An electronics retailer sets up price monitoring for 8 competitors and 15,000 SKUs, with updates every 4 hours
The system detects that a competitor has lowered the price of a TV from €749 to €699 at 2:00 p.m.
At 4:00 p.m., the algorithm suggests a price match to €699 to the category manager, who approves it
The price is updated on the website at 5:00 p.m., three hours after the competitor’s price change
Without this monitoring, the delay would have been several days.
Online price monitoring combines four components: 1) crawling competitor websites (including handling CAPTCHAs, IP bans, and changes to HTML structure), 2) product matching (EAN, textual similarity, images), 3) data consolidation and cleansing, 4) distribution to pricing tools
Vendor solutions integrate these building blocks with SLAs for data freshness and coverage, and manage the scalability of the monitored sites.
This monitoring service is based on a reliable product-matching system, which is essential for comparing products that are truly equivalent.

Agentic pricing transforms AI for price elasticity from a simple assistant into an autonomous teammate capable of executing complex strategies. This shift toward automation enables real-time profitability management in the face of market volatility.
88% of current Excel spreadsheets contain errors, a financial risk that is eliminated by this new technological era.

The retail agent-based pricing system replaces rigid automation with an AI-powered, autonomous pricing engine capable of reasoning and executing complex strategies. This technology transforms teams into strategic decision-makers who can optimize profitability in real time.
By adjusting prices up to 100 times a day, it can generate margin growth ranging from 15% to 25%.

Effective pricing management requires the rigorous integration of internal/endogenous data (costs, historical data) and external/exogenous data (competition, demand). This essential integration helps secure margins and provides an objective basis for decision-making in the face of market fluctuations. By structuring these signals, the organization transforms raw data into a lever for operational profitability, which can be effectively implemented in less than sixty days.