The two patents are among almost 50 that Walmart has secured from the\u00a0U.S. Patent and Trademark Office<\/a>\u00a0since January, per the report. The company has stressed that the patents, one of which is specific to markdowns while the other enables human-led decisioning, are \u201cunrelated to dynamic pricing\u201d and that the retailer \u201cdoesn\u2019t participate in surge pricing.\u201d<\/p>\n What the two patents do reveal, however, is that, increasingly, retail success is being determined not just by merchandising or scale, but by the ability to optimize complex systems using data. Pricing, inventory, logistics and customer engagement are becoming interconnected components of a broader optimization problem.<\/p>\n Advertisement: Scroll to Continue<\/p>\n See also: Walmart Names New CEO as Retail Moves From Shelves to Software<\/a>\u00a0<\/p>\n Retail Moves to \u2018Algorithmic Merchandising\u2019<\/p>\n Traditional retail pricing has often relied on historical patterns and human judgment, supported by periodic adjustments. By contrast, Walmart\u2019s patented system appears designed to evaluate multiple variables simultaneously and optimize markdown timing and depth across different time horizons.<\/p>\n We\u2019d love to be your preferred source for news<\/a>.<\/p>\n Please add us to your preferred sources list so our news, data and interviews show up in your feed. Thanks!<\/p>\n Algorithmic merchandising, in contrast to dynamic pricing, operates largely behind the scenes. It focuses on improving the quality of discounts rather than their visibility, aligning pricing decisions with operational realities rather than short-term demand spikes.<\/p>\n Instead of over-discounting to guarantee sell-through, retailers can use artificial intelligence (AI) tooling to calibrate markdowns more precisely, applying them where and when they are most effective. The result is smarter prices that can help achieve the same sales outcomes with less margin erosion.<\/p>\n See also: Amazon, Walmart Shift Retail Competition From Price to Technology<\/a>\u00a0<\/p>\n Meeting Consumer Expectations Without Breaking Trust<\/p>\n Any discussion of AI-driven pricing must grapple with consumer perception. In recent years, the idea of algorithmically determined prices has drawn scrutiny, particularly when it resembles surge pricing or individualized offers that vary by user. Walmart\u2019s framing of its technology is notable in this regard. The emphasis is on improving markdown decisions rather than introducing real-time price fluctuations tied to external factors like time of day or customer identity.<\/p>\n Markdown efficiency determines how much margin is lost in clearing inventory, how quickly products move through the system and how effectively retailers respond to changing demand. AI has the potential to transform this area from an art into a science.<\/p>\n Still, the algorithmic merchandizing initiative dovetails nicely with Walmart\u2019s announcement earlier this month confirming a sweeping rollout of\u00a0digital shelf labels<\/a>\u00a0across its roughly 5,200 stores in the United States by 2027.<\/p>\n The PYMNTS Intelligence and\u00a0ACI Worldwide<\/a>\u00a0collaboration \u201cBig Retail\u2019s Innovation Mandate: Convenience and Personalization\u201d found that\u00a032% of grocers<\/a>\u00a0think consumers would be very or extremely likely to switch merchants if not given access to\u00a0digital price tags<\/a> or smart shelf tags.<\/p>\n![\"Preferred](\"https:\/\/www.pymnts.com\/wp-content\/uploads\/2026\/02\/Google-PYMNTS-blackbox.svg\")
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