A formula you define (e.g. “match the lowest of 3 competitors minus 2%”)
A model trained on your sales history, price elasticity and competitor prices
Marketplace sellers reacting to Buy Box or competitor moves in near real time
Retailers with enough sales history who want a recommended price, not just a rule
Minutes — a merchant configures the rule
Longer — the model needs historical sales data to train.
“Match Competitor X minus 5%, floor $19.99”
“Raise price to $24.99 — modeled +12% margin”.
Priceva turns tracked competitor and demand data into a price you can act on immediately, not a spreadsheet you have to interpret.
Priceva’s model learns how each SKU’s sales respond to price and recommends a price that balances margin and volume, not just the lowest number.
Competitor price and stock monitoring
The data foundation for both engines: prices, stock status and promotions checked daily or up to 8 times a day across every retailer you track.
Marketplace repricing
Automatic repricing for Amazon, Walmart, Google Shopping and other marketplaces, including Buy Box-aware rules on Amazon.
Retailers with a large catalog use dynamic pricing to keep thousands of SKUs competitively priced without a person touching each one. Priceva’s rule-based engine handles routine repricing, while price optimization finds margin on slower-moving SKUs a manual process would never revisit.
Brands that sell on their own site alongside retail partners use dynamic pricing to react to a retailer’s price change the same day, protecting margin without waiting for a weekly pricing review.
Sellers on Amazon, Walmart and Google Shopping run rule-based repricing to win the Buy Box or match a competitor within minutes of a price change, then layer in demand-based optimization once they have enough order history.
Add 20 products for free and see your first rule-based or demand-based price recommendation within a day. No credit card required.