Price optimization software

Price optimization software that explains every recommendation.

Most price optimization software hands you a number and asks you to trust it. Retailgrid optimizes for gross margin return on inventory - not elasticity alone - scores every recommendation for confidence, and shows the reasoning behind each price. Built for mid-market retailers who outgrew Excel but don't want a black box.

retailgrid.io/optimize
SKU 48201Cost EUR 12.40DOS 41 daysOptimizerGMROI objectiveconf 0.91Regular+3.1% GMROIPromo+5.4% GMROIMarkdown+1.8% GMROIOne model, three recommendations - scored, explained, GMROI-optimized
The price optimization problem

Traditional RPO optimizes one number - and can't tell you why.

Classic retail price optimization models maximize a single elasticity-based objective and return a recommendation nobody can interrogate. They ignore the cash tied up in inventory, collapse regular pricing, promotions, and markdowns into one mode, and give no signal about how much to trust any given price. So the recommendations sit unused, and the team goes back to the spreadsheet.

1 goal
Most RPO tools optimize elasticity alone - ignoring inventory return
Black box
Typical share of price recommendations with a human-readable explanation
0 score
Confidence signal attached to each recommendation in legacy tools
What sets Retailgrid apart

Five things typical price optimization models don't do.

Retailgrid is built around the parts of price optimization that determine whether a recommendation actually gets used.

Fully explainable by AI

Every recommendation comes with the reasoning behind it - the signal, the rule, and the math. No black box. Your category manager can defend any price to a CFO, and the audit trail is there by default.

See agentic pricing

Optimizes GMROI, not just elasticity

Most RPO tools maximize an elasticity-based objective and ignore the cash sitting in stock. Retailgrid optimizes for gross margin return on inventory investment - the number business owners actually run on - balancing profit against inventory turnover.

See markdown & clearance

One model, three recommendations

Regular price, promotion, or markdown - one model decides which lever fits each SKU's state, instead of three disconnected tools. The same engine routes a healthy SKU to a regular reprice and an overstocked, end-of-life SKU to a phased markdown.

See dynamic pricing

Confidence score on every suggestion

Each recommendation is scored, so you know which prices to apply automatically and which to review. Low-confidence items fall back gracefully - item to cluster to category - rather than producing a price you can't trust.

Explore the workspace

Built-in benefits measurement

Retailgrid tracks realized outcomes against the forecast that drove each price, so you see the margin and revenue impact your pricing actually delivered - and the model retrains when reality drifts.

See the platform

Rules and guardrails on top

Margin floors, competitor corridors, KVI locks, MAP, and rounding rules sit over every recommendation. Optimization proposes; your business rules constrain. Nothing ships outside the boundaries you set.

See rules-based pricing
How it works

From raw sales data to validated, monitored prices.

A four-step guided flow that starts working on day one and gets more inventory-aware as you configure it - one category at a time.

01

Load & validate

Bring in product, sales, and competitor data. Retailgrid validates it and produces a data-quality score per SKU, so you know how much to trust each recommendation before you act on it.

02

Model demand & elasticity

Demand and price sensitivity are modeled at the right level of aggregation, with explicit confidence tiers and graceful fallback from item to cluster to category when data is thin.

03

Optimize for GMROI

The optimizer recommends a regular price, promotion, or markdown for each SKU - balancing margin against inventory return, inside the margin floors, competitor corridors, and KVI locks you set.

04

Monitor & learn

Realized outcomes are tracked against forecast. You see the impact each price delivered, and the model flags drift and retrains when the market moves.

Price optimization software FAQ

Common questions about retail price optimization.

What is retail price optimization software?
Retail price optimization software recommends the price for each product that best meets a business goal - margin, revenue, or inventory health - using demand and elasticity modeling instead of cost-plus rules alone. Retailgrid does this inside a familiar grid, scores every recommendation for confidence, and shows the reasoning behind each price so the team can trust and audit it.
How is Retailgrid different from traditional price optimization models?
Traditional retail price optimization (RPO) tools optimize a single elasticity-based objective and return a number you have to take on faith. Retailgrid optimizes for GMROI - gross margin return on inventory investment - not just elasticity, so recommendations account for how much cash is tied up in stock. Every suggestion is fully explainable, scored for confidence, and returned as one of three decision types: regular price, promotion, or markdown.
Does price optimization software replace my pricing team?
No. Retailgrid enriches the spreadsheet your category managers already work in rather than replacing them. It proposes prices, explains the math, and applies changes at the level of autonomy you set - full auto for low-risk SKUs, human-in-the-loop for sensitive categories. The team stays in control and keeps a full audit trail.
How long does it take to deploy?
Days, not months. Retailgrid is self-serve and works from day one in profit-only mode using your historical sales. Inventory-aware optimization activates per category as you set days-of-supply thresholds, so you can start on one category and scale to the full assortment at your own pace.
Do I need clean inventory data to start?
No. Retailgrid runs in a profit-only mode without inventory thresholds, then progressively unlocks deadline-driven markdowns and full inventory-aware optimization as more configuration is added. A data-quality score tells you how much to trust each recommendation, and low-confidence items fall back gracefully rather than producing a bad price.

See price optimization you can actually explain.

Book a 20-minute walkthrough on your own category data - we'll show you GMROI-based recommendations, confidence scores, and the reasoning behind every price.