# Trendyol Repricer Software: Rule-Based Bots vs. Simulation-Based Dynamic Pricing

Rule-based repricers react to competitor price moves. Simulation-based dynamic pricing tests the outcome first. Here is how to choose.

## Short answer

Not every Trendyol repricer works the same way. A rule-based repricer reacts to a competitor's price with a preset action. Simulation-based dynamic pricing compares the likely outcome of each candidate price under your demand, cost, stock and competitor conditions before anything changes. XPrice is a dynamic pricing platform built on the second approach.

- Category: Dynamic Pricing
- Published: 2026-02-05
- Last updated: 2026-10-20
- Canonical: https://xprice.ai/en/resources/rule-based-repricer-vs-simulation-engine

## What is a Trendyol repricer, and how does automated pricing work?

A repricer is software that updates your selling price from defined rules or calculated recommendations. Two very different things hide under that name. One **changes your price automatically**. The other **simulates the outcome before the price changes**. They are not the same job.

## Why can a rule-based repricer start a price war?

Say a competitor drops a product from $200 to $199. A "stay $1 below the competitor" rule pulls your price to $198. If the competitor runs the same logic, both prices keep sliding. The rule is not harmful by itself. Without a price floor and without commission and unit cost checks, though, it can erase your contribution profit fast.

## ERP rules vs. repricer bots vs. XPrice

| Criterion | ERP / fixed price rule | Competitor-driven repricer | Simulation / XPrice |
| --- | --- | --- | --- |
| Starting signal | Cost, exchange rate or price list | Competitor price | Price, sales history, demand, stock and market signals |
| Decision logic | Fixed rate or formula | If-then rule | Side-by-side comparison of price scenarios |
| Sales volume impact | Usually not modeled | Not in every tool | Estimated with a price elasticity assumption |
| Profit limit | Depends on the rule you set | Depends on the floor you set | Checked in every scenario once cost and commission data exist |
| Human control | Rule-dependent | Rule-dependent | Reasoned recommendation plus approval flow |

## What does a Monte Carlo simulation add?

XPrice combines demand models with a Monte Carlo simulation. By default it runs 10,000 iterations and weighs demand uncertainty against your real sales data, commission tiers and unit cost.

Take the question "If I raise the price 6%, how will orders change?" Answering it means looking at the price increase, the unit contribution and the expected demand together. If the elasticity estimate is weak, treat the result as a scenario, not a promise.

## Which approach fits which store?

- **Fixed cost rule:** simple catalog updates.
- **Rule-based repricer:** products with clear limits that need a fast competitive response.
- **Simulation-based dynamic pricing:** sellers who want revenue, contribution profit and stock impact in one view before they decide.

Next, see [how a 5% price cut changes the sales volume you need](https://xprice.ai/en/resources/price-cut-vs-sales-volume). For the Trendyol connection, visit the [integrations section](https://xprice.ai/en/product#integrations).

## FAQ: Does using a repricer always cost you money?

No. Losses come from uncontrolled price cuts and incomplete cost data. A repricer with a correct price floor and operational checks can work well.