Pricemaster continuously tests pricing opportunities across your catalogue to discover where you can increase margin without sacrificing sales volume.
Instead of racing competitors to the bottom, AI Margin Miner systematically discovers higher-profit price points using live market behaviour, competitor reactions and real customer demand.
Repricers only react downward. They auto-match the cheapest seller and drag the entire market to the floor — destroying margin one micro-adjustment at a time.
Competitor drops 50p → everyone follows → margin evaporates. Repeat daily.
Identify SKUs where customers will pay more. Validate with real demand. Lock in.
AI Margin Miner identifies opportunities to raise prices gradually and safely — then watches the rest of the market move to match. Every confirmed move becomes a permanent margin gain.
A small, controlled increase on a candidate SKU. Capped by your rule ceiling.
Conversion rate, units, revenue and competitor moves are watched live.
If volume holds and competitors follow, the new price becomes the baseline.
The same five-stage loop runs in parallel across your entire catalogue, 24/7. Every SKU is a candidate. Every test is a controlled experiment. Every win compounds.
Choose a product yourself, or let AI Margin Miner identify the best candidates automatically — high-margin, stable-demand SKUs with room above current price.
Pricemaster nudges price upward for 3–7 days, bounded by your rule ceiling and a hard minimum-margin floor. Conservative, repeatable, reversible.
Live tracking on competitor moves, conversion, units, revenue and margin impact. Every signal is logged and fed back into the model.
If sales hold and competitors follow upward, the new price becomes the baseline. If not, an automatic rollback within minutes — the test is logged as learning.
The cycle continues across thousands of SKUs in parallel. Small wins compound into meaningful, ongoing profit growth.
AI Margin Miner transforms pricing from reactive firefighting into a repeatable commercial growth strategy — with clear scoreboards, weekly progress and unlockable margin tiers.
"We're not trying to be the cheapest. We're trying to find the highest profitable price the market will accept."
A live story from a UK reseller running AI Margin Miner across a power-tools catalogue.
Trade Counter Direct enrolled a single SKU — a popular Bosch SDS hammer drill — in AI Margin Miner. Pricemaster nudged price up +3.2%, then again, then again. Each step was held for 5 days while the platform watched competitor activity and conversion.
Within three weeks, three of four major competitors had matched the new price level. Order volume came in within the margin of error. Profit per sale lifted from £59 to £95. The result was rolled out across 1,800 sibling SKUs in the same category.
AI Margin Miner is built for large catalogues — exactly where small percentage gains create the largest absolute profit growth.
Most eCommerce businesses fixate on traffic and sales volume. Pricemaster focuses on extracting more profit from the traffic and demand you already have.
You don't need a bigger marketing budget to grow profit. The traffic you already have can yield more.
Margin gains come from price intelligence — not from working harder for more clicks.
Every locked baseline raises the profit floor on every future sale of that SKU.
Tests, rollbacks and competitor reactions in one place. Pricing as an operating system.
Stop reflexively matching every cheap competitor. Hold position when the data backs you.
Every test produces evidence — what your customers will pay, what your market will tolerate.
Every component of the AI Margin Miner platform is designed for catalogues at scale, with the guardrails commercial teams need to trust automation with revenue.
Automated upward price tests with statistical confidence checks.
Detect when rivals match your move — and how fast — at SKU level.
Auto-revert if conversion, units or margin drift outside bounds.
Surface the next best candidate SKUs to test, ranked by expected upside.
Run alongside your existing pricing rules and ceilings — no rip-and-replace.
Each successful test becomes the permanent new floor on that SKU.
131M+ data points / month. Hourly polling across the major UK marketplaces.
Every experiment is logged. Replay, audit, and compare campaigns over time.
Run thousands of parallel experiments without manual orchestration.
Native Shopify, Magento, WooCommerce, BigCommerce, OpenCart, Wix.
+ OpenCart, Wix, REST API
A short guide for pricing managers, eCommerce directors and merchandising teams evaluating margin optimisation software.
AI pricing optimisation goes beyond rule-based repricing by using machine learning to identify, test and lock in higher-margin price points across a large catalogue. The objective is not to find the lowest price the seller can survive — it's to find the highest price the market will accept while order volume holds. That distinction is what separates profit-led pricing software from defensive repricing software.
Traditional repricing software is designed to react downward. When a competitor undercuts, the platform follows them. This protects sales velocity, but only by sacrificing margin — and because every other competitor in the market runs identical software, the result is a coordinated, recursive race to the bottom. AI Margin Miner is built around the opposite assumption: that there are price points above current market where demand is still elastic in your favour, and that the only way to find them is to test.
Doubling traffic typically doubles costs — paid acquisition, fulfilment, customer service, returns. Doubling margin per order drops nearly all of it to the bottom line. For mature eCommerce businesses with stable demand, profit optimisation outperforms top-line growth by every meaningful unit-economic measure. Pricing intelligence software is the highest-leverage lever in that toolkit.
Automated profit optimisation works by running many small experiments in parallel. AI Margin Miner identifies SKUs with the largest expected margin upside (stable demand, healthy spread between current price and rule ceiling, low recent competitor volatility), runs bounded upward tests over 3–7 days, and observes conversion rate, units sold, revenue, margin and competitor reactions. Successful tests lock in a new baseline. Unsuccessful ones roll back within minutes and feed the learning loop.
When a credible seller raises a price, a meaningful share of competitors follow within days — especially in concentrated categories. Margin management software that detects this follow behaviour at SKU level can use it to validate higher baselines with confidence. AI repricing software that only watches competitors and never moves first never benefits from this dynamic; it can only ever react to it as a loser.
Demand curves move. Cost structures shift. Customer expectations re-anchor. A pricing automation software platform that runs continuous, controlled experiments is the only way to keep your prices calibrated to the current market — not the one your last manual review captured. Pricing automation for Shopify, Magento and other large-catalogue platforms is no longer optional for businesses that take margin seriously.
The point of any pricing tool — repricer, dynamic pricing engine, or AI pricing strategy platform — is profit. Volume and revenue are intermediate metrics. AI Margin Miner is engineered around profit per order, profit per SKU and total catalogue profit growth, with all four feedback loops (conversion, competitor follow, sales volume, margin retention) wired directly into the price-setting decision. That's how an intelligent eCommerce pricing platform should work.
Schema-ready answers to the most common questions from eCommerce directors, pricing managers and merchandising leads.
AI pricing optimisation uses machine learning and live market signals to systematically test, monitor and adjust prices across an eCommerce catalogue. The goal is to discover the highest price the market will accept while maintaining sales volume — rather than mechanically matching the cheapest competitor.
AI Margin Miner selects candidate SKUs, raises their price slightly for 3–7 days, then monitors competitor reactions, conversion rate and revenue. If sales stay stable and competitors follow upward, the higher price becomes the new baseline. The process repeats continuously across the catalogue.
Yes, but always within rules and margin guardrails you define. Every test is bounded by a maximum increase, a minimum-margin floor and an automatic rollback if performance degrades.
AI Margin Miner watches conversion rate, units sold and revenue in real time. If any metric falls outside of acceptable thresholds the price is reverted automatically to the previous baseline within minutes.
Yes — this is one of the platform's core insights. Across thousands of recorded experiments, when a market leader nudges price upward, a meaningful share of competitors will follow within days. AI Margin Miner detects this follow behaviour and uses it to lock in higher baselines.
Yes. Pricemaster integrates natively with Shopify, Magento, WooCommerce, BigCommerce, OpenCart and Wix. Price changes flow back to your store automatically through the integration.
Yes — the platform is designed for large catalogues. It runs many parallel experiments simultaneously, prioritising SKUs with the highest expected profit upside and compounding small percentage gains across the entire catalogue.
Repricing software only reacts downward — when a competitor drops, you drop. AI Margin Miner reacts upward. It looks for opportunities to raise prices, validates them with real customer and competitor behaviour, and locks in gains. Repricing protects volume; Margin Miner grows profit.
Every rule includes a configurable minimum-margin floor. The platform will never price below your guardrail, regardless of competitor activity.
Yes. Rollback protection is built in. If a test underperforms on conversion, revenue or margin, the price reverts within minutes — and the result is recorded so the system learns what works on which SKU classes.
Start systematically discovering more profit across your catalogue — one controlled experiment at a time, compounding every week.