I have a bold prediction: dynamic pricing will take over the retail landscape in 2025—both in-store and online, albeit in different ways.

Online Shopping

For online shopping, I foresee this manifesting as dynamic discounting. Whether driven by AI or traditional IF statements, I believe we’ll see customers paying different prices for the same product in ways that feel beneficial to them. Online stores will likely deploy dynamic pricing programs capable of real-time cart, shopper, and session analysis to calculate instant discounts. These discounts could be presented to shoppers via AI chatbots communicating in natural language, pop-ups offering buying cues, or follow-up emails.

‍While this end goal is advanced, we’ll likely see a "lite" version of this technology first. Early implementations might involve pricing engines that analyze store performance, slow days or seasons, popular products, pricing trends, and more. A major part of this will revolve around smarter product recommendations combined with discounting, driven by AI that's more accurate and effective than ever before.

AI Shopping Assistants

On that topic, I predict the growing prevalence of AI Shopping Assistants across various platforms—at the store level, within browsers, and integrated into AI phone assistants like Google Assistant and Siri. This trend is already emerging, with examples like Amazon’s Rufus and AI chatbots on countless websites. It’s only a matter of time before these systems not only recommend products but also deliver personalized discounts.

In-Store Shopping

Conversely, the brick-and-mortar space may lean toward surge pricing—essentially the opposite of dynamic discounting. This will likely be most noticeable in grocery stores and fast food restaurants. While dynamic discounting could enhance the customer experience, surge pricing may take a more negative turn. With the rollout of digital price tags in grocery aisles (a trend already common in fast food), prices could rise during peak shopping periods—holidays, major events like the Super Bowl, or dinnertime—and drop during slower periods.

This system, powered by algorithms or AI, would analyze historical and real-time store data, along with external factors like seasonality, current events, and item popularity. The goal? To influence when people shop and what they buy—a retailer's dream.

Online vs. In-Store: Key Differences

It’s important to note why dynamic pricing will look so different online versus in-store. The operational goals and challenges of the two formats are fundamentally distinct.

For online retailers, the primary goals are to maximize:

• AOV (Average Order Value): How much a customer spends in one transaction.
• CVR (Conversion Rate): Ensuring shoppers complete their purchases.
• Repurchase Rate: Encouraging repeat customers.

Online sellers focus heavily on these metrics, deploying strategies like discounts, monthly promotions, loyalty programs, and clearances. In many ways, e-commerce is already dynamic in its pricing models.

Brick-and-mortar stores share some of these goals but also face additional considerations:

• Foot Traffic: The number of visitors entering the store.
• Revenue per Square Foot: Measuring how effectively physical space generates sales.
• Sales per Employee: Workforce efficiency and productivity.
• Local Market Share: Competing with nearby retailers.

These factors shape the tactics of physical stores in ways e-commerce businesses don’t have to consider.

That’s my bold prediction for 2025: dynamic pricing will redefine how we shop, both online and in-store, but in markedly different ways.