Revenue
Price on demand, inventory and elasticity — with the math exposed.
Dynamic Pricing Engine is dynamic pricing software for teams that want the reasoning shown, not hidden. Plans start at $59 a month with a 14-day free trial.
Dynamic pricing has a reputation problem, and it is deserved. Most implementations are a black box that occasionally prices a product at £0.03 or quietly charges loyal customers more than new ones. The Dynamic Pricing Engine takes the opposite position: every price is explained rule by rule, guardrails always win, and an experiment reports whether its result is actually conclusive.
Pricing logic is expressed as rules that stack in sequence — demand-based uplift, inventory pressure, competitor position, time-of-day, customer segment. Each one takes the price produced by the rule before it and states what it did and why.
The output for any item is a complete derivation: base price, each adjustment with its trigger and magnitude, any guardrail that bound the result, and the final figure. When a customer or a regulator asks why something cost what it cost, there is an answer that does not require reading source code.
A floor that a clever rule can argue its way past is not a floor. Guardrails here are applied after all rules have run and cannot be overridden by any of them — minimum margin, absolute price floor and ceiling, maximum change per cycle, and maximum deviation from a reference price.
The maximum-move-per-cycle limit is the one that prevents the failure people actually fear. Even if a data feed breaks and a rule demands a 70% cut, the price moves by at most your configured step, and the attempted move is logged as a guardrail breach for someone to look at. Bad inputs become an alert rather than a pricing incident.
Changing a price is a decision about revenue, not just margin. Raise by 10% and whether that is a gain depends entirely on how many units you lose — which is what price elasticity measures.
The simulator fits elasticity from your own historical price and volume data, then projects the revenue curve across a range of candidate prices and marks the optimum. It also shows the confidence interval around that curve, which is usually the more honest output: if your history contains only two distinct price points, the estimate is weak and the tool says so instead of drawing a smooth line through nothing.
Price tests are where teams most often fool themselves. A variant looks better after four days, the change ships, and revenue does not move. The engine refuses to call a winner until the result would survive scrutiny.
Stopping a test the moment it looks good is the most common way to ship a change that does nothing. Fixing the sample size in advance, and respecting it, is most of what separates a pricing programme from pricing theatre.
Competitor-aware pricing with a margin floor that cannot be breached, and a derivation for every price when a customer asks.
Perishable inventory where demand and time-to-event dominate. Rules stack naturally onto occupancy and days-remaining.
Category-level guardrails across sellers who each want something different, with per-seller rules bounded by platform-wide limits.
Segment rules producing consistent, defensible quotes, so two salespeople quoting the same account arrive at the same number.
Define pricing rules over demand, inventory depth, competitor position, time-to-expiry and customer segment. Simulate the revenue curve before anything goes live, run experiments, and keep a full audit of every price change and why it happened.
Dynamic Pricing Engine starts at $59 a month with a 14-day free trial. Prisync Professional is $99 per month per company.
No. Guardrails are applied after every rule and always win: a price floor, a ceiling, a minimum margin and a cap on how far one cycle may move the price. The audit shows which guardrail bit and why.
Simulate the revenue and profit curve across a price range first. The output states the elasticity assumption back to you and flags when the optimum sits at the edge of the range — meaning the real optimum is outside it.
On revenue per visitor, not conversion, because a price rise that cuts conversion can still win. Each test reports the p-value, the confidence and — if it is not yet conclusive — how much more traffic it needs.
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