forecasting, not history
The highest-cost decisions in e-commerce are made under uncertainty. Forecasting reduces the uncertainty — it does not eliminate it.
Inventory orders placed without demand projections
An inventory purchase order placed based on trailing average sales without accounting for seasonal demand shifts, promotional calendar, or advertising spend changes will be wrong in predictable directions. The forecast does not have to be perfect — it has to be less wrong than the trailing average.
Advertising budget set without revenue projections
A monthly advertising budget set based on last month's spend without projecting the expected revenue impact of that spend produces a budget that may be too high (if the category is slowing) or too low (if seasonal demand is increasing). The projection is the input to the budget — not a output of it.
Expansion decisions made without market size estimates
Launching into a new marketplace, category, or product line without a revenue projection forces the decision on intuition. A demand estimate — even a rough one built from category data — changes the decision from a guess to a calculated bet.
for the decisions that require them.
Each model is built for a specific decision. Forecasting models built for the wrong decision produce precise wrong answers.
Demand Forecasting
SKU-level sales projections for the next thirty, sixty, and ninety days — adjusted for seasonality, promotional calendar, and advertising spend changes. The demand forecast is the input to inventory reorder quantities and advertising budget allocation.
Revenue Projection
Channel-level revenue projections forward thirty to ninety days based on demand forecast, conversion rate assumptions, and traffic projections from advertising spend plans. The revenue projection is the input to financial planning and cash flow management.
Inventory Coverage Projection
Forward-looking inventory coverage by SKU: how many days of stock remain at current and forecasted demand rates. Stockout risk identified before it appears in the trailing data. Reorder quantities sized to the forecasted demand, not the trailing average.
Scenario Modeling
Alternative demand scenarios for high-impact variables: a promotional event, a competitor entering the category, or an advertising spend change. Scenario models quantify the revenue and inventory impact of decisions before they are made.
Calibrate against actuals. Update continuously.
A forecasting model that is not updated against actuals becomes a historical artifact. Ours is updated monthly.
Historical Data Foundation
Two to three years of sales data by SKU where available, normalized for out-of-stock periods, promotional events, and external demand shocks. The historical foundation is the baseline from which the forecast model is built.
Model Build & Calibration
Demand model built with seasonality decomposition, trend adjustment, and promotional lift factors. Model accuracy backtested against the most recent ninety days. Calibration continues monthly as actuals replace projections in the historical series.
Delivery & Decision Integration
Monthly forecast delivery to the client team with variance analysis from the prior projection. Forecast outputs connected directly to inventory reorder recommendations and advertising budget planning.
for every significant decision.
Every forecast includes a confidence range, not just a point estimate. Decisions should be made from the range, not the midpoint.
30/60/90-day SKU-level demand projections with seasonality and promotional adjustments.
Channel-level revenue forecasts for financial planning and budget allocation.
Forward-looking days-of-cover by SKU with stockout risk identification.
Alternative projections for key decision variables.
Actual versus projected comparison with model calibration update.
Forecasting models integrated with ARIA's inventory monitoring and performance reporting.
Data Analytics & AI includes additional services that compound on this one.
Plan from projections,
not from last month
We work through referrals. If you have been referred, send us a message and we will show you what a demand forecast would change about your current inventory and budget decisions.