While rule-based repricer makes a price change based on the instructions you gave it (if A happens, then respond with B), AI automatically factors in a wide range of competitors’ metrics that will impact the Buy Box win rate, including ASIN, fulfillment, the list price, seller metrics, and more, to make the price adjustment more precisely and flexibly.

• It uses a customized model: For each competitor, we calculate a unique competitive relationship model that takes into account the product status, ASIN, fulfillment, competitors’ prices, and many other relationships in the competitive relationship. This way, using the AI Repricer, it will be easier and more detailed to get price relationships with all competitors in the price adjustment process and it will be possible to make price adjustments more accurately.
• The shelf model has memory: the price adjustment behavior can be modified with each price changed report (SQS) feedback, so the adjustment behavior can be more flexible and we can approach the buy box price more efficiently.
• It strives for the maximum benefit for the customer: After getting the buy box the price adjustment model will automatically detect whether the current price adjustment result has a chance to raise the price. With this function, we can avoid missing the opportunity to raise the price or to help customers improve their price settings.
  
  
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