Pricing and promotions
See the price movement behind the market.
Crawlr combines recurring price collection with dependable product identity so pricing teams can compare like for like, retain promotion mechanics, and focus on the market changes that require action.
Comparable market context
A price observation keeps the context that makes it meaningful.
Product identity, price type, promotion mechanic, seller, currency, availability, and collection time stay connected instead of collapsing into one misleading number.
- Product identity
- MATCHED
- Price type
- SEPARATED
- Change event
- TIMESTAMPED
How pricing works
From recurring observations to actionable market changes.
- 01
Define the comparison
Agree the matched products, competitors, markets, currencies, price types, and promotion fields.
- 02
Collect with context
Retain list, selling, member, and promotional prices with seller and availability evidence.
- 03
Surface change
Deliver histories, promotion events, and exception alerts around the decisions your team owns.
Operating detail
What goes into the workflow—and what comes out.
Capabilities
- List, selling, member, and promotional price capture
- Promotion text and mechanic normalization
- Matched-product price histories and change events
- Rule-based alerts and export-ready summaries
Inputs
- Matched catalog
- Competitor set
- Markets and currencies
- Alert conditions
Outputs
- Price observations
- Promotion events
- Price histories
- Exception alerts
Use cases
- Competitive pricing
- Promotion analysis
- MAP monitoring
- Market-entry research
Delivery modes
- API
- Scheduled price feeds
- Alerts and reports
- Private client web app
Pricing and promotions FAQ
Answers about price types, matching, and alerts.
Connected commerce intelligence
Continue through the Crawlr data layer.
Product matching
Connect retailer listings to the same underlying product with normalized attributes, explainable evidence, and reviewable confidence.
Assortment and availability
Measure assortment breadth, catalog overlap, new listings, delistings, stock signals, and regional availability over time.
Multi-source data collection
Collect dependable structured data from websites, mobile apps, APIs, authenticated platforms, files, and other digital sources.