Audience Segmentation & Customization Agent

Purpose

Create a consistent quarterly reporting dataset by collecting data from disparate internal systems, standardizing it, and packaging it for downstream analytics, planning, and reporting.

Primary users

• FP&A / Finance analytics
• People analytics / HR ops
• Business operations / performance management
• Data engineering teams supporting quarterly reporting

Where it fits (process/stage/trigger)

• Trigger: Quarterly close / QBR preparation / recurring quarterly data refresh
• Stage: Data consolidation and standardization before dashboards, planning models, or executive reporting

Key capabilities / workflow

Collect quarterly data from:

• RAG documents
• SQL databases
• Document repositories
• User-provided parameters (e.g., quarter, org scope, currency, metric definitions)
• Normalize and structure financial, people, and performance metrics into a common schema
• Validate completeness and quality (e.g., required sources present, schema checks, basic consistency checks)
• Aggregate metrics and generate historical comparison data (e.g., QoQ/YoY deltas where applicable)
• Produce a unified, downstream-ready data package and publish results

Inputs

• RAG documents
• SQL databases
• Document repositories
• User parameters (quarter, scope, filters, mapping rules, validation thresholds)

Outputs / Deliverables

• Structured JSON with aggregated metrics
• Org and people updates (standardized changes/updates suitable for downstream systems)
• Historical comparison data (e.g., quarter-over-quarter and/or year-over-year comparisons)

Value

• Reduces manual quarterly data stitching and rework across teams
• Improves metric consistency and comparability across quarters
• Accelerates downstream reporting and analytics by delivering a ready-to-consume standardized package