Automate price monitoring and track the market
Get competitor prices, changes, and trends, no URLs needed, just accurate data that fuels your pricing strategy

What is price monitoring and how does it work?
Price monitoring detects, collects, and tracks competitor prices automatically, without needing static URLs or manual input. It finds relevant products across the market, monitors changes, and delivers structured data ready for reports, negotiations, or repricing tools.
Price Monitoring Results
Daily competitor price points captured across regions
Average margin gain after data-driven repricing rules
Typical detection-to-reaction window for major price moves
Why price monitoring powers better catalog performance
Staying price-competitive means knowing your market in real time. This solution delivers continuous, accurate price tracking across regions and competitors, giving teams the insights needed to act fast and protect margins.
Real-time market visibility
Continuous crawls surface every competitor price the moment it changes
Margin-safe repricing
Rule engine adjusts offers only within pre-set profit bounds
Region-aware insights
Localised tracking reveals country-specific price gaps and taxes
Negotiation leverage
Hard data strengthens talks with suppliers and brands
Instant alerting & feeds
API and email pushes notify teams before margins erode
Scales effortlessly
Millions of SKUs monitored without extra infrastructure or staff
Ready to stop guessing and start tracking real prices?
Request a free price sample across key products and competitors in your region
Ecommerce automations by use cases
Price monitoring detects, collects, and tracks competitor prices automatically, without needing static URLs or manual input. It finds relevant products across the market, monitors changes, and delivers structured data ready for reports, negotiations, or repricing tools.
Taxonomy Audit
Product Attributes Enrichment
Product Content Creation
Product Photos Creation
Product Categorization
Catalog Intelligence
Multi-Geo
Multi-Brand
Product Categorization
How does the platform discover new competitors if I don’t supply URLs or seller lists?
Behind the scenes, the crawler begins with the identifiers in your catalog, GTIN, MPN, brand, and title keywords, and launches a multi-stage discovery loop. First it sweeps the top 500 e-commerce domains in your target region, harvesting candidate listings that match at least two identifiers. Next, a similarity model checks imagery, attribute patterns, and price bands to filter out look-alikes, grey-market bundles, or refurbished stock. The final shortlist is written to a “competitive graph” that refreshes nightly; if a new merchant lists the item tomorrow, the graph expands automatically, so you never have to maintain static seller files.
How often are prices refreshed, and can we accelerate the cadence for key SKUs?
Every product on your watch list receives a base-frequency crawl, hourly, every four hours, or daily, depending on traffic volume and marketplace latency rules. You can tag “priority” SKUs (e.g., high‐margin or loss-leader items) for turbo sampling; these receive a delta check as often as every ten minutes during business hours or promotional events. Cadence is just a slider in your dashboard, so adjusting from daily to hourly monitoring is a two-click change and takes effect on the next crawl cycle.
What integration options exist for moving the data into our pricing engine or data warehouse?
Data lands wherever you like: REST and GraphQL endpoints for real-time pulls, webhooks for push-style streams, SFTP and S3 drops for batch files, and native connectors for Snowflake, BigQuery, and Redshift. Each record arrives in a normalised schema, SKU, competitor ID, region code, currency, list price, promo price, timestamp, so you can pipe it straight into a repricer or BI dashboard without transformation scripts. For Tableau or Power BI users, a pre-built extract refreshes visualisations on the schedule you set.
How do you differentiate between flash sales, coupon discounts, and permanent price drops?
The crawler captures three layers of pricing data: the visible list price, any inline promo banners, and coupon metadata gleaned from page markup or browser-side API calls. Machine-learning classifiers label each price as “Base,” “Promotion,” or “Voucher-conditional.” When a discount is timer-based or requires a code at checkout, the system flags it separately so your repricer can decide whether to match, ignore, or only adjust during the same promo window. Historical price trails preserve every fluctuation, letting analysts spot trends versus one-day anomalies.
Can the system track stock levels and shipping costs alongside price to give a true landed-cost view?
Yes. During each page fetch we also record in-stock flags, quantity limits, and shipping selectors. For marketplaces that expose seller delivery fees through an API, those charges are appended to the price record, producing a “landed cost” column. This means your margin calculations can compare not just headline price but the total a shopper pays at checkout, revealing under-the-radar tactics like low price + high shipping that erode competitiveness.
How does it enforce MAP policies and alert us to violations?
For SKUs covered by Minimum Advertised Price agreements, you load the policy file (SKU → MAP threshold) once. The monitoring engine then triggers an instant alert, email, Slack, Teams, or webhook, whenever it detects a public price below the allowed floor. Each alert includes screenshot evidence, the violating seller’s ID, the exact price delta, and a 30-day violation history so account managers can escalate with iron-clad documentation. A weekly compliance digest summarises total infractions by brand and marketplace, simplifying executive reporting and supplier score-carding.
Price monitoring
Pricing is based on the volume and complexity of your operations. Get a personalized quote tailored to your product catalog size, automation needs, and platform requirements