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From Data to Decisions in Adobe Analytics

Sylexa Team · 8/20/2025

Team around a laptop reviewing analytics dashboards

Dashboards don't move metrics—decisions do. To reach decisions, you need trustworthy data, a shared taxonomy, and a repeatable experimentation loop.

The outcome: faster iteration cycles, fewer disputes over definitions, and KPIs that move because tests are prioritized and measured consistently.

Foundations: trustworthy data

  • Taxonomy: standardize names for events, props/eVars, and dimensions
  • Governance: lint tracking plans and block invalid changes in CI
  • Documentation: make a living spec for analysts and engineers

From reporting to decisions

Define a hypothesis backlog tied to business outcomes, with success metrics and guardrails. Run tests, collect evidence, and socialize decisions—not just dashboards.

  1. Create a hypothesis template (assumption, expected impact, metric, variant)
  2. Prioritize by impact/effort and data confidence
  3. Run experiments and record outcomes centrally
  4. Promote learnings to playbooks and design system tokens

Example implementation

  1. Define a tracking plan with events and properties (namespaced, versioned)
  2. Instrument client/server with validation and sampling for QA
  3. Stand up dashboards that map directly to hypotheses and KPIs
  4. Create a weekly decision forum to approve/stop/scale experiments

Operational tips

  • Automate taxonomy linting in CI/CD
  • Tag dashboards with the owner and intended decisions
  • Share wins and failures—document both to avoid repeat mistakes