Introduction
Germany’s quick commerce (Q-commerce) market is booming, with platforms like Flink, Gorillas, and Getir competing to deliver groceries in 10–20 minutes. For brands and dark store operators, demand forecasting is critical—especially given varying consumption patterns across cities like Berlin, Munich, and Frankfurt.
Actowiz Solutions partnered with top German FMCG suppliers and fulfillment chains to leverage Q-commerce APIs and AI algorithms for real-time, SKU-level demand forecasting. This enabled smarter inventory planning, reduced stockouts, and improved responsiveness during promotional periods and seasonal spikes.
Actowiz’s API Integration & AI Forecasting Approach
1. Q-Commerce API Connectivity
Actowiz built secure, high-throughput connectors to access:
- Flink API: Product pricing, stock, location tags, promotions, order frequency
- Getir API: SKU availability, average delivery volume, shopping cart history
- Gorillas API (limited): Price change logs, real-time stock snapshots
The API responses were normalized to a unified schema for
cross-platform comparison.
2. Data Points Extracted
| Field |
Description |
| SKU ID |
Unique across platforms, mapped to brand catalog |
| Product Name |
Normalized using NLP models |
| Price & Offer Price |
Captured hourly to detect flash sales |
| Stock Availability |
Real-time, binary or range flag |
| Demand Score |
Derived from order frequency + views + cart adds |
| Zip Code |
Pin-point geographic forecasting granularity |
3. Sample Data Extract (Berlin)
| Timestamp |
Platform |
City |
SKU |
Demand Score |
Stock Flag |
Offer Price |
Forecast (Next 24h) |
| 2025-06-15 10am |
Flink |
Berlin |
Alpro Oat Milk 1L |
85 |
Medium |
€2.49 |
225 units |
| 2025-06-15 10am |
Getir |
Berlin |
Alpro Oat Milk 1L |
72 |
High |
€2.59 |
189 units |
Insight: Forecast aligned with rising breakfast item orders due to long weekend in Berlin.
4. AI Models for Demand Forecasting
Actowiz deployed a suite of predictive models:
- LSTM Neural Networks – For short-term demand trends across hours/days
- ARIMA + SARIMA – Seasonal adjustments (holidays, weekends, weather shifts)
- Random Forest Regressors – Incorporated promotional impact, stock availability, and price fluctuations
- Bayesian Forecasting – Captured uncertainty & spikes for top 500 SKUs
Models were trained on historical + real-time API data for maximum accuracy.
Insights Delivered
- Alnatura organic SKUs saw surge in Munich every Sunday post-promo
- Energy drinks peaked in Berlin on Fridays between 4pm–9pm
- Bundesliga match days influenced snack category spikes in Frankfurt
- Getir flash sales drove spillover demand for matching SKUs on Flink
Actowiz flagged these through automated email + API alerts.
Client Testimonial
“Actowiz took our demand planning from guesswork to precision. Their AI forecasting powered by Q-commerce APIs helps us maintain optimal inventory with no guesswork.”
— Inventory Head, Leading FMCG Distributor, Germany
Conclusion
With real-time data from Q-Commerce APIs and predictive AI, Actowiz Solutions empowers FMCG brands and delivery networks in Germany to make smarter, faster inventory decisions.
From Berlin’s breakfast rush to Frankfurt’s snack spikes, demand is no longer unpredictable. It’s forecasted, mapped, and optimized—thanks to API scraping, ML modeling, and Actowiz’s intelligent data engine.
