Business Objective
Our client is a USD 50Bn+ Global Consumer Packaged Goods manufacturer in the Foods Category. E-commerce is an industry-wide growth engine. Therefore the focus was to understand how key categories are performing across e-commerce platforms and use those insights to drive growth.
As the first step towards this goal, we planned to build an e-commerce data mart using a subset of data sources, hydrating a state-of-the-art enterprise data lake, in order to achieve a multi-fold reduction in effort.
Another objective was to build a data-backed approach to drive sales by optimizing promotions run on retailers’ e-commerce platforms.
Challenges
- Consistency of data quality over a 1 year history
- Difficulties in data roll-up/look-up
Solution MethodologyÂ
- Established the end-to-end data pipeline to acquire, process and monitor quality of e-commerce partner data
- Built a highly automated framework to harmonize data and performed data quality checks using volume/value/share benchmarks against competitors and across categories, geographies, etc.
- Developed base & promo price elasticity models at PPG x e-commerce retailer level for the major categories (Total modeled sales vs. actuals had a high degree of accuracy: +/- 5% MAPE)
- Built a scenario planning tool to enable e-commerce promo planning discussions
Business Impact
- Expanded the rigorous promo analysis process into the online channel as well, by orchestrating all relevant sources of data
- Model-based calculations revealed Return on Spend improvement from 23% to 30%+
