Maya-Beth Finotti Skills

Diagnoses underperforming paid ad accounts by tracing tracking, structure, targeting, creative, bidding, offer and external causes.

Sets paid-media CAC, ROAS, cash and kill-switch guardrails from contribution margin, payback and runway, with owners, overrides and restart rules.

Diagnoses whether a running ad is suffering creative fatigue or a confounder across Meta, Google Ads, LinkedIn and TikTok, then recommends the next action.

Computes CAC, ROAS, MER and payback from advertising spend data, then judges spend health against break-even, history and external benchmarks.

Maps an ICP and buying signals into sized, budgeted ad audience tiers for prospecting, lookalikes, first-party lists and retargeting without overlap.

Allocates a fixed paid-media budget across campaigns, platforms and funnel stages using marginal return, evidence gates and bounded reallocation rules.

Plans budget increases for proven paid campaigns, choosing step sizes, hold periods and rollback triggers while checking marginal economics, evidence and capacity.

Maps B2B buying committees and multi-decider household purchases to role-specific messaging, ad-platform targeting proxies and buying-stage sequences.

Selects paid advertising channel families by business economics, audience, funnel stage, budget and allowable CAC, then defines a focused test plan.

Plans paid-advertising careers with interview preparation, skill-gap roadmaps, NDA-safe portfolios and choices between agency, in-house and freelance work.

Builds hiring packets for paid-advertising roles, covering role scope, scorecards, interview loops, work samples and staged 30-60-90 ramps.

Designs multi-stage retargeting plans for paid advertising using conversion data, audience exclusions, message ladders, frequency caps and measurement tests.