Technology and the Shift in Managing 'Personalised Offers'

The distinction between personalisation and what is actually sophisticated segmentation matters enormously, especially as personalisation innovation moves into the age of AI. In this article, I offer a framework to help clarify what constitutes a truly personalised offer and why this matters for maximising the returns from a loyalty program.

What is True Personalisation?

A genuinely personalised offer is unique and exclusive to an individual customer. Anything less is simply intelligent segmentation. We can understand this distinction by looking at two dimensions in an offer:

Audience Granularity: Is the offer directed at a group or tailored to an individual?

Eligibility: Is the offer open to all customers or restricted to a specific audience?

When combined, these two dimensions create a 2x2 matrix for sharpening the definition of personalisation but also illustrating how offers have evolved - and continue to evolve - over time.

Stage 1: Mass-Market Promotions (Group-Based, Open)

For decades, most retailers have leaned on mass promotions such as "20% off everything this weekend" or "Buy One Get One Free." While these tactics reliably move volume, they come at a high cost. Margins are eroded, brand equity is diluted, and customers are effectively trained to purchase when discounts are offered.

The problem goes deeper: because these promotions apply indiscriminately, much of the investment flows to shoppers who are deal-driven and often the least profitable. Meanwhile, the most loyal and profitable customers are under-rewarded. In effect, retailers subsidise bargain hunters while neglecting their best customers.

This dynamic has fuelled the growth of Everyday Low Price (EDLP) retailers, who win by offering consistent prices to all customers. By avoiding the trap of store-wide promotions, EDLP players build trust and capture value from customers that mass-promotion retailers are failing to nurture.

In the APAC market, we've seen this play out dramatically. Retailers that rely heavily on promotional catalogues and blanket discounts find themselves in a race to the bottom, constantly trying to outdo competitors on price rather than building genuine loyalty. Checking the catalogue becomes a ritual, but it's one that trains customers to wait for deals rather than shop based on preference or convenience.

Stage 2: Segmented Offers (Group-Based, Gated)

Using modern loyalty platforms, many retailers are transitioning away from mass promotions by creating a pool of gated offers. These offers are not open to everyone; they are restricted by eligibility rules - for example, being a member of the loyalty program. From this pool, each customer is issued a curated selection based on their past behaviour and the retailer's commercial priorities.

While this is a clear step up from blanket promotions, it remains one-size-fits-all. The pool usually covers only a portion of the product range. For instance, if a pharmacy retailer features Huggies nappies in its pool, a loyal Babylove shopper may find nothing relevant. The retailer misses incremental sales, the supplier loses visibility, and the customer feels overlooked.

A further limitation is that qualification and reward structures are rarely customised. Different shoppers will respond to different incentives, and a fixed pool cannot adapt to these nuances.

Curated pools are certainly more effective than mass promotions, but they still leave large gaps. In reality, this is still targeting, not true personalisation.

The APAC retail landscape provides ample evidence of this stage in action. Major retailers have invested heavily in their loyalty platforms and mobile apps, creating sophisticated segmentation engines that can deliver different offers to different groups. 

A pet owner might see offers on pet food, whilst a young family receives nappy promotions. This represents real progress, and customers generally appreciate the increased relevance compared to mass-market catalogues.

However, the limitations become apparent when you consider the diversity within these segments. Not all pet owners buy the same brands, not all families have children of the same age, and shopping patterns vary wildly even within seemingly homogeneous groups. 

A segment of "vegan fitness enthusiasts" might include someone who is a marathon runner focused on plant-based protein powders, and another who does yoga and only shops for vegan snack bars. Even within this narrow group, the needs and product choices differ significantly, showing how personalisation is necessary even when segments seem very specific.

Stage 3: Personalised Offers (Individual-Based, Gated)

This is where true personalisation begins. A genuinely individualised offer tailors the product, qualification, and reward to each customer. For example, two shoppers might receive completely different incentives for the same category:

Customer 1: "Spend $10 on Frozen Fruit & Vegetables this month and get 110 points."

Customer 2: "Spend $18 on Frozen Fruit & Vegetables this month and get 180 points."

With hundreds of millions of potential variations, offers can be highly relevant to each individual. Retailers that use this approach see far greater engagement and redemption compared to segment-based digital coupons.

Crucially, this model isn't limited to "high-low" retailers that rely on discounting. Everyday Low Price (EDLP) retailers can also adopt it, as algorithms can be configured to reward only incremental spend. This preserves the promise of consistent low prices whilst still nudging additional purchases.

For brands, the precision is equally compelling. Instead of funding broad, inefficient promotions, they can invest where it guarantees results. For example, a "challenge" offer in the frozen category typically delivers a 4:1 sales uplift relative to investment.

The shift to true personalisation represents a fundamental change in how retailers think about customer engagement. Rather than asking "what offers should we run this week and with which suppliers?", the question becomes "what does each customer need to hear from us right now?" This requires a different mindset, different technology, and different partnerships with suppliers.

AI Innovation and Progress in Personalisation

Achieving one-to-one personalisation has been a retail goal for decades. But even as the industry has made real progress towards recognising individual shoppers through loyalty and digital channels, truly customised promotions remain a challenge. Traditional retail promotions rely on either undifferentiated blanket discounts or "targeted" offers manually deployed to broad customer segments, limiting relevance and efficiency.

Eagle Eye recently launched 'Personalised Promotions', an AI-powered solution that allows retailers to automatically create one-to-one offers to millions of shoppers in real time, moving personalisation from strategy into scalable execution. 

With Personalised Promotions, retailers can:

• Deliver tailored offers to each customer as an individual, resulting in greater return per promotional dollar, reduced operational workload, and improved customer recruitment, reactivation, and long-term engagement. 
• Leverage AI and machine learning models powered by Google's Vertex AI to create, personalise, allocate and execute targeted discount offers for each shopper, aligned to both customer preferences and retailer objectives and budgets.
• Strengthen retailer-supplier collaboration by giving CPG brands a proven, measurable way to influence customer behaviour. Brands gain access to clear audience, performance and incremental sales reporting. 
• Achieve attribution at the individual level, creating new opportunities for supplier funding while providing clearer measurement of promotional impact, unlike traditional promotional platforms that rely on predefined segments and limited "best-fit" pools.
• Deploy new, omnichannel, AI-generated offers bound by customisable business objectives and guardrails, allowing them to retain centralised control over their promotional strategies while enjoying the scale and efficiency gains afforded by an AI-first personalisation engine. 

Along with the highly successful Personalised Challenges, Personalised Promotions is part of Eagle Eye's full suite of retail-sector focused loyalty and personalisation innovations designed for enterprise retailers and grocers, convenience store groups and CPG brands.

Loyalty and the AI Era: Ready to Embrace Genuine Personalisation At Scale

For loyalty programs to remain relevant and valuable in an increasingly competitive landscape, the evolution from segmentation to true personalisation isn't optional. It's the next essential chapter in delivering customer experiences that genuinely matter.

APAC's retail market is particularly well-positioned to embrace this shift. With high smartphone penetration, sophisticated payment infrastructure, and customers who are already comfortable with loyalty programs, the foundations are in place. What's been missing until recently is the technology and AI innovation to deliver genuine personalisation at scale without requiring years of in-house development.

The path from mass promotions to true personalisation is a strategic imperative. Retailers across APAC that continue to rely primarily on broad discounting will find themselves increasingly disadvantaged against the eCommerce pure-plays like Amazon. Those that embrace genuine personalisation will build deeper relationships, command better margins, and create experiences that customers genuinely value.