Retailers do not have a pricing problem. They have a commercial decisioning problem.
For years, retailers have invested in pricing intelligence, competitive price scraping, elasticity models, margin optimization engines, markdown algorithms, and promotional planning tools. Many have moved beyond intuition and now use advanced analytics to determine where they can raise prices, where they need to match competitors, and where they should hold position.
But even in analytically mature organizations, a major gap remains: pricing and promotions are still too often managed as separate worlds.
Pricing teams are usually focused on protecting or expanding margin. Promotional teams are often focused on driving traffic, accelerating sales, clearing inventory, supporting lifecycle management, or creating customer excitement. Merchandising, marketing, finance, operations, and analytics may all contribute to these decisions, but they are not always working from one integrated commercial strategy.
The result is that retailers may optimize individual decisions while under-optimizing the total enterprise portfolio.
A price increase may improve item-level margin but weaken customer price perception. A promotion may drive sales but give away margin that was hard-earned elsewhere. A markdown may clear inventory but distort demand signals. A competitor response may protect share in one category while creating unintended margin pressure across the broader assortment.
The opportunity is to evolve from isolated price and promo optimization to portfolio-level price and promotional orchestration. More simply: retailers need to stop treating margin only as an outcome. They need to start treating margin as a resource.
The Traditional Retail Pricing Trade-Off
At its core, retail pricing is a balancing act. Retailers buy inventory at a cost and need to sell it profitably. That means pricing decisions are often designed to capture margin—but margin cannot be chased blindly.
If prices are too low, the retailer may drive volume while leaving margin on the table. If prices are too high, the retailer may improve short-term margin rate but lose units, traffic, or customer trust.
The classic elasticity problem is only part of the story. Yes, demand may fall as price rises, especially in categories where customers are price-sensitive or substitutes are easy to find. But the longer-term issue is customer perception.
Customers do not evaluate a retailer only through one transaction. They build a perception over time. If a retailer begins to feel expensive, inconsistent, or disconnected from value, the impact can extend beyond a single product. It can influence future trips, basket size, loyalty, and customer confidence.
Pricing is never just about the price of an item. It is about the relationship between margin, demand, customer perception, competitive position, and long-term enterprise value.
Promotions Follow a Different Logic
Promotional planning introduces a different set of objectives. Retailers run promotions to drive traffic, accelerate demand, create awareness, support lifecycle management, clear inventory, defend share, or close a sales gap. In some cases, a promotion is less about the promoted item itself and more about the trip it creates.
That is the logic of halo.
Some products are highly elastic and highly visible. They may act as trip drivers, bringing customers into stores or onto digital channels. The retailer may accept lower margin on those items because the broader basket, customer engagement, or long-term relationship creates value elsewhere.
In other words, pricing often starts with margin. Promotions often start with sales, traffic, or inventory movement. Both are valid—but when they are managed separately, they can work against each other.
The Silo Problem
In many retailers, pricing and promotional planning are not only analytically separate. They are organizationally separate.
One team may be optimizing everyday price. Another may be planning weekly or seasonal promotions. Another may be managing markdowns. Another may be responding to competitors. Finance may be tracking margin rate. Merchandising may be focused on category growth. Marketing may be focused on traffic and engagement.
Each function may be making rational decisions inside its own mandate. But disconnected rational decisions can create irrational outcomes at the enterprise level.
A promotion may be planned on an item where pricing has already been sharpened. A price increase may be taken in a category that marketing is trying to position as value-oriented. A traffic-driving promotion may be evaluated only on item profitability, without properly accounting for basket halo. A category may be pushed to recover margin without understanding whether customers are actually price-sensitive.
The customer does not experience these decisions as separate internal processes. The customer experiences one retailer, one value proposition, one price image, and one shopping journey.
That is why pricing and promotions need to be managed as one connected commercial system.
Margin as a Portfolio Resource
The better executive question is not:
How do we maximize margin on this item?
It is:
Where should we earn margin, where should we invest margin, and how do those choices improve total enterprise value?
In financial services, portfolio management is built on the idea that not every asset plays the same role. Some assets provide stability. Some create higher expected return. Some carry more risk. Others protect the downside. The goal is not to maximize each position independently. The goal is to construct the portfolio to deliver the best overall outcome.
Retailers can apply a similar logic to pricing and promotions. Not every item in the assortment should play the same role.
Some items can carry more margin because demand is relatively inelastic, the product is differentiated, competitive reference points are weaker, or the customer need is less price-sensitive. These items create margin capacity.
Other items should be priced or promoted more aggressively because they are highly elastic, highly visible, strategically important, or central to price perception. These areas consume margin capacity, but they may create value through trips, conversion, basket expansion, customer acquisition, or loyalty.
The opportunity is to identify where margin can be harvested without materially damaging demand, and where margin should be deliberately reinvested to drive broader business outcomes. That is portfolio-level price and promo optimization.
From Optimization to Orchestration
Traditional price optimization asks:
What is the optimal price for this item?
Traditional promotional optimization asks:
What discount will maximize sales, units, or gross profit for this event?
Those are useful questions, but they are incomplete. A portfolio-level approach asks more strategic questions:
- Where can we take margin without damaging demand or customer trust?
- Which items should be protected because they shape price perception?
- Which products are true trip drivers, and what is the full basket impact when we promote them?
- Which categories should defend share, and which should expand margin?
- Where should promotional funding come from?
- How do everyday pricing, promotions, markdowns, loyalty offers, and competitive response work together to deliver the financial plan?
This is the shift from isolated optimization to enterprise orchestration. The objective is not to make every item equally profitable. The objective is to make the total retail portfolio more productive.
The AI and Analytics Foundation
The ability to manage pricing and promotions this way depends on a strong analytical and AI foundation.
Retailers need advanced forecasting capabilities that can capture demand at the item, customer, store, region, and channel level. They need elasticity models that reflect not only product attributes, but also customer attributes, competitive context, seasonality, inventory position, promotional history, and broader market conditions.
They also need optimization engines that can evaluate multiple commercial stimuli at the same time. Price is only one lever. Promotions, markdowns, loyalty offers, personalized incentives, media exposure, assortment changes, and service levels can all influence demand. In many organizations, these levers are still modeled and planned separately, even though the customer experiences them together.
The next generation of retail decisioning will require models that can simulate these interactions and help leaders understand trade-offs before decisions are made. That includes the ability to run macro scenarios through the commercial planning process:
- What happens if traffic softens?
- What happens if a competitor becomes more aggressive?
- What if inflation changes customer price sensitivity?
- What if inventory arrives late?
- What if the business needs to close a sales gap without destroying margin?
- What if loyalty offers can achieve the same demand response as a broad-based promotion, but with better economics?
This is where AI becomes strategically important—not as a black-box pricing engine, but as a decision intelligence layer that helps retailers forecast demand, simulate scenarios, allocate margin, and orchestrate commercial actions across the enterprise.
Closing Thought
Retailers are operating in an environment where customers are value-conscious, competitors are transparent, and margin pressure is constant. In that environment, pricing and promotions cannot be managed as disconnected levers.
The retailers that win will be those that understand how to balance margin capture with demand creation, short-term profit with long-term trust, and item-level decisions with portfolio-level strategy.
In a subsequent post, I will cover the analytical and AI capabilities required to power this kind of portfolio-level approach, including advanced forecasting, item- and customer-level elasticity, simultaneous optimization across pricing and promotional stimuli, loyalty offer optimization, and macro scenario planning.
For now, the strategic point is simple:
Retailers should stop treating price and promotion as separate levers. They should manage them as an integrated portfolio—because in modern retail, margin is not just a metric to report. Margin is a resource to allocate.
If you are a retail, analytics, data, merchandising, loyalty, or commercial strategy leader thinking about how AI should improve enterprise decision-making, I would welcome the conversation. Connect with me on LinkedIn or follow The Decisioning Layer for future posts on AI, advanced analytics, and commercial decisioning.
Views are my own and do not represent my employer.