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Lost revenue, wasted ad spend, and a ranking penalty that outlasts the restock.","2026-10-23","A stockout is a SKU running out while demand exists. The four costs — lost sales, wasted ads, ranking decay, and substitution — and how to size them.",false,"md",{},"\u002Fglossary\u002Fstockout",3,[336,337,338,339,340],"safety-stock","reorder-point","contribution-margin","low-margin-sku","bayesian-inference",{"title":342,"description":329},"What is a Stockout? 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On a marketplace the listing either disappears from search or shows as unavailable, so the cost is not only the orders that did not happen: advertising that continues to run against an unavailable listing is spent for nothing, search ranking decays during the out-of-stock window and takes time to recover after restock, and a share of the shoppers who wanted the product buy a competitor’s version and do not come back. The visible lost revenue is usually the smallest of the four costs.",[398,399,370],"h2",{"id":369},[401,402,404],"pre",{"language":403},"text",[405,406,408],"code",{"class":407},"language-text","Direct lost contribution = daily demand × days out of stock × contribution per unit\n\nTotal stockout cost ≈ direct lost contribution\n                      + ad spend during the window\n                      + ranking recovery cost\n                      + permanently switched customers",[398,410,373],{"id":372},[401,412,413],{"language":403},[405,414,415],{"class":407},"A SKU sells 22 units\u002Fday at ฿180 contribution and runs out for 9 days\nduring a campaign period.\n\nDirect lost contribution = 22 × 9 × 180 = ฿35,640\nAds still running on the listing              ฿6,200\nEstimated ranking recovery: ~2 weeks at reduced impressions\n\nThe restock order that would have prevented it was worth ฿16,000.",[398,417,376],{"id":375},[394,419,420],{},"Four things, and only the first is easy to count. Lost contribution is daily demand times days out times contribution per unit, and it is the number most sellers stop at. Advertising is the second: ads that keep running against a listing nobody can buy are pure waste, and on automated campaigns they often keep running because the campaign is set at the shop or category level. Ranking is the third and the most persistent, because marketplace search rewards recent sales velocity and a zeroed listing stops accumulating it; recovery after restock is measured in weeks, not days. The fourth is substitution — a share of buyers find a competitor and stay there — and it is the only one that never comes back.",[398,422,379],{"id":378},[394,424,425],{},"Because demand on a mega-campaign day can be several multiples of a normal day while replenishment lead times are unchanged, so the buffer that comfortably covers ordinary variation is consumed in hours. The compounding factor is that campaign demand is also the most valuable demand: the traffic is subsidised by the platform, the conversion rate is higher, and the ranking gained during a high-traffic window carries forward. A stockout on 11.11 therefore costs several times what the same stockout costs in an ordinary week, which is why campaign-aware cover — planning stock against the forecast for the specific day, not the trailing average — matters more than a higher buffer year-round.",[398,427,382],{"id":381},[394,429,430],{},"No, and treating it as such is how shops end up with dead capital. Both are errors in the same decision, and the correct trade-off depends on the ratio between the contribution lost per unit of missed demand and the cost of holding a unit that does not sell. For a high-contribution, non-perishable, stable-demand product the stockout cost dominates and a generous buffer is right. For a low-contribution, seasonal, or fashion-cycle product the overstock cost dominates and running thin is right. This is the newsvendor trade-off, and it is why a single service-level target applied to a whole catalogue is always wrong somewhere.",[398,432,385],{"id":384},[394,434,435],{},"Stockouts cost more than the lost revenue, and the extra costs are the ones no report shows. Ads that ran during the window are pure waste, the ranking algorithm demotes listings that go unavailable during high-traffic periods, and on live commerce a stockout mid-session ends the velocity instantly. Because the costs are invisible and the restock cost is visible, shops systematically under-invest in cover.",[437,438,440],"blog-callout",{"title":439},"Common mistake","Planning cover against average demand. Stockouts are caused by variance, not by the mean — a SKU selling 20 a day on average and 60 on a campaign day will run out even though the average is well covered. Cover has to be planned against the distribution of demand over the lead time, which is exactly what safety stock is for.",[398,442,388],{"id":387},[394,444,445],{},"DataGlass forecasts demand per SKU and projects days of cover against current stock, incoming replenishment, and known campaign windows, then ranks restock candidates by the contribution at risk rather than by units. 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Priced by what a stockout costs you, not by a rule of thumb.",{"path":529,"title":530,"short":531,"draft":330},"\u002Fglossary\u002Freorder-point","Reorder point","The stock level that triggers a replenishment order — expected demand over the lead time, plus the safety buffer.",{"path":533,"title":534,"short":535,"draft":330},"\u002Fglossary\u002Fcontribution-margin","Contribution margin","Revenue minus every variable cost of selling one more unit — the profit each sale actually contributes after fees, ads, and fulfillment.",{"path":537,"title":538,"short":539,"draft":330},"\u002Fglossary\u002Flow-margin-sku","Low-margin SKU","A product whose contribution per unit is too thin to fund the attention it consumes — often a former bestseller nobody re-checked.",{"path":541,"title":542,"short":543,"draft":330},"\u002Fglossary\u002Fbayesian-inference","Bayesian inference","Estimating with a range instead of a single number, so a decision can account for how little it actually knows.",1792784981948]