This talk presents a real-time service we have developed to help to reduce the delivering time between customer's ordering and receiving of products.

1. SPARTE
Sales Prediction And Real-Time
Estimation
Data Science Forecasting Team
Minhui WU

2. Context
● Veepee Group:
Since January 2019, vente-privee.com and all of its European subsidiaries are
grouped together under a new common brand, Veepee.

3. How to offer a better shopping experience ?
SPARTE
Sales Prediction And Real-Time Estimation

4. Use Case 1: Intermediate Orders
● Post Sale Mechanism
● What we expect to improve

5. Use Case 2: Product Ranking
● Catalog Page
Veepee.fr -> homepage ->
catalog Page
● Rank product according to
forecasted popularity,
instead of past popularity

6. Use Case 2: Product Ranking
● Catalog Page
● Rank product according to
forecasted popularity,
instead of past popularity
● We can be more reactive to
product popularity changes

7. SPARTE Workflow
7 Models based on predicting time
○ 1h, 6h, 12h, 24h
○ 48h, 72h, 96h

8. SPARTE Features
■ Data
■ Live orders
■ Products (stocks, prices, discounts, delivery
delays, NGP, ...),
■ Campaigns (start, end, ...)
■ Context (month, day of week…)
■ Dynamic Features Engineering
■ Basic (price, discount, NGP, brand…)
■ Time series (Kpi extracted from sales TS with
TSfresh)
■ Math estimation from TS (linear, power, log)
■ History (KPIs from the past campaigns
aggregated by brand, sub sector…)

9. SPARTE Features
■ Data
■ Live orders
■ Products (stocks, prices, discounts, delivery
delays, NGP, ...),
■ Campaigns (start, end, ...)
■ Context (month, day of week…)
■ Dynamic Features Engineering
■ Basic (price, discount, NGP, brand…)
■ Math estimation from TS (linear, power, log)
■ Time series (Kpi extracted from sales TS with
TSfresh)
■ History (KPIs from the past campaigns
aggregated by brand, sub sector…)

10. ● Key Figures
○ More than 200 active daily campaigns
○ 7 prediction models BY TIMESTEP for each sector
○ Hourly Scheduling
● Model : XGBoost Regressor
● Performance Evaluation: WMAPE
SPARTE Model & Evaluation

11. Related Projects
● Product ranking (Alcyon):
- ALgorithm for Catalog Yield optimizatiON
- 1st A/B test done, 2nd test is ongoing
● Demand Forecast (Pythia):
- Predict sale quantity before sale starts

12. Context
● Data Science Forecasting Team Members
Georges KOHNEN Bart AELTERMAN Joel
QUESADA VALLEJO
Robin LESPES Minhui WU