Storekeeper
Forecasting

Demand forecasting software, demand planning tools and inventory forecasting software that end in a reorder decision

A forecast that stops at a chart just moves the guessing one screen later. Storekeeper's forecasts finish the job: a reorder quantity, an expedite warning, or a markdown flag, per SKU, recalculated every day from your own sales history.

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SKU On hand Cover

SKUs, scroll for the rest

A live preview of Storekeeper's forecasting engine on fictional sample dataon the rows you pasted. The full product connects to your POS and store and runs this continuously.

The short answer

Demand forecasting software predicts how many units of each SKU you will sell over a planning horizon, from that SKU's sales rate, trend and seasonality. Demand planning software takes the forecast one step further and turns it into supply decisions: reorder points, order quantities, safety stock and purchase orders. Storekeeper does both from $49 a month for a single location, with auto-drafted POs on the $149 Growth plan. Enterprise demand planning suites (Netstock, ToolsGroup, Blue Ridge, o9) do the same for large multi-warehouse networks at quoted prices.

The method

From sales rate to verdict, transparently

The demo above runs this exact chain on sample data. Nothing is a black box; every number can be traced back.

1

Rate and trend

Each SKU's average weekly sales, adjusted by its recent trend: a rising SKU forecasts hotter than its average, a fading one cooler. Twelve months of history lets it see last year's peak.

2

Horizon demand

The rate projected over the window you plan in: 30, 60 or 90 days. This is the demand the stock on hand has to survive.

3

Cover vs lead time

Days of cover at the current rate, compared to the supplier's lead time plus safety stock. This comparison is where risk lives.

4

The verdict

Healthy, reorder (with quantity), stockout risk (expedite), or dead stock (with the frozen dollars). A decision, not homework. Reorder lines roll into draft POs on our inventory replenishment software.

Know what you are buying

Demand forecasting software vs demand planning software vs inventory forecasting tools

Vendors use the three labels loosely. The question that separates them is what the output is: a curve, a plan, or an order.

Category Output Typical buyer Storekeeper
Demand forecasting software A predicted demand curve per SKU, product line or region, with accuracy metrics Finance and S&OP teams sizing revenue, budgets and capacity Per-SKU forecast with trend and seasonality, visible on every verdict
Demand planning software The forecast plus supply decisions: reorder points, safety stock, order quantities, purchase plans Buyers, planners and operations leads who place the orders Reorder point, quantity, expedite flag and draft PO per SKU, daily
Inventory forecasting software Projected stock levels over time: when each SKU runs out and how much is left at horizon Retailers and ecommerce brands managing stockouts and overstock Days of cover per SKU against lead time, with dead stock priced in dollars
Sales forecasting software Pipeline and rep-level revenue forecasts from a CRM Sales leaders Not what Storekeeper does; look at your CRM's forecasting module

Why "AI forecasting" usually disappoints, and what we do differently

Most inventory forecasting tools fail in one of two ways. Either they are a rules engine wearing an AI badge, which means you are still setting the thresholds by hand; or they are a genuine model that outputs a demand curve and leaves the hard part, so what do I order on Monday, entirely to you.

Storekeeper's position is boring and deliberate: the arithmetic is transparent planning math you could audit line by line, and the machine learning works where it actually helps, reading demand signals, trends and seasonality per SKU, and reading messy real-world data. You can see the philosophy in the live demo: paste rows in any format and the AI reads them, but every forecast, cover figure and reorder quantity comes from the same auditable engine that scores the samples.

Forecasts feed straight into drafted purchase orders, stockout prevention and dead-stock cleanup, because a forecast that does not change an order was just an expensive chart.

Dedicated planning tools exist at the mid-market end, and the best known is Sage's Inventory Planner, which sits on top of your existing system and quotes on the volume of inventory you manage. Our Inventory Planner alternatives page compares it honestly against the platforms that bundle forecasting, and explains why planning is priced separately almost everywhere you look.

How to forecast inventory demand per SKU, and which method each product needs

To forecast inventory demand, start with 12 months of clean sales history per SKU, match a method to each product's pattern, adjust for seasonality, trend and planned events, then grade the forecast against actual sales every period. A forecast only pays for itself when it moves the reorder point, so the last step is feeding it into what you buy.

Clean history matters more than the model. Strip out one-off spikes such as a bulk order or a viral week, separate promotional sales from baseline demand, and treat days when a SKU was out of stock as missing, not as zero demand. A spreadsheet forecast that skips this bakes last year's stockouts into next year's buy. If your sales sit in a storefront, two marketplaces and a POS, you also need them pulled into one dataset keyed by a shared SKU before any method works. Storekeeper does this cleanup on import and flags the SKUs where history is too short or too broken to trust.

Demand pattern Method that fits Where it breaks What Storekeeper does
Steady, flat sellers Moving average Lags behind any real trend Weighted recent rate, so a slow drift still shows up
Growing or fading SKUs Exponential smoothing with trend Overshoots after a one-off spike Trend measured on cleaned history, spikes excluded
Seasonal products Seasonal models such as Holt-Winters Needs one to two full years of history Raises the reorder point ahead of last year's peak, by lead time
Slow, lumpy long tail Intermittent-demand methods Never forecasts cleanly; error stays high Smaller buffers and a dead-stock flag instead of false precision
New SKUs, no history Judgment or a similar product Optimism; launch buys run high Borrows the curve of a product you nominate until real sales arrive

Grade every forecast. Most teams track mean absolute percentage error (MAPE) and bias. Bias is the dangerous one: a forecast that runs 15 percent high on every SKU quietly builds excess stock and carrying cost across the whole catalog, while a forecast that runs low shows up as stockouts. Storekeeper sizes safety stock from each SKU's own error, so a noisy product gets a bigger buffer and a predictable one ties up less cash.

Then make the forecast move the trigger. Expected demand over the supplier lead time plus that buffer is the reorder point; when stock crosses it, you order. Most inventory systems let you type a reorder point once and never touch it again. Here it is recalculated daily, and on Growth the order quantity lands in a draft purchase order for you to approve.

Who buys demand planning software

Demand planning software for small business, retail, ecommerce and QuickBooks shops

Enterprise suites assume a planning team. These four buyers have one person and a spreadsheet, and they need the decision, not the model.

Shopify and POS retailers who lost Stocky

Shopify shut Stocky down on August 31, 2026, and Shopify admin has no per-SKU forecast or suggested order quantity. Storekeeper brings that job back for every variant. Details and a migration plan on our Stocky replacement page.

QuickBooks users with a reorder point and no forecast

QuickBooks Online and Enterprise reorder at a level you type in; neither forecasts demand per item. Storekeeper reads the sales history and hands back the reorder point and the PO. See QuickBooks inventory forecasting and SKU forecasting.

Ecommerce brands with variant-heavy catalogs

Apparel, footwear, supplements: demand is uneven across sizes, colors and flavors. A per-variant forecast stops you reordering a whole size run when two sizes sold. Our ecommerce inventory management page covers multichannel sync.

Distributors with long lead times

A 60-day lead time means today's order is a bet on demand two months out. Forecast-driven reorder points are the only thing that survive that gap. See wholesale inventory software.

Compare before you buy

Demand planning tools compared on price and what they hand back

Prices from each vendor's own pricing page. Where a vendor only quotes, we say so.

Tool Published price What the forecast becomes Best for
Storekeeper $49/mo Starter, $149/mo Growth ($24 and $74 billed yearly) Reorder point, quantity, expedite flag, dead-stock dollars; draft POs on Growth 200 to 20,000 SKUs, one buyer, up to five locations
Inventory Planner (Sage) Quote only, based on inventory volume Replenishment recommendations and POs on top of your existing system Larger catalogs that want a long-established planning layer
Prediko $49/mo under $100k GMV; higher bands quoted Forecast, purchase plan and POs for Shopify stores Shopify brands comfortable with pricing that rises with GMV
StockTrim By revenue band, $67 to $397/mo under $5M (all bands) Forecast and order recommendations; BOM forecasting +$50 to +$100/mo in those bands Brands that also make products from raw materials
Katana Core from $299/mo plus order and location usage Planning, forecasting and AI replenishment included on every plan Makers who need production scheduling alongside forecasting
Zoho Inventory, QuickBooks From $29/mo (Zoho) or included in QuickBooks tiers No demand forecast; alerts at a reorder point you set by hand Counting and control, with the buying decision left to you
Netstock, ToolsGroup, Blue Ridge, o9 Quote only Multi-echelon demand and supply plans tied to an ERP, with a planning team running them Distributors and manufacturers on NetSuite, SAP, Dynamics or Oracle

Revenue and GMV pricing looks cheap for a small store and climbs as you grow; Storekeeper prices by location and channel instead. Plan details are on the pricing page, and our best inventory management software comparison covers the full platforms that bundle forecasting with orders and warehousing.

Frequently asked

Demand forecasting and demand planning software questions, answered

What is demand planning software?
Demand planning software forecasts how much of each product will sell over a planning horizon and turns that forecast into supply decisions: reorder points, safety stock, order quantities and purchase plans. It differs from plain demand forecasting software, which stops at the predicted demand curve, and from sales forecasting software, which projects revenue from a CRM pipeline.
What is the best demand forecasting software?
For a business with one buyer and 200 to 20,000 SKUs, the best demand forecasting software is one that hands back an order decision, not just a curve: Storekeeper from $49 a month, Prediko from $49 for Shopify stores under $100k GMV, or Katana from $299 if you also manufacture. For multi-warehouse distributors on an ERP with a planning team, Netstock, ToolsGroup and Blue Ridge are the usual shortlist.
Is demand planning the same as demand forecasting?
No. Demand forecasting is the prediction: units per SKU per period, from history, trend and seasonality. Demand planning is the process around it: agreeing the forecast, then deciding what to buy, when and how much, including safety stock and supplier lead times. Forecasting is an input; planning is the decision. Storekeeper does both and shows the forecast behind every reorder verdict.
How much does demand planning software cost?
Published prices for demand planning tools aimed at small and mid-size businesses run from about $49 to $400 a month: Storekeeper Starter $49 and Growth $149, Prediko from $49, StockTrim $67 to $397 by revenue band under $5M, Katana Core from $299 plus usage. Inventory Planner, Netstock, ToolsGroup and Blue Ridge quote per deployment and usually add an implementation project.
Does QuickBooks have demand forecasting?
No. QuickBooks Online and QuickBooks Enterprise track quantity on hand and alert at a reorder point you enter per item; Enterprise with Advanced Inventory can create a PO at that fixed level. Neither models demand per SKU from sales velocity, trend or lead time. Storekeeper connects to the sales history and adds the forecast, reorder point and draft PO on top.
How do you forecast inventory demand?
Pull 12 months of sales per SKU, remove one-off spikes and stockout days, and pick a method that fits each product: a moving average for steady sellers, trend smoothing for growing ones, a seasonal model for peaks. Adjust for planned promotions, measure the error each period, and feed the forecast into the reorder point so it changes what you buy.
How do you measure inventory forecast accuracy?
Compare forecast to actual units sold per SKU each period. Mean absolute percentage error (MAPE) shows how far off you are on average, and bias shows whether you consistently over or under-forecast. Bias costs more: a steady 15 percent over-forecast builds excess stock across the catalog. Fix the worst SKUs first and accept that slow movers stay noisy.
How much sales history does demand forecasting software need?
Six months of order history produces a usable rate and trend for most SKUs. Twelve months lets the model see last year's seasonal peaks and raise reorder points ahead of them. SKUs with less history are forecast from a similar product you nominate until they have enough sales of their own.

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