Forecast sales and plan stock

Retailers forecast sales per item and store to plan stock accordingly

Needs setupAI Act: no extra obligationsForecasting from figuresRetail & consumer goods

Fits: Sales · Purchasing · Logistics & warehousing

Fewer empty shelves and less slow-moving stock. Orders match actual demand more closely.

Is this for you?

  • You have at least one to two years of sales data per item.
  • Orders are currently placed by gut feeling or based on the previous year.
First step today

Export the weekly sales of an important item over two years and use the template below to have AI show seasonality, trend and outliers.

How to go about it

  1. Define items, stores and period
  2. Collect sales data and influencing factors
  3. Have a sales forecast created
  4. Check against actual sales
  5. Feed it into order suggestions
  6. Retrain every month

Templates to copy

Try it now
in the training
Analyse
in the training
Plan the rollout
in the training
Included in the training

The complete guide

  • 6 steps explaining exactly what to do
  • 3 proven templates to copy into your own AI
  • Safe use: data, checking, deciding, informing
  • Pitfalls, effort and how to recognise success

With the training you get all 430 guides for as long as your access runs.

See the trainingOne-off per person, no subscription

Same approach, other use cases

22 more use cases follow the pattern “Forecasting from figures”.

Assess storm and flood risk per addressDevelop and test trading strategies with machine learningEstimate market-rate salaries for positionsEstimate yields and plan harvest and marketingForecast clients’ demand for skilled workersForecast crowds and waiting timesForecast liquidity for the coming weeksForecast material requirements and suggest reordersForecast passenger numbers and adjust frequencyForecast revenue from the pipelineForecast staffing needs from care grades and occupancyForecast wind and solar feed-in
‹ PreviousSee all use casesNext ›

G-HK-01 · Legal status 08.10.2026