Lost sales occur when customers can’t buy a product because it’s out of stock, leading to immediate revenue loss. If untracked, these missed opportunities distort demand forecasts, causing recurring stockouts and reduced profitability. Tracking lost sales helps businesses identify true demand, prevent under-ordering, and optimize inventory strategies.
Key Points:
- Stockouts cost retailers nearly $1 trillion annually, with 50% of intended purchases lost.
- Tracking lost sales reveals hidden costs like higher shipping fees and customer dissatisfaction.
- Metrics like spill rate (sales lost during stockouts) help quantify these losses.
- Tools like Forthcast integrate lost sales data into forecasts for accurate replenishment planning.
Ignoring lost sales damages forecasts, customer loyalty, and operational efficiency. Businesses can recover revenue and improve inventory management by tracking unmet demand and automating reorder processes.
Helium10 Inventory Management - Avoid Stockouts & Lost Sales
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Main Challenges in Tracking Lost Sales Data
Tracking lost sales is easier said than done. Even when businesses understand its importance, capturing and using this data effectively is a whole other story. Most systems simply aren't designed to measure what didn't happen. But tackling these challenges is key to improving replenishment strategies and avoiding repeated stockouts.
Inaccurate Demand Data
One of the biggest hurdles is the over-reliance on Point-of-Sale (POS) data. This type of data only tells part of the story - it shows what customers bought, but not what they wanted and couldn’t get. As Manfred Reiche, Subject Matter Expert at Alloy.ai, puts it:
"Even POS doesn't always fully capture true demand as it only reflects actual purchases. It doesn't tell you what was desired, but not purchased, because your product was not available."
This creates "constrained sales data", meaning your records only reflect what you sold, not the full market demand. This incomplete picture can lead to forecast decay, where inaccurate data causes ongoing understocking issues. Without intervention, this cycle can spiral into a chronic problem, forcing businesses to manually tweak their forecasts just to stay afloat.
Lack of Real-Time Monitoring
Another major issue is the absence of real-time tracking. Without it, businesses can’t identify exactly when a product goes out of stock or calculate how many sales are lost as a result. To make matters worse, many ERP systems don’t store daily inventory snapshots. Without these historical records, it’s impossible to compare in-stock and out-of-stock days to calculate metrics like the "spill rate" - the proportion of customers who walk away when they find a product unavailable.
This lack of visibility often traps businesses in reactive replenishment. They only realize they need to restock once the shelves are empty. Meanwhile, customers who encounter stockouts - whether online or in-store - disappear without leaving any trace of their unmet demand. Even with access to real-time data, quantifying these missed opportunities remains a tough challenge.
Difficulty Estimating Unconstrained Demand
Figuring out what customers would have bought if stock had been available is no small feat. In e-commerce, the average Lost Sales Ratio falls between 20-30%, meaning about one in four potential purchases is lost due to stockouts. Yet most systems aren’t equipped to estimate this accurately.
The available methods - Exclusion (removing out-of-stock data), Imputation (guessing potential sales), and Flagging (marking stockout events) - all come with flaws. These range from losing valuable insights to relying on highly detailed historical data and making speculative assumptions. On top of that, factors like lead time uncertainty and "order crossing" (when orders arrive out of sequence) add even more complexity. This makes it nearly impossible to pinpoint when demand was unmet versus when it was merely delayed.
How Tracking Lost Sales Improves Replenishment Planning
Tracking lost sales turns incomplete data into actionable insights, helping you set accurate reorder points and prevent stockouts. Let’s break down how identifying these gaps leads to smarter inventory decisions.
Capturing Unconstrained Demand
Your point-of-sale system tells you what customers purchased, but it doesn’t capture what they wanted to buy when shelves were empty. This difference separates constrained demand (what you sold) from unconstrained demand (what you could have sold). By tracking lost sales, you can estimate the true demand for your products. Without this data, forecasting systems consistently underestimate demand, creating a vicious cycle where stockouts lead to smaller forecasts, which then cause even more stockouts. Treating lost sales as actual demand helps you set reorder points that reflect market appetite and reduces the risk of chronic understocking. In fact, when items are unavailable, retailers lose nearly half of their intended purchases.
Using Historical Trends and Anomaly Detection
Not all disruptions are created equal. A one-time weather event delaying shipments is very different from a recurring pattern of understocking during peak sales periods. Anomaly detection helps distinguish these scenarios, allowing you to refine forecasts. By analyzing historical data - like comparing stores that didn’t run out of stock during the same promotion - you can fill in the gaps and create a more accurate time series for forecasting tools. Ignoring lost sales skews demand predictions, but tracking them ensures your forecasts reflect reality.
Improving Forecast Accuracy
Lost sales data makes your forecasting system smarter. When zero sales during a stockout are recognized as unmet demand, your system avoids lowering future forecasts. This prevents a dangerous cycle where stockouts lead to smaller forecasts, reduced inventory, and further stockouts. Tracking lost sales also allows you to calculate metrics like the "spill rate", which measures how many customers leave without buying when a product is unavailable. For companies with high stockout rates, the revenue loss from unmet demand can reach millions annually. What’s worse, 32% of customers will stop shopping with a brand they love after a single bad experience, such as finding their desired item out of stock.
Steps to Implement Lost Sales Tracking in Replenishment Strategies
3-Step Process to Implement Lost Sales Tracking in Inventory Management
Turning the concept of lost sales tracking into actionable steps requires a clear plan. Here’s how to embed this practice into your operations to avoid stockouts and improve demand forecasting.
Monitor Inventory Levels in Real Time
Start by taking daily inventory snapshots for every SKU. Many ERP systems don’t keep historical stock records, so this step is vital for determining when items went out of stock and for how long. These snapshots create a dependable baseline for lost sales tracking.
Ensure your data is synchronized across all sales channels, whether it’s Shopify, WMS, 3PLs, or other marketplaces. Without proper synchronization, your system might display inventory that’s actually unavailable, frustrating customers and skewing lost sales data.
Pay attention to the right metrics. Instead of focusing solely on the fill rate (the percentage of fulfilled orders), prioritize your in-stock rate. This metric reflects the percentage of demand you were prepared to meet with available inventory. Fill rates overlook potential customers who never placed orders due to stockouts. To measure your spill rate (lost sales during stockouts), compare average daily sales on days when items were in stock versus out of stock.
Use AI-Driven Tools for Accurate Estimation
When managing hundreds or thousands of SKUs, manual calculations aren’t practical. AI-driven tools can analyze detailed SKU-level point-of-sale data to estimate what you could have sold during stockout periods. The critical part is ensuring these systems treat lost sales as part of demand, not just as a reporting metric.
Many systems track lost sales as a KPI but fail to integrate this data into demand forecasts. Use imputation methods and categorical flagging to distinguish between demand fluctuations and supply chain issues. This approach ensures your demand data remains accurate, feeding into better stock level optimization.
Automate Reorder Alerts and Purchase Orders
AI tools can estimate lost sales, but automation is key to acting on those insights. Automating the reordering process helps you avoid delays and future stockouts. Set up automated reorder alerts that notify you when SKUs dip below safety stock levels, accounting for lead times and demand.
Look for systems that don’t just send alerts but also calculate optimal order quantities. This eliminates guesswork and aligns purchasing decisions with actual demand, including lost sales data. By integrating lost sales into your forecasting engine, your inventory system can proactively meet demand as soon as stock is replenished, rather than scrambling to catch up.
Finally, maintain data accuracy with regular physical inventory counts. This ensures your digital records match actual stock levels, preventing errors that could disrupt your replenishment strategy.
How Forthcast Helps Track Lost Sales and Optimize Replenishment
Forthcast addresses the challenges of inaccurate and delayed demand data, enabling businesses to track lost sales and streamline their replenishment processes effectively.
Features for Tracking Lost Sales
Forthcast takes stockouts seriously by recording them daily and calculating unconstrained demand - the sales that could have occurred if inventory had been available. This approach eliminates the "forecast to zero" issue, where stockouts lead to reduced future projections.
"The system figures the lost sales as if they were sales and your forecast for the year stays at [the original level]. When [the item] starts shipping again, your system is ready to keep up with sales with no manual interventions needed." - Stuart Dunkin, CEO, Data Profits
By reintegrating lost sales into forecasts, Forthcast ensures that stockouts don’t cause a downward spiral in demand predictions. Its anomaly detection tools flag out-of-stock events and use imputation to fill in missing sales data, maintaining a smooth time series. This means businesses can see a clearer picture of true consumer demand - not just recorded transactions. With SKU-level tracking, companies can pinpoint which products are causing revenue losses.
Smarter Forecasting and Reorder Recommendations
Forthcast doesn’t stop at tracking lost sales - it builds on this data to create smarter forecasts. It provides 6-month demand projections that treat lost sales as part of historical demand. The platform also triggers automated reorder alerts based on sales velocity, current inventory, and supplier lead times. For recurring items, Forthcast recalculates usage by factoring in lost-sales days multiplied by average daily demand. These features help businesses maintain the right inventory levels, cutting down on both stockouts and overstocking.
Boosting Profitability with Better Inventory Management
By capturing unconstrained demand, Forthcast helps Shopify merchants recover revenue lost to repeated stockouts. Its dynamic safety stock adjustments adapt to changing demand patterns and supplier performance, ensuring businesses maintain the right inventory buffers without tying up excess capital. The platform provides a centralized view of inventory across warehouses and sales channels, closing data gaps. With automated purchase order generation, Forthcast doesn’t just track issues - it actively works to prevent them.
All these advanced tools come at a highly accessible price of $19.99 per month, with a 14-day free trial. This makes sophisticated sales tracking and inventory optimization available to businesses of all sizes.
Conclusion
Tracking lost sales helps businesses identify unrealized demand, leading to smarter inventory decisions. Without this data, stockouts are recorded as "zero sales" in forecasting systems, which reduces future projections. This creates a cycle of under-ordering and consistent missed revenue. By capturing the true demand, companies can improve inventory forecasting accuracy and replenishment planning.
Take this example: A company generating $100M in annual sales with a 50% spill rate could lose millions of dollars every year due to untracked stockouts. On top of that, 32% of customers may stop supporting a brand they love after just one bad experience.
"If you don't account for these OOS events by adjusting the data set going into your models, they can't learn from the mistake, and you're doomed to repeat it."
– Manfred Reiche, Subject Matter Expert, Alloy.ai
Addressing lost sales allows businesses to align their strategies with actual market demand. Treating unfulfilled sales as valid demand stabilizes forecasts, protects customer loyalty, and supports replenishment strategies that focus on maximizing ROI.
By leveraging tools that capture unconstrained demand, flag out-of-stock events, and automate reorder triggers, companies can break free from the cycle of under-forecasting. These actions turn missed opportunities into actionable data, paving the way for a replenishment strategy that reflects the real market potential.
For Shopify merchants, solutions like Forthcast make lost sales tracking straightforward and accessible. Starting at $19.99 per month with a 14-day free trial, it’s a practical way to implement these strategies and regain control over your inventory.
FAQs
What’s the easiest way to estimate lost sales during stockouts?
The simplest method to gauge lost sales is to calculate the revenue missed during stockouts. This involves considering factors such as how long the product was unavailable, the expected daily sales, and the product's price. A widely used formula is: (Expected Daily Sales - Actual Sales) × Product Price × Out-of-Stock Days.
For a more precise estimation, demand forecasting tools can come in handy. These tools analyze both historical and real-time data, offering a clearer picture of potential lost sales.
How do I calculate spill rate for a SKU?
To figure out the spill rate for a SKU, start by comparing sales data from days when the item was in stock to days when it was out of stock. This will help you estimate the sales lost due to stockouts. Once you have the total spill cost (the value of those lost sales), divide it by the total sales or demand during the same period. This calculation gives you a clear picture of how stockouts are affecting your business.
How does lost sales data change reorder points and safety stock?
Lost sales data provides a clear picture of customer demand during stockouts, offering valuable insights to fine-tune reorder points and recalibrate safety stock levels. By incorporating this information, businesses can improve inventory planning, strike a balance between supply and demand, and minimize the risks of both overstocking and missed sales opportunities.
