What Is a Planogram and Key Retail Concepts?
A planogram is a visual layout that defines product placement on shelves.
- Specifies facings per SKU based on forecasted demand (units/week/store).
- Controls shelf position using category and visibility rules.
- Aligns assortment with predicted seasonal sales trends.
- Shelf space optimization: Allocating space based on forecasted sales volume.
- Category management: Grouping products to match shopper buying patterns.
- SKU: Unique product identifier.
- Assortment: Product mix based on seasonal demand forecasts.
These definitions ensure accurate and measurable shelf planning.
How Does Nexgen POG Use Data for Seasonal Forecasting?
Seasonal planogram software integrates forecasting data into planogram creation for precise execution.
Workflow:
- Import historical sales data (units/week/store, seasonal trends).
- Apply forecasting models to predict future SKU demand.
- Use autofill logic to assign SKUs based on forecast priority.
- Allocate shelf space using predicted sales (e.g., increase facings by 25% for high-demand SKUs).
- Apply placement rules for visibility and category flow.
- Generate planograms for store-level implementation.
Feature Breakdown:
- Autofill logic: Selects SKUs based on forecast accuracy and priority ranking.
- Space allocation: Adjusts facings using forecasted demand metrics.
- Placement rules: Ensures high-demand products are placed in high-visibility zones.
Where Is Data-Driven Forecasting Applied?
- Grocery stores forecasting demand for festive products.
- Apparel retailers planning seasonal collections.
- Beverage sections adjusting for summer vs winter demand.
Example:
- A retailer forecasts a 30% increase in cold beverage demand during summer.
- Shelf facings for these SKUs increase from 4 to 6 per product.
- Low-demand winter beverages reduce shelf space by 20%.
What Is the Business Impact of Forecast-Driven Planograms?
- Increase in sales due to better product availability (10–25%).
- Reduced stockouts for high-demand seasonal SKUs.
- Improved inventory turnover and reduced overstock.
- Higher shelf productivity using accurate demand allocation.
Conclusion
Data-driven forecasting combined with planograms ensures precise seasonal shelf planning. By using Nexgen POG, retailers can align demand predictions with shelf execution, optimize space allocation, and maintain high product availability during peak seasons.
FAQ
1. What is data-driven forecasting in retail?
It uses historical sales and trends to predict future product demand.
2. How do planograms use forecast data?
They adjust facings, assortment, and placement based on predicted demand.
3. What is autofill in forecast-based planning?
It assigns SKUs automatically based on forecast priority and performance.
4. How is shelf space optimized using forecasts?
It is allocated based on expected sales volume per SKU.
5. How do retailers measure forecasting success?
By tracking forecast accuracy, sales performance, and inventory turnover.
6. What are the risks of not using data in forecasting?
Retailers may face excess inventory, missed sales opportunities, and inefficient shelf utilization.
7. How often should forecasting be updated?
Forecasting should be reviewed regularly, especially during peak seasons or when market trends change.
