

Review Google Ads bidding goals, reported learning status, conversion delay, and delivery constraints before proposing strategy or target changes.

Quantify a proposed change to ad campaign or portfolio budget totals, with assumptions and approval scope; use the reallocator when the total must remain fixed.

Compare actual ad spend with a supplied period budget and forecast transparent remaining-spend scenarios; use reallocation to move fixed campaign caps.

Prepare a balanced transfer between supplied ad campaign budgets while preserving a fixed total and all protected bounds; use budget pacing to forecast period spend.

Compare acquired-customer cohorts at a common observed horizon using defined revenue, retention, and CAC; separate observed value from lifetime forecasts.

Review product advertising economics using aligned net revenue, returns, and explicit variable costs; distinguish contribution from gross ROAS and company profit.

Audit supplied ad-platform and analytics conversion tracking configuration and safe diagnostics; separate transport acceptance, deduplication, and actual counted outcomes.

Compare campaign lead cost with matched CRM qualification and sales outcomes, accounting for cohort maturity, stage definitions, and join coverage.

Reconcile event, attribution, date, identity, and revenue definitions across ad platform, analytics, and CRM reports before treating differing totals as tracking failure.

Design a bounded marketing or conversion experiment with a supplied meaningful effect, feasible traffic, guardrails, and a predeclared decision rule.

Review a supplied marketing or conversion experiment against its declared design, mature outcomes, uncertainty, and guardrails; allow inconclusive or invalid results without forcing a winner.

Locate observed landing-page and conversion-funnel friction for ad or marketing traffic, then propose diagnostic checks or experiments without asserting untested causes.