Retail conversations in 2025 are dominated by one buzzword: AI. From predictive models to generative pricing, retailers are rushing to inject artificial intelligence into every function - including promotions.

But here’s the reality for most mid - sized and even large retailers: you don’t need advanced AI to improve promotions. In fact, chasing AI without fixing the fundamentals often leads to wasted spend, campaign fatigue, and misfiring discounts.

This blog is about getting back to basics. Before you think AI - first, let’s talk about practical, actionable steps that can dramatically improve your promotional outcomes today - using the tools and data you already have.

Why Promotions Still Underperform in 2025

Even in the era of real - time analytics and machine learning, many retailers struggle with:

• Over - discounting the wrong SKUs

• Running the same offers across regions or stores

• Poor promotion - to - sales attribution

• One - size - fits - all tactics that alienate core segments

• Inconsistent coordination between store ops, digital, and marketing teams

These issues aren’t solved by algorithms alone. They require better inputs, sharper execution, and more disciplined measurement.

1. Run SKU - Level Postmortems, Not Just Campaign Reviews

Most retailers look at promotions in terms of gross revenue or footfall impact. But a true view of success comes at the SKU level.

Practical Tip:

After every campaign, analyze:

• Which SKUs drove incremental uplift vs those that were already selling well

• Which SKUs cannibalized full - price sales

• Which SKUs saw stockouts or oversupply

Then feed that insight into future campaign planning. For example, a pasta brand that sold out during a Ramadan bundle might not need discounting next time. A high - stock, low - conversion snack item might need creative bundling or cross - category pairing instead.

2. Tie Promotions to Clear Business Goals, Not Just Calendar Events

Many retailers fall into the trap of running promotions just because a date appears on the retail calendar. But what are you actually trying to solve?

• Do you want to increase average transaction value?

• Move ageing inventory?

• Win back lapsed customers?

• Drive trial of a new category?

Practical Tip:

Before launching a promotion, align your teams on one primary goal. Then shape the offer, targeting, and messaging around that.

For example:

• Goal: Increase ATV. → Create mix - and - match offers or bundling.

• Goal: Drive trial. → Target low - engagement customers with entry - level SKUs at a small incentive.

• Goal: Clear inventory. → Focus on high - stock, low - velocity SKUs - but avoid making them the center of mass promotions that hurt brand perception.

  
  

  
  

3. Segment Promotions by Customer Type

In 2025, retailers have access to more customer data than ever - but too few use it to drive promotion targeting. Most shoppers receive the same deal, regardless of purchase history, preferences, or value to the brand.

Practical Tip:

Use simple segmentation to run smarter promos:

• Loyal customers: Early access or personalized offers on high - margin items

• Churned customers: Win - back coupons tied to past preferences

• First - time shoppers: Incentives to convert quickly, not necessarily deep discounts

• Low - value repeaters: Test upsell or cross - sell offers to increase basket size

Even with basic RFM (Recency, Frequency, Monetary) data, you can segment and send more relevant offers that increase ROI without increasing discount depth.

4. Localize Offers by Store Cluster or Region

Not all stores perform equally - and promotions shouldn’t be applied blindly across your network. Store clusters vary in customer mix, product velocity, and price sensitivity.

Practical Tip:

• Identify top - performing and underperforming stores for a given category

• Test regional variations in pricing, mechanics (e.g., buy - one - get - one vs. flat discount), and messaging

• Adjust the promo calendar per cluster to avoid overexposure or overstock

For instance, what works in Jakarta’s central outlets may flop in suburban mini - marts. In the GCC, expat - heavy neighborhoods might respond better to different value bundles than family - oriented areas.

5. Train Store Staff to Execute the Final Mile

Even the most well - designed promotion fails if the execution falls flat in - store. In omnichannel environments, execution consistency is a massive challenge.

Practical Tip:

• Create a promo playbook for store teams with clear SKU lists, visuals, and talking points

• Use WhatsApp groups or retail communication apps to share daily updates, FAQs, or real - time clarifications

• Run surprise audits or mystery shopping in the first few days of the campaign to fix gaps early

Empowering store staff to become brand advocates (not just stockers) can increase the visibility and perceived value of your offers - especially for fashion, beauty, and lifestyle brands.

6. Track Promotions Beyond Redemption

Redemption rates and lift during a campaign tell only part of the story. What happens after the promotion matters more.

Practical Tip:

Use your existing POS and loyalty data to measure:

• Repeat rate: Did promo customers come back in the next 30 - 60 days?

• Margin impact: Did the promotion result in a net gain or loss?

• Upsell success: Did the promo increase total basket value?

• Cannibalization: Did it pull volume from non - promoted SKUs?

This post - campaign intelligence helps refine future targeting and discount levels.

7. Test One Variable at a Time

Retailers often run promotions with too many variables changing at once - making it impossible to know what worked.

Practical Tip:

• Isolate one element per test: Offer type, price point, channel, or message

• Run A/B tests with control stores or digital audiences

• Track not just conversion, but also order value, return rate, and repeat behavior

This experimental mindset makes promotions a learning engine, not just a sales lever.

So Where Does AI Actually Fit?

AI becomes most effective when layered on top of a strong foundation. If your product tagging is inconsistent, customer data is incomplete, or promotion tracking is fragmented - AI will only amplify the noise.

Retailers who see success with AI in promotions typically:

• Have clean, unified product and customer data

• Have run iterative experiments that AI can learn from

• Use AI to predict and scale what's already been tested in real life

In short: Fix the basics, then add the brains.

Conclusion: Don’t Wait for AI. Act Now.

AI can be a powerful enabler. But it is not a prerequisite for running smarter promotions. In 2025, the retailers who win are not those with the fanciest tech - but those who apply discipline, segmentation, and experimentation to their promotional playbook.

Start with what you know:

• Your best - selling SKUs

• Your most loyal and lapsed customers

• Your store performance differences

• Your team’s ability to execute on the ground

Then test. Learn. Repeat.

Because the future of retail promotions isn’t just predictive. It’s practical.