Our Process

A Proven Methodology for Outlet Transactional Data Excellence

Four structured phases take CPG teams from fragmented retailer data to a fully operational, analytics-ready pipeline — in 12 weeks or less, with zero disruption to existing reporting workflows.

1Assess & DesignWks 1–2
2Ingest & StandardizeWks 3–6
3Enrich & ModelWks 7–10
4Deploy & ActivateWks 11–12
Phase 01Weeks 1–2

Assess & Design

Every successful data program starts with a clear picture of where you stand. Our specialists conduct a comprehensive audit of all existing outlet data sources, map integration touchpoints, and co-design the target data architecture with your team.

Work Streams

  • 1Current state data audit across all retail systems
  • 2Retailer POS source inventory and access review
  • 3Integration mapping: source-to-target field alignment
  • 4Data model design for harmonized outlet schema

Deliverables

  • Data architecture blueprint
  • Source-target field mapping document
  • Gap analysis with prioritized remediation plan
  • Implementation roadmap with milestones
Phase 02Weeks 3–6

Connect & Harmonize

With the architecture agreed, the platform begins automated ingestion across all outlet data sources. AI agents execute hundreds of correction rules on every batch — aligning file structures, detecting missing records, removing duplicates, and flagging anomalies — before the harmonization engine matches fields, entity names, store identifiers, and timelines into a single consistent model.

Work Streams

  • 1Source ingestion across all identified retail formats and segments
  • 2AI agent-driven automated correction: structure, gaps, duplicates, anomalies
  • 3Harmonization rules engine — UPC, store ID, entity names, category codes, UOM
  • 4Semantic layer configuration for consistent cross-retailer field definitions

Deliverables

  • Unified data feeds from all connected outlet sources
  • Harmonization ruleset documentation
  • Data quality scorecards (baseline and ongoing)
  • UAT environment ready for client review
Phase 03Weeks 7–10

Enrich & Model

With harmonized data flowing, AI agents continuously monitor cross-store consistency — flagging drift and triggering auto-corrections as new data arrives. Our specialists then layer in enrichment: aligning product master records, mapping store hierarchies, applying category tagging, and backfilling historical data so your analytics start with both depth and reliability.

Work Streams

  • 1Product master alignment across retailer item databases
  • 2Store hierarchy mapping: chain, banner, format, region
  • 3Category and sub-category tagging with CPG taxonomy
  • 4Historical backfill of up to 24 months transactional data

Deliverables

  • Enriched, analytics-ready outlet dataset
  • Master data reference library (products, stores, categories)
  • Historical backfill validated and loaded
  • Enrichment methodology playbook
Phase 04Weeks 11–12

Deploy & Activate

Production deployment is the beginning, not the end. We integrate directly with your BI tooling, deliver a library of pre-built reporting templates, and run structured training sessions so your commercial teams can self-serve from day one.

Work Streams

  • 1BI tool integration (Tableau, Power BI, Looker)
  • 2Reporting template library delivery — 15+ standard views
  • 3Commercial team training sessions (live + recorded)
  • 4Formal handoff, runbook, and escalation documentation

Deliverables

  • Production-grade deployment with SLA monitoring
  • Reporting template library (outlet, category, account views)
  • Trained internal team with self-serve capability
  • Operations runbook and support escalation guide

12-Week Implementation Timeline

From kickoff to production in a structured, predictable sequence designed around your team's bandwidth.

W1
W2
W3
W4
W5
W6
W7
W8
W9
W10
W11
W12
PHASE 01
PHASE 02
PHASE 03
PHASE 04
Wks 1–2
Wks 3–6
Wks 7–10
Wks 11–12
End of Week 2

Architecture blueprint signed off

End of Week 6

Live data feeds in staging

End of Week 10

Enriched dataset validated

End of Week 12

Production go-live

Support Model

You're Never Left to Figure It Out Alone

Every engagement includes structured support from kickoff through steady-state operations — not just during the implementation window.

Dedicated Support Manager

A named account manager who knows your data environment and acts as your single point of contact throughout the engagement and into production.

Weekly Check-ins

Structured weekly status calls with a written summary, action log, and forward agenda — so every stakeholder stays aligned on progress and blockers.

SLA Guarantees

99.5% pipeline uptime, <4-hour incident response for critical data failures, and monthly data quality reports delivered to your team on the 1st business day.

Ready to Start Your Implementation?

Our onboarding team will scope your specific retailer environment and provide a tailored 12-week plan — no obligation, no boilerplate.