From Spreadsheets to Omnichannel Intelligence: Scaling Retail Analytics
Maximising retail growth by replacing manual data entry with a centralised, real-time reporting platform.
INDUSTRY
Retail and E-commerce (Fashion).
Company Type
Omnichannel retail brand.
Measurable Outcomes
Unified retail analytics for real-time inventory and marketing decisions.
Core Business Challenge
Manual competitor product mapping for RFPs created severe bottlenecks, draining expert time and delaying bid responses.
Transformation Approach
Custom AWS data warehouse and automated ETL pipelines feeding real-time, interactive Tableau dashboards.
The Challenge
Managing an expanding retail footprint across physical stores and digital channels requires accurate, real-time visibility. However, as this fashion brand scaled, its operational data became trapped in disparate silos, severely hindering strategic decision-making.
Fragmented Data: Online metrics (Shopify, Meta, Google Ads) and offline POS data (Odoo) were completely disconnected.
The Manual Grind: A single team member was tasked with manually transcribing complex sales, engagement, and footfall data into Google Sheets.
Blind Spots: High error rates and reporting lags led to misinformed inventory forecasting and delayed marketing pivots.
Limited Drill-Down: Existing legacy reporting tools lacked mobile capabilities and the deep-dive functionality required by leadership.
Why This Mattered
The Transformation Approach
We engineered an automated data foundation built for commercial scale. Instead of relying on manual data entry, we deployed automated ETL pipelines to extract and normalise data from Meta, Shopify, Google Analytics, and offline POS systems into a secure, centralised AWS data warehouse.
To democratise this intelligence, we built a custom NextJS web application featuring embedded Tableau dashboards. This upgraded reporting suite replaced limited, open-source tools with interactive, real-time visibility. Executives and functional leaders gained immediate, drill-down access to monitor sales by channel, store footfall, and targeted marketing spend.
BEFORE
Siloed Systems
(Online & Offline)
➔
Manual Spreadsheets
(High Error Rate)
➔
Delayed Decisions
Stagnant ROI
AFTER
Automated ETL
(AWS Warehouse)
➔
Unified Platform
(Tableau Dashboards)
➔
Agile Execution
Optimised Growth
Solution Components
To execute this omnichannel transformation seamlessly, we deployed a robust architecture:
Automated ETL Pipelines: Extracted and consolidated raw data from Meta, Shopify, Google Ads, and Odoo POS.
Centralised AWS Data Warehouse: Built on AWS RDS (MySQL) to serve as an uncompromising single source of truth.
Advanced Business Intelligence: Embedded Tableau dashboards delivering drill-down, predictive analytics, and mobile accessibility.
Custom Web Application: Engineered a secure, scalable NextJS front-end for seamless stakeholder access across the organisation.
Business Outcomes
Omnichannel Visibility
Fused online e-commerce data with physical retail footfall into a seamless, 360-degree view.
Automated Reporting
Eliminated manual spreadsheet entry entirely, removing human error and accelerating insights.
Optimised Inventory
Real-time product analytics now allow teams to precisely align stock levels with regional demand.
Targeted Marketing
Clear attribution for ad spend across Meta and Google platforms maximizes return on investment.