Dynamic pricing software
that shows its work.

Dynamic pricing software adjusts prices automatically as market conditions change, instead of leaving them fixed until someone edits a price list by hand. It reads signals such as demand, stock cover, competitor prices, cost inputs, and time to expiry, applies the pricing rules the business has agreed on, and writes the result back to the storefront, ERP, or quoting system. Two separable jobs sit inside that: the data side that produces the signals, and the decision side that turns signals into a price the company is willing to defend. GoRules is the decision side, a pricing rules engine where strategy tables, guardrails, and rounding rules live in one versioned, auditable place.

Take SKU-4471, a headphone listing at $129.00 with a $96.00 unit cost. Overnight demand runs at 1.12 times its 28-day baseline, stock cover is 14 days, and the cheapest tracked competitor sits at $126.50, so the listing is 2.0% above market. The audio strategy table matches that combination and proposes a 3.5% increase, or $133.52. The guardrail policy then runs: the 8% daily move cap passes, the 22% category margin floor passes at 28.4%, and the price-ending rule rounds to $133.99. The price publishes with all four rules and their inputs recorded, so the move is still explainable months later.

A price optimization platform estimates what the market will bear: elasticity curves, demand forecasts, recommended prices. A pricing rules engine executes the policy you have decided on: which strategy applies to which segment, where the floors and caps sit, how prices round, when a change needs approval. Optimization output is an input to the rules engine rather than a replacement for it, because a recommendation still has to clear margin floors, contract minimums, MAP agreements, and category strategy before it becomes a real price. GoRules is the rules engine, so model scores and recommended prices arrive as plain inputs and the final number stays a readable rule outcome.

Guardrails run as an ordered Policy after the strategy tables and can only narrow the result: category margin floors, maximum movement per day and per week, key-line price locks, contract and MAP minimums, and a route-to-review outcome for anything outside the band. Because they are decision-table rows rather than code, the pricing team can read them and finance can approve them. Before a change ships, branch the policy and run last month's catalog through both versions in the simulator to compare price moves and margin impact. If something still misbehaves in production, roll the release back in one click.

Regulators draw a line between dynamic pricing, which responds to market conditions and shows every shopper the same price, and personalized pricing, which sets a price from an individual's data. The EU Omnibus Directive requires traders to disclose when a price has been personalized through automated decision-making, the EU Price Indication Directive requires a discount to reference the lowest price of the previous 30 days, and New York's Algorithmic Pricing Disclosure Act imposes its own notice on personalized algorithmic prices. Because every price rule in GoRules is readable and versioned, you can show which inputs a price actually used, evidence that customer identity was not one of them, and produce the change history behind any promotional reference price. GoRules supplies the traceability; the obligations remain yours.