Frederic Labadie

Frederic Labadie Portfolio — AI Design Brief

Site type

Personal portfolio for an Amsterdam-based Analytics Architect, data strategy professional, and digital measurement leader.

Primary audience

Recruiters, hiring managers, analytics leaders, product leaders, marketing technology teams, UX-adjacent teams, and AI/design tools reviewing the portfolio structure.

Desired impression

Senior, analytical, precise, evidence-led, editorial, and technically credible. The site should feel like an analytical dossier, technical field notebook, or evidence board rather than a generic startup portfolio.

Current positioning

Frederic Labadie is a full-time Analytics Architect at Telus Digital. His best-fit areas are analytics architecture, product telemetry, analytics engineering, UX telemetry, and marketing analytics. He is Amsterdam-based and has EU work authorisation.

Visual language

Blueprint, technical dossier, analytical field notes, case-library archive, and evidence board.

Content architecture

The portfolio is intentionally organized by problem shape rather than employer chronology. The case library includes seven lenses:

• AI workflows
• Data engineering
• Instrumentation
• Adoption and enablement
• Marketing analytics
• Experimentation
• Question discovery

Current proof points to preserve

• 83% alert-noise reduction in V1 production AI alert triage.
• 38 hours of analyst time recovered per month.
• Approximately 50% BigQuery pipeline cost reduction.
• +10.8% year-over-year CTR lift from CDP migration.
• 14 years analytics experience.
• 11 Amplitude credentials.
• MSc Data Analytics.
• EU work authorisation.

Selected case themes to preserve

• Shadow IT / compatibility configurator: the data surfaced the gap, but frontline staff explained why.
• State-regulated retail BI enablement: the reporting layer survived the team that built it.
• Mixed-methods Stanley Steemer research: telemetry located the problem; method diagnosed the user gap.

Do not change

• Preserve the evidence-led tone.
• Preserve the case-library structure.
• Preserve the homepage’s “measurement problem” positioning.
• Preserve the distinction between proof points, case studies, and methodology.
• Preserve the muted, professional, blueprint-like palette.
• Avoid generic SaaS-template gloss.
• Avoid over-polished personal-brand language that weakens the analytical voice.
• Avoid making the work sound like vague strategy; keep the measurement, systems, and adoption language.

Design task guidance

When proposing improvements, prioritize:

1. readability
2. recruiter scan speed
3. case-study hierarchy
4. proof-point clarity
5. mobile usability
6. accessibility
7. preserving the existing voice
8. making the case library easier for AI/design tools to interpret

Interpretation notes for AI/design tools

Read the portfolio as evidence of judgment, systems thinking, instrumentation skill, stakeholder adoption, analytics architecture, and mixed-methods reasoning. The strongest design improvements should make that evidence easier to scan without flattening the site into a generic resume page.