Data-Driven Personalisation: How Smart E-Vouchers Help APAC Brands Understand Consumer Behaviour

August 25, 2026
8 分鐘 / 8 mins

How Smart E-Vouchers Become a Consumer Behaviour Data Engine

Most marketers view e-vouchers as reward distribution tools. The differentiator that separates Smart E-Vouchers from conventional alternatives is their capacity to capture behavioural data at every consumer interaction — automatically, and in real time.

Every On-us Smart E-Voucher open begins recording: when, on which device, for how long, which merchants were browsed, and where the redemption occurred. These 20+ behavioural metrics represent the most accurate first-party consumer intelligence a brand can own.

What Behavioural Data Can E-Vouchers Capture?

Open behaviour — Time, location and device type at open

Engagement depth — Dwell time (On-us average: 2.5 minutes), scroll depth, banner click-through rate

Merchant preference — Category and specific merchant browsed, final selection made

Redemption behaviour — Location, time, originating channel (App / WhatsApp / SMS / Email)

Non-redemption signals — Opened-but-not-redeemed ratio, expiry vs. active abandonment

The Role of Personalisation in Consumer Engagement

Research consistently shows that consumers engage with and redeem rewards that feel tailored to them at significantly higher rates than generic promotions. On-us Intelligence analyses historical interaction data to automatically identify each consumer's most likely merchant category preference, adjusting the merchant mix recommendation with every subsequent reward issuance.

The Data-Driven Optimisation Loop

1. Execute campaign — Distribute e-vouchers; track 20+ behavioural metrics

2. Analyse — Identify high-engagement segment characteristics

3. Retarget redeemers — Send personalised "next action" vouchers to redemption cohort

4. Re-engage non-openers — Trigger differentiated messaging with alternative merchant mix

5. Continuous optimisation — Each campaign's data feeds the next, creating a compounding improvement flywheel

How AI Powers Precision Reward Recommendations

On-us Intelligence AI analyses each consumer's historical interaction record, merchant preferences and redemption timing to automatically generate a personalised merchant ranking for every reward issuance — so Consumer A sees a different merchant sequence than Consumer B within the same campaign, each curated for maximum relevance.

See On-us Intelligence data capabilities. Book a demo.

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