{"id":28265,"date":"2026-03-10T10:55:00","date_gmt":"2026-03-10T05:25:00","guid":{"rendered":"https:\/\/blog.aspiresys.com\/?p=28265"},"modified":"2026-03-10T11:45:16","modified_gmt":"2026-03-10T06:15:16","slug":"unlock-revenue-potential-with-oracles-price-optimization-solution-maximizing-profits-and-customer-satisfaction-through-ai-driven-pricing-strategies","status":"publish","type":"post","link":"https:\/\/www.aspiresys.com\/blog\/retail\/oracle-retail-solutions\/unlock-revenue-potential-with-oracles-price-optimization-solution-maximizing-profits-and-customer-satisfaction-through-ai-driven-pricing-strategies\/","title":{"rendered":"Unlock Revenue Potential with Oracle’s Price Optimization Solution: Maximizing Profits and Customer Satisfaction Through AI-Driven Pricing Strategies"},"content":{"rendered":"\n

Have you ever wondered what determines the price of a product? Is it the cost of manufacturing, the desired profit, or the product\u2019s perceived value? Retailers understand that finding the perfect balance between value and cost is crucial in attracting customers and out-competing other products. With the advancement of AI and machine learning, businesses now have access to powerful tools for data analysis<\/a> and technology that can aid in this process.  <\/p>\n\n\n\n

Amazon is an excellent example of a company that changes the prices of its product’s multiple times a day. This is made possible by price optimization technology, which can predict market trends and provide businesses with valuable insights. By using this technology, businesses can attract more customers, increase their revenue, and gain a larger market share.  <\/p>\n\n\n\n

Oracle has been at the forefront of helping retailers tap into the market. Oracle Retail Promotion and Markdown Optimization version 23 offer the capability to optimize promotions and markdowns, aiming to increase in-season sell-through and potentially boost revenue and gross margin. Oracle Retail Offer Optimization enables retailers to forecast the demand of different customer segments and identify the customer segment with the highest likelihood of redeeming marketing offers. <\/p>\n\n\n\n

As retailers move away from blanket promotions and towards more targeted pricing strategies, personalization becomes a critical consideration.<\/p>\n\n\n\n

This raises a key question: how can retailers personalize offers to different customer segments using\u00a0AI?<\/strong>\u00a0<\/h2>\n\n\n\n

Retailers use AI to group customers into meaningful segments using signals\u00a0such as\u00a0purchase\u00a0history, price sensitivity, channel preference, and response to past offers. Oracle Retail Offer Optimization supports this by forecasting demand at the segment level and\u00a0identifying\u00a0which segments are most likely to redeem specific offers. This helps retailers tailor offers by segment (and even by location) without relying on broad, one-size-fits-all promotions.\u00a0
\u00a0
Before we unravel the\u00a0new technology,\u00a0let\u2019s\u00a0dive into the problem that most retailers face.<\/p>\n\n\n\n

Puzzle of Pricing Strategy <\/strong> <\/h2>\n\n\n\n

A survey data from Pew shows that 22% of Americans shopped online in 2000; today, it is nearly 80%. The convenience of buying for customers has meant new operational challenges for retailers.  <\/p>\n\n\n\n

Here are some of the pain points they face:  <\/p>\n\n\n\n