Pricing optimization

Calendar markdowns in a market that moves every day

Your prices come from central guidelines and a markdown calendar: a set percentage off at six weeks, more at eight. Your range keeps growing and turning faster, and the calendar treats every color, size, and store the same.

Competitors with better price data move faster. You mark down items that would have sold at full price, and you hold price on items that needed a nudge weeks ago.

Every price change also has to be explained. Merchants, finance, and increasingly regulators ask what data drove a price and who decided it.

How pricing optimization works

Your pricing team builds explainable demand models in H2O Driverless AI and uses them to suggest prices inside the rules you set.

Step 1: join the signals

Bring together sales and price history by item and store, seasonality, inventory on hand and on order, promotions, and competing prices.

Step 2: model demand and elasticity

H2O Driverless AI builds regression and time series models with automatic feature engineering, to estimate how each item's demand moves with price.

Step 3: suggest prices inside your rules

The model proposes the price or markdown for each item that best meets your margin and sell-through goals, within the floors, ceilings, and brand rules your team sets.

Step 4: explain every suggestion

Reason codes show which factors drove each price, such as stock depth, a trend, or a competing offer.

Step 5: approve, measure, and refresh

Your team approves the prices, and updated forecasting shows how each change performed.

Keeping people in charge of pricing policy