AI-Powered Loyalty Programs Retailers Can’t Ignore

Consumers are enrolled in 17.4 loyalty programs on average. That number comes from the Global Customer Loyalty Report 2025, and it should make every retailer a little uncomfortable. Not because loyalty is “solved”—but because your customers are already spread across a crowded wallet of memberships, apps, and accounts.

Here’s the uncomfortable part: even with growing participation, customer satisfaction with loyalty programs is declining year over year. So the problem isn’t awareness or adoption. The problem is value. Most loyalty programs feel like homework: buy a lot, wait a long time, maybe get something you don’t really want.

For retailers in Ireland (and any market facing margin pressure, higher acquisition costs, and volatile demand), a loyalty program is still a must-have. But the modern version can’t be “points for purchases” and a monthly email blast. The loyalty programs that win in 2026 will be AI-assisted, omnichannel, and utility-first—built around how people actually shop, not how we wish they shopped.

Why loyalty programs are now a baseline (not a differentiator)

A loyalty program is table stakes because it’s one of the few assets you can build that lowers your dependence on paid media over time. When you have a real member base—with permissions, purchase history, and engagement signals—you can market more efficiently, forecast demand better, and protect margin with targeted incentives instead of blanket discounting.

That said, simply “having” a program doesn’t earn loyalty. Customers don’t wake up emotionally attached to a points balance. The data backing this is consistent across studies: loyalty is driven by practical benefits—saving money, earning tangible rewards, and getting relevant offers.

This is where many programs break down:

• They’re slow to reward (earn rates feel stingy).
• They’re hard to redeem (limited options, confusing rules).
• They’re the same for everyone (no recognition, no relevance).

AI in retail and e-commerce changes the economics of this. When personalization and customer behavior analysis are built into the program, you can give customers what they value without turning loyalty into a discount-only race to the bottom.

The reality customers are signaling

The Global Customer Loyalty Report 2025 (Antavo) highlights three blunt truths:

1. Members want more ways to earn.
2. Members want more ways to redeem.
3. 76% want transactional rewards like discounts and cashback.

If your program is mostly “collect points, redeem for a voucher later,” it’s not meeting the baseline expectation anymore.

What a “successful” loyalty program actually delivers

A successful loyalty program does three jobs at once: it changes customer behaviour, it creates measurable margin, and it improves the shopping experience. If you don’t get all three, you’ll end up with a program that looks active on paper but doesn’t move the needle.

1) Utility: rewards that feel real, fast, and flexible

Customers don’t want a loyalty program that promises a future benefit after 12 purchases. They want to feel value early.

Practical structures that work (especially for grocery, pharmacy, beauty, and fashion):

• Instant benefits on sign-up (welcome reward, first-purchase bonus, free delivery threshold)
• Mixed rewards (cashback + member pricing + partner rewards)
• Micro-redemptions (let customers redeem small amounts frequently)

If you want one sentence that’s worth sticking on a whiteboard:

If redemption feels like friction, loyalty feels like work.

2) Choice: multiple earning paths beyond “spend more”

“Spend-based only” programs miss a huge opportunity: customers engage in ways that don’t immediately show up as revenue but still reduce costs or increase conversion.

Earning options that tend to perform:

• Buying across categories (encourages basket expansion)
• Choosing lower-cost fulfilment options (click & collect, locker pickup)
• Reviews, referrals, and community participation
• Subscriptions and replenishment behaviours

This is also where AI can help most: it can identify which non-spend behaviors correlate with long-term value, then reward those behaviors intentionally.

3) Clarity: rules customers can understand in 10 seconds

Most companies get this wrong. They build loyalty like a compliance document.

Your loyalty proposition should pass the “10-second test”:

• What do I get?
• How do I earn it?
• How do I use it?

If it takes a FAQ to explain how redemption works, you’re leaking participation at every step.

How AI upgrades loyalty from “points” to personalization

AI-powered loyalty programs aren’t about flashy features. They’re about using your data to make the program more relevant and less wasteful.

You already have signals across e-commerce and stores: product affinity, basket patterns, return behavior, promo sensitivity, channel preference, and timing. AI in retail and e-commerce helps turn those signals into decisions that customers actually feel.

Personalised rewards without blanket discounts

The easiest (and most expensive) loyalty strategy is “10% off for everyone.” It trains customers to wait for promos and erodes margin.

A better approach is personalised incentives based on customer behavior analysis:

• Give discounts only where they change behavior (first repeat purchase, lapsed reactivation)
• Offer non-discount perks to high-value customers (priority support, early access, free alterations)
• Use category-specific offers to grow basket mix instead of subsidizing purchases customers would make anyway

This is where AI earns its keep: predicting incremental lift—not just rewarding what would have happened regardless.

Smarter segmentation: stop treating “members” as one group

A loyalty database is not one audience; it’s a set of micro-audiences.

Practical segments AI can help maintain dynamically:

• New members who haven’t made their second purchase
• High spenders with declining visit frequency
• Promo-driven shoppers who only buy on sale
• Online-first members with high return rates
• Store-first members who respond to in-app reminders

These segments shift weekly. Static rules don’t keep up. AI models can.

Omnichannel loyalty that doesn’t feel stitched together

Customers don’t think in channels; they think in tasks: browse, compare, buy, collect, return.

If your loyalty program is strong online but invisible in-store (or vice versa), it will underperform.

AI supports omnichannel execution by:

• Unifying identity across touchpoints (app, email, POS, customer service)
• Triggering real-time offers (e.g., cart abandonment, back-in-stock, store proximity)
• Recommending next-best actions to staff or customer service (save a sale, prevent a return)

The win isn’t “more messages.” It’s fewer, better-timed messages that match intent.

Fixing loyalty satisfaction: the 5 failure modes to address first

If satisfaction is dropping despite higher enrolment, it’s because many programs have become bloated, stingy, or irrelevant. Before you redesign everything, fix these five issues.

1) Earning feels too slow

Customers do the math. If rewards feel unattainable, they disengage.

Action: run a simple audit—how long does it take an average member to earn their first meaningful reward? If it’s more than a few transactions in your category, tighten the loop.

2) Redemption is restrictive

People want options: discounts, cashback, partner rewards, experiential perks. The more flexible redemption is, the more “real” the program feels.

Action: expand redemption types, and reduce minimum thresholds.

3) The program doesn’t recognise context

A parent buying school uniforms in August has different needs than the same customer shopping in December.

Action: use AI-driven personalization to switch from “monthly promo calendar” to “contextual rewards.”

4) Privacy and transparency are vague

Customers will share data when the trade is clear. They won’t tolerate surprises.

Action: explain data use plainly inside the loyalty experience:

• What data you collect
• What you do with it
• What the customer gets in return

5) Everyone gets the same thing

Uniform rewards are easy to manage but wasteful. Your best customers want recognition; your at-risk customers need a reason to come back.

Action: introduce tiers carefully, and make the benefits tangible (not just a badge).

A practical blueprint: build an AI-ready loyalty program in 90 days

You don’t need a two-year transformation project. You need a controlled rollout that proves value.

Phase 1 (Weeks 1–3): Define value and measure the baseline

Do these before picking tools:

• Define the “job” of loyalty (repeat rate, basket size, frequency, margin)
• Establish baseline metrics: repeat purchase rate, redemption rate, member share of revenue, churn/lapse rate
• Identify your first two use cases (e.g., second purchase acceleration and win-back)

Phase 2 (Weeks 4–8): Launch the minimum lovable program

Focus on clarity and utility:

• Simple earn rules
• Immediate welcome benefit
• Redemption that works in both store and e-commerce
• A single view of member activity (even if it’s not perfect yet)

Phase 3 (Weeks 9–12): Add AI where it pays for itself

Start small and measurable:

• Propensity model: who’s likely to lapse in the next 30 days?
• Offer optimization: which incentive increases incremental purchases?
• Next-best action: what message should this customer get now?

If you can’t measure incremental lift, you’re not doing AI—you’re doing automation.

People also ask: quick answers for retail teams

Do loyalty programs still work when everyone has one?

Yes—but only when the program provides fast, practical value and makes redemption easy. “Points for later” isn’t competitive anymore.

Are discounts the only rewards customers care about?

No, but 76% prefer transactional rewards like discounts and cashback. The smart move is mixing transactional rewards with perks that don’t destroy margin.

What’s the first AI use case to prioritise in loyalty?

Second-purchase acceleration. Getting a new member to make purchase #2 is one of the highest ROI plays, and AI can identify the right nudge and timing.

Where loyalty is heading next for Irish retail and e-commerce

In this “AI in Retail and E-Commerce” series, a pattern keeps showing up: the retailers winning right now aren’t shouting louder—they’re getting more precise. Loyalty is the perfect place to apply that precision because it sits at the intersection of customer data, omnichannel experience, and retention economics.

If you’re planning for 2026, treat your loyalty program like a product, not a promotion. Make it easy to understand, satisfying to use, and respectful of customer data. Then use AI-driven personalization to stop wasting incentives on customers who didn’t need them.

The question worth asking in your next leadership meeting isn’t “Do we need a loyalty program?” It’s this: If satisfaction is declining across the industry, what will we do that actually feels better than the program customers already have?