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Prova-Artefakt

AI-Readiness-Scorecard für Marketingteams

Bewerte, ob ein Marketingteam die Signale, Daten, Arbeitsrhythmen und kodifizierte Urteilskraft hat, um AI-Workflows verantwortungsvoll zu pilotieren.

Vorlagenfelder

  • Readiness item
  • What 4+ looks like
  • Current score from 1-5
  • Evidence
  • Gap
  • Owner
  • Next 30-day fix

Ausgefülltes Beispiel

Die ausgefüllten Beispiele unten bleiben auf Englisch, weil Prova eingereichte Artefakte auf Englisch prüft.

An in-house growth team preparing to pilot AI-supported reporting and campaign recommendations.

First-party conversion signals are reliable
First-party data strategy is in place
AI-native campaign types are understood and operational
Paid, owned, and earned are planned as one system
Emerging channels are considered deliberately
Primary KPIs are separated from optimization metrics
Campaign data is clean, labeled, and queryable
Planning principles and brand guides are codified for AI use

Schwache Version vs. starke Version

Schwache Version

ItemData is clean
Score4
EvidenceWe have dashboards
GapSome naming issues
OwnerAnalytics
Next fixImprove tracking

Warum es scheitert

  • The score is unsupported.
  • Dashboards do not prove the data is queryable or trustworthy.
  • "Some naming issues" hides the operational impact.
  • The owner is a department, not a person or role.
  • "Improve tracking" is not a 30-day fix.

Starke Version

ItemCampaign data is clean, labeled, and queryable
Score2
EvidenceGoogle Ads and Meta naming conventions differ; LinkedIn uses old campaign taxonomy; weekly report still relies on manual spreadsheet cleanup
GapAI cannot compare cross-platform performance without manual reconciliation
OwnerMarketing analytics lead with paid media lead as reviewer
Next 30-day fixStandardize naming for new campaigns and create a one-page exception log for legacy campaign data

Warum es funktioniert

  • Evidence is concrete.
  • The score is honest.
  • The gap explains why AI output would fail.
  • Ownership is specific.
  • The next fix is narrow enough to complete.

Was Prova prüft, was generische AI oft übersieht

  • Whether readiness scores are backed by evidence
  • Whether "we have dashboards" is being mistaken for usable operating data
  • Whether gaps are prerequisites or nice-to-haves
  • Whether the team is ready for a pilot or needs foundation repair first
  • Whether the next sprint should be workflow audit, measurement architecture, rollout planning, or diagnostic repair

Nächster Schritt

Willst du Feedback zu deiner Version? Prova startet mit einem kurzen Assessment, damit der Review-Standard zu deiner Rolle, deinem Ziel und deiner ersten Zielgruppe passt. Danach kommst du in den Sprint, der zu deiner aktuellen Arbeit passt.

Prova ist derzeit nur auf Englisch verfügbar.

Vor dem Absenden: entferne Kundennamen, vertrauliche Zahlen und alles, was dein Team nicht in einem Trainings- oder Coaching-System speichern würde.

Weiter zu Prova auf Englisch