About the Company.
A fast growing, size inclusive fashion retailer operating across ecommerce, marketplaces, and boutique stores. The brand offers denim, dresses, co-ords, maternity wear, and custom fit apparel that are built on sustainability, inclusive sizing, and rapid product drops. As the business scaled, it needed a unified analytics foundation to manage inventory, reduce returns and improve customer insights.
Solution Summary
Algoscale built an end-to-end analytics ecosystem spanning data ingestion, modeling forecasting, and BI dashboards. The solution centralized all sales, product, inventory, and marketing data into a unified warehouse, enabling real time insights across growth, returns, stock movement, and customer behavior.
Customer Challenges.
The client faced significant challenges from fragmented contract management and lack of automation
Inventory mismatches across online and offline channels with frequent stockouts for top-selling SKUs
High return rates mainly due to size and fitting issues,
Limited segmentation and behavior analysis with no visibility into lifetime value or repeat patterns
Difficulty evaluating marketing ROI and campaign effectiveness
Fragmented data across multiple systems.
Daily reporting required manual processing but no single source of truth for sales, inventory, and return performance.
Algoscale Solution.
Algoscale engineered a custom AI/NLP-based contract intelligence pipeline to automate translation, extraction, and governance
Centralized data from Shopify, CRM, marketplaces, ad platforms, and inventory systems
Implemented star schema models for customers, sales, returns, inventory and marketing
Built forecasting models for demand, replenishment, and stock optimization
Implemented SDC logic to track product attributes changes and customer profile evolution
Automated data refreshes via Airflow and standardized data pipelines with validation and monitoring.
Interactive Power BI dashboards for Sales & revenue insights Category & SKU performance Size-and fit related return analytics Inventory forecasting & replenishment Marketing ROI & customer segmentation
Built a multi layer Data Lake for structured data flow and designed a Snowflake data warehouse with scalable SQL pipelines,
Algoscale Differentiators.
Deep experience in geospatial analytics, ML-based catchment modeling, and retail planning.
Ability to merge first party data with external mobility, demographic, and competitor datasets.
Proven frameworks to minimize cannibalization and quantify store expansion ROI.
Strong expertise in building intuitive location intelligence dashboards for strategic planning.
Values Delivered.
Through this engagement, Algoscale delivered measurable improvements:
20% of SKUs generated nearly 70% of revenue, clearly identified through unified analytics
Fit Guide insights reduced size related return rates by ~12%
Stockout-related revenue loss dropped by ~25%
Inventory turnover improved by 20% with centralized data & better forecasting
Improved customer segmentation increased repeat purchases & marketing efficiency by 45%
Technologies We Use.
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