How AI Decisioning Helps Retail Marketers Maximize ROI on Promotions

There are few pills harder to swallow in the marketing world than “do more with less.” But it’s a reality retail marketers have experienced first-hand since 2020. Gartner has defined the 2020s as the “era of less,” with budgets declining by an average 9.1 percent in 2023 and another 7.7 percent in 2024. Yet marketers have still navigated choppy waters throughout the decade with scrappy determination and data-driven strategies.

This year is no different, with 2025 already stirring up tariff woes, supply chain concerns, and tightening purse strings. To help right the ship and focus on revenue, many retail marketers will once again rely on personalization and promotional strategies to drive sales. 

Marketers will need to ensure that every dollar spent and every discount given is optimized to generate more sales while staying within their tight budget. But traditional promotional strategies may not do both, and many retailers end up either blowing their budget or struggling to personalize discounts to each individual customer. Both are problems for return on investment (ROI).

OfferFit’s Optimizing Promotional Spend lays out the problem with traditional discounting before making a case for a 1:1 promotional strategy using AI decisioning to find the lowest discount necessary for every customer while staying within a tight budget.

Here’s how retailers could leverage AI decisioning to transform their discounting campaigns into ROI-focused revenue engines.

The limits of the outdated discounting strategies

There is no question about whether consumers consider discounts when shopping. Promotions were a “major factor for 74 percent of U.S. online shoppers in 2023,” according to Capital One. More than 60 percent of Americans said discounts were more important than ever and 89 percent identify price as the main influence in purchasing decisions. 

But retail marketers have always faced the same dilemma when thinking through promotional strategies. If marketers offer a discount to a customer who would have converted without one, they can quickly blow their budget while training customers to wait for steep discounts. 

Even with personalization tools, marketers can still struggle to stay within their budget. Marketers can’t spend as much as an algorithm wants them to, especially if it can’t quickly adjust when budgets get tighter. The question then becomes, how do marketers offer the discounts to as many people as possible within a set budget?

The Constrained Optimization Problem

With or without the help of AI, marketers must balance individual needs with global constraints–what data scientists call a constrained optimization problem.

If a shoe company offers $20 discounts to every customer knowing many will buy new shoes and even buy more with that footwear, they still have to grapple with a limited daily budget. If that budget is $10k a day, it’s impossible to offer enough $20 discounts for every customer. There’s also the question of whether some customers could have spent the same amount with a $10 or even $5 discount.

Traditional promotional strategies struggle to solve all these challenges. Even though bigger discounts bring in more revenue on average, some customers won’t buy even with the maximum discount, while others are open to spending even more when they see “$20 off!”

AI decisioning can help marketers find the optimal offer for each customer or the lowest discount needed to convert that maximizes incremental revenue after subtracting promotional spend. But that only solves one aspect of the constrained optimization problem. If retail marketers have a fixed promotional budget, they will need AI Decisioning Agents that find the right tradeoffs between the optimal discount for each individual and the best fit for the overall budget. 

Reframing promotional spend with ROI

With budgets tight, it's tempting to default to giving everyone the same discount or to drive down the average discount as a blunt cost-saving tactic. Neither strategy increases the bottom line. 

Effective promotional strategies instead focus on maximizing ROI or the incremental dollar of revenue earned for each dollar of promotion spent. Focusing on ROI allows marketers to make choices that respond to individual customer preferences. AI Decisioning Agents can select the right discount for each customer, especially when marketers offer a wide variety of discount options to choose from.

ROI is a more effective means of measuring and understanding promotional strategy. The key advantage of the ROI framing is that it allows us to consider all customers on equal footing and make decisions that drive the overall best outcome. 

Embracing strategic discounting

Now is the time to maximize every marketing dollar spent, which makes strategic discounting tantamount to success for many marketers. As marketers consider incremental revenue and the holistic ROI of promotional strategies, the right AI Decisioning Agent can help solve the constrained optimization problem facing so many retail organizations.

To do so, marketers will need to work closely with their AI decisioning success teams to realize a data-driven approach to finding the optimal discount for every customer to convert while still respecting budget limitations.

Want to see how constrained optimization actually works in practice? Download the full white paper Optimizing Promotional Spend today.