Data Driven Retail Growth
RETAIL
Global Premium Furniture Brand
Retail analytics connecting customer data for smarter campaigns and retail business decisions.
Objectives
The objective was to unify disparate data sources to create a holistic view of customer behavior. The client aimed to drive higher revenue through smarter campaigns while optimizing marketing spends across channels.
Connecting customer data for retail analytics
We built a centralized data lake by integrating data from seven key systems, including legacy product catalogs, Salesforce, eCommerce platforms, POS systems, and social media. Using a GraphDB-based data model, we connected customer touchpoints to uncover relationships, patterns, and buying behavior. Advanced analytics powered by Python enabled trend detection, cross-sell insights, and campaign recommendations. A scalable Node-based layer ensured seamless integration with downstream marketing and reporting systems.
Benefits
- 360° customer view: Connected all customer interactions across digital and physical channels into a single, actionable view.
- Cross-sell & up-sell insights: Identified complementary product opportunities based on real buying patterns and behavior graphs. Resulting into 18–20% topline addition.
- Smarter campaigns: Enabled highly targeted online and offline campaigns using seasonal trends and social sentiment analysis.
- Marketing cost optimization: Quantified email marketing effectiveness, helping eliminate low-ROI spends and reduce overall campaign costs. Reduced email campagign cost by 70%.
- DATA ANALYTICS
- PREDICTIVE ANALYSIS