Five tips to use AI in loyalty and promotions campaigns

Enterprise Times met with Michal Sedzielewski co-founder of Voucherify at the MACH X event in Toronto. Voucherify is an API-first promotion and loyalty management platform designed to help businesses build, manage, and scale personalised incentive programmes. The event, The Agentic Advantage, hosted by the MACH Alliance, helped enterprise leaders shift from AI trials to developing “AI-ready” systems with composable technology. The conversation explored how Voucherify evolved from a small Polish software agency into an API first promotions and loyalty platform. The company uses AI and composable architectures to let enterprises run highly targeted, quickly deployable, and scalable incentive campaigns. As a result, Sedzielewski provided his top five tips for enterprises looking to apply AI to loyalty and promotional campaigns.

1. Fix data quality before you touch AI

For AI to work effectively, it needs clean duplicates, standardise formats, and resolve conflicting records. Organisations must consolidate key data sources (transactions, product catalogue, customer attributes, engagement history) into a unified, actionable profile. Organisations should consider investing in a minimal data model that marketing, product, and engineering all understand. (E.g., customer, order, product, promotion, channel events).

2. Start with simple, targeted incentives

Launch simple, personalised coupons and offers first (e.g., second order incentive, lapsed customer win backs, tailored bundles). Use AI to Identify high value segments and triggers. Then optimise send time, channel, and basic offer structure. Measure incremental lift (vs. a control group) before investing in complex tiers, points liability models, or “gamified” mechanics.

3. Think about scalability

Consider the ability of the promotion/loyalty engine to handle very high traffic and load. (E.g. Black Friday, Christmas, TV campaigns like the Big Brother Brazil promo), without crashing, slowing down, or mis‑calculating discounts. Plan for the huge numbers of customers hitting the site/app at once with multiple promotions and complex rules being evaluated in real-time.

In addition to redemptions spiking suddenly because a campaign “goes viral”. As a result, the AI‑driven loyalty and promotion system must be architected so that, if a campaign is successful, the underlying engine and infrastructure can scale up smoothly. Moreover, keep validating promos correctly at peak demand. Rather than failing on the most important revenue days.

4. Balance innovation with guardrails and fraud protection

AI can move very fast—and so can promo abuse. Put hard guardrails around discounts (caps per user/order/day, exclusion rules, stackability rules). Use AI and analytics to spot anomalies and fraud patterns early. (e.g., viral code sharing, unusual redemption spikes). Ensure the business can rollback or adjust campaigns quickly if something goes wrong.

5. Design for customer experience, not just conversion

Ensure relevance (e.g., don’t send meat offers to vegans or deep discounts to customers who would pay full price anyway). Coordinate content, timing, and channels so promotions feel like part of a coherent journey, not spam. Remember: trust and experience are the real loyalty drivers; AI and promotions should support that, not undermine it.

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