
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.
• 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
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.
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
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.
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