Inventory Forecasting
StockWise uses your historical sales data to predict future demand, helping you make informed inventory decisions.
How Forecasting Works
Data Collection
StockWise analyzes your order history to understand sales patterns:
- Daily sales volumes
- Weekly patterns
- Seasonal trends
- Growth or decline trends
Prediction Generation
Using statistical methods, StockWise generates forecasts for each product variant:
- Short-term predictions (7-14 days): Higher accuracy
- Medium-term predictions (15-30 days): Good accuracy
- Long-term trends: Directional guidance
Continuous Learning
Forecasts are updated daily as new sales data becomes available, improving accuracy over time.
Viewing Forecasts
Dashboard View
The main dashboard shows forecast-derived metrics:
- Days remaining (based on predicted consumption)
- Reorder point (incorporates forecast data)
- Inventory status
Variant Detail View
The forecast chart displays:
- Blue solid line: Actual historical sales
- Green dashed line: Predicted future sales
Compare predicted vs. actual to gauge forecast reliability.
Forecast Accuracy
What Affects Accuracy
| Factor | Impact on Accuracy |
|---|---|
| Data history length | More history = better accuracy |
| Sales consistency | Stable patterns = higher accuracy |
| Recent changes | Promotions/events can skew forecasts |
| Seasonality | Seasonal products need more data |
Minimum Data Requirements
- 14 days: Minimum for basic forecasts
- 30 days: Recommended for reliable forecasts
- 90+ days: Ideal for capturing patterns
Interpreting Confidence
Products with:
- Consistent sales: Higher confidence predictions
- Variable sales: Lower confidence, wider ranges
- New products: Limited confidence until data builds
Factors Not Captured
StockWise forecasts based on historical patterns. It doesn't automatically account for:
- Planned promotions
- Marketing campaigns
- Supply chain disruptions
- Economic changes
- Competitor actions
Consider these factors when reviewing recommendations.
Using Forecasts Effectively
Daily Operations
- Use "Days Remaining" for immediate decisions
- Check "Order Now" alerts daily
- Review critical items (A-class) frequently
Weekly Planning
- Review forecast vs. actual comparisons
- Identify products with declining accuracy
- Adjust safety stock for variable products
Monthly Strategy
- Analyze trends across product categories
- Plan for upcoming seasonal changes
- Review and adjust threshold settings
When Forecasts May Be Less Reliable
New Products
Products with less than 30 days of history will have limited forecast accuracy. Monitor closely and maintain higher safety stock.
Seasonal Products
During season transitions, forecasts may lag behind actual demand changes. Manually adjust expectations.
After Major Changes
Significant events (viral product, major promotion, supply issue) can skew forecasts temporarily. They will normalize as new data accumulates.
Tips for Better Forecasts
- Maintain data quality: Ensure Shopify inventory is accurate
- Be patient: Accuracy improves over time
- Combine with judgment: Use forecasts as input, not gospel
- Adjust for known events: Plan for promotions manually
Related: Forecast Accuracy | Dashboard Guide