Demand forecasting software is an important part of a successful retail management system. It helps retailers estimate how much product customers will buy in a given period using past sales, current inventory, and planned promotions.
In April 2026, US retail inventories reached a value of $827.3 billion, up 3% from April 2025, according to the US Census Bureau. With figures that high, inaccurate demand forecasting has greater repercussions for a retailer’s liquidity and profitability. A bad forecast can leave too much money in slow-moving stock, or not enough product to serve customers.
This guide covers how demand forecasting software works and compares the available tools for ecommerce and retail businesses.
What is demand forecasting software?
Demand forecasting software is a retail tool that retailers use to predict future product demand. The software analyzes historical sales data alongside inventory movement and seasonal trends.
Demand forecasting estimates how many orders a business will receive over a selected period of time. For ecommerce retailers, forecasts should connect to real sales data including online store orders, in-store point-of-sales (POS) data, marketplace orders, inventory levels, and returns. Accurate estimates also factor in upcoming promotions, and sales events. Store owners should also account for new product launches and planned discontinuations to keep data consistent.
Demand planning software is used to calculate:
- Sales and order volume
- SKU-level demand
- Stockout risk
- Reorder timing
- Seasonal demand
Some software options focus only on generating forecasts. Other platforms connect these predictions directly to back-end operations.
These systems can be used to track inventory replenishment needs, automate purchase orders (POs), and monitor supplier lead times. They can also trigger stock alerts and generate operational reports for the entire commerce team.
Before moving on to the best demand forecasting tools, let’s look at how the category differs from some other related, but not identical, systems:
| Tool | Function | How it helps businesses | Focus |
|---|---|---|---|
| Demand forecasting software | Predicts future demand using historical sales data, seasonality, trends, and external factors | Helps businesses decide what inventory they will need and when | Forecast accuracy, demand signals, and planning future purchases |
| Inventory management software (IMS) | Tracks inventory levels, movements, and availability across locations | Helps businesses manage what inventory they currently have | Stock counts, reorder points, transfers, and fulfillment |
| Enterprise resource planning (ERP) software | Connects core business functions such as finance, procurement, inventory, manufacturing, and operations | Serves as a central system of record for business data and processes | Coordinating transactions and workflows across the organization |
| Financial planning and analysis (FP&A) software | Supports budgeting, forecasting, financial modeling, and scenario planning | Helps businesses understand the financial impact of operational decisions | Revenue, expenses, cash flow, profitability, and business performance |
In summary:
- Demand forecasting software predicts demand.
- Inventory management software tracks inventory.
- ERP software manages business operations.
- FP&A software plans financial performance.
The best demand forecasting software options for ecommerce and retail
Demand forecasting software ranges from tools that create ecommerce reports to complete enterprise-planning platforms.
The best option depends on how much historical data a business has and whether it needs simple forecasts or full replenishment planning.
| Tool | Suited for | Key features | Shopify integration | Starting price |
|---|---|---|---|---|
| Shopify Analytics and reports | Shopify beginners | Sales and order forecasts | Native Shopify feature | From $29/month annually (for Shopify) |
| Inventory Planner by Sage | Replenishment planning | Forecasts, POs, locations | App available in the Shopify App Store | Free install; quote-based |
| DemandMind | SKU-level forecasting | Seasonality, drivers, exports | App available in the Shopify App Store | From $19/month |
| Fabrikatör | Automated replenishment | Forecasts, POs, lead times | App available in the Shopify App Store | From $99/month |
| Stockie | Alerts and purchase orders | Reorders, alerts, forecasts | App available in the Shopify App Store | From $4.99/month |
| Netstock | Mid-market planning | AI-powered demand planning | Custom integration | Custom pricing |
| SAP IBP | Enterprise planning | AI and statistical model demand planning | Custom integration | Price upon request |
| Blue Yonder | Enterprise retail planning | Demand sensing, scenarios | Middleware | Quotation-based |
| o9 | Scenario planning | AI forecasts and sales and operations planning (S&OP) | Custom integration | Quotation-based |
| DemandForecast.ai | AI-driven forecasting | SKU-level forecasts, stockout alerts, trend detection | App available in the Shopify App Store | From $19/month |
Built-in Shopify ecommerce reports and spreadsheets
These native tools are often sufficient for early-stage businesses or those with stable demand. They don’t require extra software to track key retail data.
These reports cover key metrics for retailers:
- Total sales over time. This report tracks revenue changes across days, weeks, or months.
- Total sales by order. This metric shows the gross value of each individual transaction.
- Inventory sold daily by product. This data monitors item volume to track daily stock turnover.
- Sales attributed to marketing. This report identifies which campaigns generate buyer purchases.
- CSV exports. These files let businesses transfer data into external tools for custom analysis.
- Spreadsheet forecasts. These spreadsheets predict future demand and revenue using sales trends.
Store owners with as little as eight weeks of consistent weekly orders can start using demand forecasting. After one year of orders, they can begin forecasting seasonality, according to Shopify.
Shopify inventory planning apps
When spreadsheets aren’t enough to track growing stock, stores can transition to dedicated inventory management software.
Retailers can evaluate these tools in the Shopify App Store, which includes an inventory category and more than 16,000 apps.
Four apps that help manage stock:
- Inventory Planner by Sage. Forecasts future demand and automates replenishment across multiple stock locations.
- DemandMind. Runs SKU-level forecasts that account for seasonal shifts and tracks performance metrics.
- Fabrikatör. Uses AI for forecasting and automates PO creation based on supplier lead times.
- Stockie. Generates accurate forecasts from Shopify sales history and sends low-stock alerts through Slack or email.
Enterprise demand planning platforms
Large retailers with complex supply chains and multiple locations may need more comprehensive enterprise planning platforms. Systems like SAP IBP and Blue Yonder connect demand planning with ERP and other supply chain systems.
These tools are usually built for larger businesses. Implementation can require significant setup, clean master data, and integration work across multiple systems. Post implementation, developer hours and other costs may be required for upkeep and maintenance.
In its 2025 ERP report, Panorama Consulting Group found a median enterprise software project timeline of nine months and a median project cost of $450,000.
For organizations on the Shopify Plus plan, forecasting tools can connect with Shopify through custom apps, third-party integrations, or APIs.
What to look for in demand forecasting software
Demand forecasting methods can vary, but consider the following when choosing this retail software for your business:
- Ecommerce and POS data integration
- SKU-level and location-level forecasting
- Seasonal and promotional planning
- Replenishment and purchase order workflows
- Explainability and forecast review
Ecommerce and POS data integration
Ecommerce and POS data integration syncs sales channels to show real-time purchasing behavior. When systems don’t sync channels, inventory tracking is inaccurate.
Demand forecasting software tracks these data points:
- Online store orders
- POS orders
- Marketplace orders
- Customer returns
- Order cancellations
- Discounts and campaigns
- Inventory by location
SKU-level and location-level forecasting
Inventory forecasting tracks product demand at each storage location. It shows which exact sizes and colors sell in specific physical stores. Store owners use these insights to allocate items effectively so they don’t tie up capital in excess stock.
Demand forecasting software can evaluate demand across variables such as:
- Variant demand
- Product size and color demand
- Store-level demand
- Warehouse versus store availability
- Stranded inventory
Bentley, a Canadian luggage and travel accessories retailer with more than 125 locations, needed real-time inventory visibility to eliminate channel friction. They partnered with Shopify Plus agency Molsoft to adopt Shopify and Shopify POS, using a custom connector to migrate historical sales data.
After syncing data across its channels in real time, it achieved a 129% year-over-year increase in total revenue, a 74% lift in online sales, and a 17% growth in point-of-sale transactions.
Seasonal and promotional planning
Seasonal events and marketing campaigns change up purchasing patterns. When systems don’t account for these shifts, inventory counts become inaccurate during high-volume periods.
Demand forecasting software coordinates these demand variations to align stock levels with marketing timelines. It can project demand for events like:
- Black Friday and Cyber Monday (BFCM)
- Holiday sales
- New product launches
- Influencer campaigns
- Collabs and limited product “drops”
- Email and paid media spikes
- Discount events
Replenishment and purchase order workflows
Automated replenishment workflows manage reordering tasks based on inventory thresholds and supplier timelines.
Tracking these metrics ensures that businesses restock items before inventory depletes, which keeps supply chains balanced without locking up excess capital.
Demand forecasting software can be used to track demand planning metrics including:
- Reorder points
- Safety stock
- Supplier lead times
- Purchase orders
- Incoming inventory
- Pack sizes and minimum order quantities
- Cash-flow impact
Explainability and forecast review
Software interfaces clarify the logic behind inventory predictions so teams don’t have to guess why numbers changed. Without this transparency, procurement managers cannot verify if a spike reflects a meaningful trend or a data anomaly.
Demand forecasting software should be able to provide explanations including:
- Why a forecast changed
- Which data influenced the forecast
- Confidence level
- Manual overrides
- Forecast vs. actual reporting
To analyze performance over multiple quarters, systems calculate mathematical accuracy using four metrics:
- Mean absolute percentage error (MAPE). Measures the average size of prediction errors relative to actual sales volume.
- Weighted mean absolute percentage error (wMAPE). Adjusts for product volume so high-turnover items don’t distort the overall error rate.
- Forecast bias. Shows if a model regularly overestimates or underestimates demand over time.
- Forecast value add (FVA). Confirms whether a specific analytical step increases accuracy compared to a simple baseline.
Store owners can export data from Shopify or use connected applications to run these comparisons. When reports indicate that forecasts are consistently too high or too low, adjusting the configuration parameters helps align future predictions with market behavior.
How to use Shopify data for demand forecasting
Use Shopify data for demand forecasting by following these steps:
- Pull historical sales and order data
- Add inventory and product availability context
- Add upcoming business context
- Build the forecast and review variance
- Share the forecast with fulfillment partners
1. Pull historical sales and order data
Review historical sales and order records to identify performance patterns over time. Establish a baseline across daily, weekly, and monthly intervals to understand business performance.
If weekly orders don’t fluctuate, eight weeks of consistent data provide a reliable starting point for a basic forecast. When records cover one year, factor in seasonality to account for high-demand and low-demand periods.
Find these metrics in the Shopify admin. The “Sales over time” report, the “Total sales” report, and the “Analytics overview” isolate trends and averages. Break out sales by product, variant, location, and channel. This baseline reveals standard order volumes before marketing adjustments shift consumer demand.
2. Add inventory and product availability context
Inventory planning ensures that fulfillment systems don’t fail during peak shopping periods. Compare current stock levels against sales trends to estimate future supply needs. When using historical sales as a factor in forecasting, don’t overlook inventory-related context. For example, sales history can understate demand if you do not account for periods when selling stopped due to stockouts.
Track stock metrics across the Shopify admin to balance supply with upcoming demand. Start with key data:
- Sales velocity. The Inventory sold daily report tracks product turnover rates.
- Stock levels. Comparing current inventory against sales trends estimates total fulfillment capacity.
- High-risk items. Monitoring specific product categories prevents stockouts during promotional events.
Don’t forget to factor in returns and exchanges when forecasting replacement stock.
This helps turn a sales forecast into an inventory plan, especially as order volume grows.
3. Add upcoming business context
Baseline data only reflects past performance. Marketing initiatives and product changes alter future sales cycles, so historical patterns alone don’t predict upcoming demand accurately.
Gather business plans across departments to identify variables that influence order volumes:
- Upcoming promotional schedules
- Planned product launches and discontinuations
- Adjustments to email marketing and advertising spend
- Influencer placements
- Wholesale orders
- Store openings
Collecting this context before generating a forecast prevents unexpected order fluctuations.
4. Build the forecast and review variance
Combine historical sales data and marketing plans to build a weekly forecast. Reviewing these numbers against actual sales shows where assumptions deviate from reality.
Follow these steps to manage the review process:
- Calculate the expected number of orders for each week.
- Match the forecasted numbers against actual sales data.
- Change the baseline variables for the next cycle if predictions run high or low.
- Focus on overall trends to prepare warehouse operations.
Don’t expect perfect forecasts. Aim for forecasting within a 10% to 15% margin of error.
5. Share the forecast with fulfillment partners
Third-party logistics providers (3PLs) require advanced notice to organize warehouse labor and physical resources. Sending order projections to these partners early deters shipping delays when order volumes rise.
Increase the frequency of forecasting during peak shipping seasons. Reviewing projections every two weeks during holiday periods helps partners match warehouse staffing levels with real-time sales numbers.
Demand forecasting software FAQ
What is the best demand forecasting software for a small ecommerce business?
Early-stage or small ecommerce businesses use built-in tools like Shopify analytics or spreadsheets. As a business expands, they transition to affordable inventory applications like Stockie or DemandMind for dedicated stock keeping unit SKU tracking.
How much sales history do you need for demand forecasting?
Basic demand forecasts require a minimum of eight weeks of consistent weekly order history. To account for high-demand and low-demand seasonal shifts, a business needs at least one year of sales records.
How accurate should a demand forecast be?
Shopify documentation notes that a healthy demand forecast targets a 10% to 15% margin of error. When reports show that predictions run too high or too low, adjusting configuration parameters restores tracking accuracy.
Can Shopify help with demand forecasting?
Store owners forecast demand through built-in Shopify analytics reports, including the “Sales over time” report and the “Total sales report.” The Shopify App Store provides dedicated inventory planning software like Inventory Planner by Sage and Fabrikatör.
For enterprise brands, the Shopify Plus plan supports integrations with advanced planning platforms like SAP IBP or Blue Yonder using custom application programming interfaces (APIs).
