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University of FlowStateOpen online learning

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Digital Marketing Analyst

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Current availability

The subject-specific curriculum is authored but not yet published for completion. Learners may inspect its scope and learning design now. Start, grading, and completion remain unavailable until every listed gate passes.

  • qualified review approval is required
  • reviewer identity, qualification, evidence, and approval date are required

What this course establishes

  • Translate a business and audience problem into an ethical funnel, channel plan, campaign taxonomy, metric contracts, and testable measurement plan
  • Validate campaign, cost, interaction, conversion, and revenue data and calculate channel economics with reproducible numerators, denominators, windows, and deduplication
  • Evaluate attribution and experiments without causal overstatement and communicate accessible, privacy-preserving recommendations with uncertainty and guardrails

Entry knowledge

  • Spreadsheet formulas and percentages
  • Basic descriptive statistics
  • Familiarity with websites, email, search, social, and paid media

Scope boundaries

  • Uses a fictional campaign dataset only and does not authorize production tracking, audience purchase, sensitive targeting, deceptive persuasion, dark patterns, spam, platform-policy evasion, or collection without a lawful purpose and required consent
  • Does not replace legal/privacy review, accessibility evaluation with disabled people, statistics or causal-inference expertise, channel-platform certification, creative or brand review, information security, or authorized budget approval

Fastest competency route

Completion is competency-based and self-paced. Prior experience may shorten study only when every required calculation, control, artifact, ethical boundary, and substantive revision is demonstrated; no fixed duration, employment, certification, traffic, revenue, ranking, or campaign outcome is promised.

  1. Pass diagnostics for objectives, funnels, taxonomy, instrumentation, consent, data quality, economics, attribution, experimentation, accessibility, and advertising integrity
  2. Complete the supplied synthetic multichannel campaign analysis and decision portfolio
  3. Correct every duplicate, taxonomy, denominator, conversion, attribution, consent, accessibility, claim, email, and inference defect before final assessment

Full self-paced route

  1. Strategy, audience, funnel, channel, and measurement design
  2. Data quality, campaign economics, attribution, and reporting
  3. Experiments, privacy, accessibility, advertising integrity, and decisions
  4. Applied portfolio and final assessment

Lesson and assessment map

01

Strategy, audience, funnel, taxonomy, and measurement contracts

Build a decision-ready marketing measurement system from legitimate audience needs and business outcomes rather than vanity metrics.

4 questions: recall, application, judgment, and error correction.

02

Data quality, channel economics, attribution, and accessible reporting

Reconcile multichannel evidence and explain performance without confusing platform credit, business value, or causal impact.

4 questions: recall, application, judgment, and error correction.

03

Experiments, privacy, advertising integrity, and decisions

Make bounded optimization decisions using credible experiments and lawful, accessible, non-deceptive marketing practices.

4 questions: recall, application, judgment, and error correction.

Required applied assignment

Multichannel measurement and decision portfolio

Audit and analyze only the supplied fictional campaign data. Preserve the source, create a controlled transformation, and do not treat platform credit as causal impact or mark privacy, accessibility, advertising, endorsement, email, platform, financial, or legal review complete without qualified evidence.

  • Decision brief, audience/journey and channel-role map, campaign taxonomy, parameter QA, event/conversion hierarchy, metric dictionary, consent and retention design
  • Immutable-data note, cleaning log, row-level issue register, deduplicated analysis table, channel economics, weighted totals, funnel, finance reconciliation and attribution comparison
  • Pre-registered experiment with allocation/exposure checks, power rationale, primary outcome, guardrails, accessible result template and inference boundaries
  • Advertising/endorsement/email/search/accessibility/privacy audit, corrected creative brief, final evidence-bounded recommendation, rollback/monitoring, peer critique and revision history

Passing standard: 85 of 100 points, with substantive revision required.

Continue after this course

  • SQL, warehouses, marketing data pipelines, identity resolution with privacy safeguards, and semantic metric layers
  • Experimental design, incrementality, media-mix modeling, causal inference, forecasting, and optimization
  • Search, lifecycle/email, paid media, content, conversion research, accessible creative, and platform-specific operations
  • Privacy engineering, consumer protection, records, procurement, and marketing law in each operating jurisdiction