Incentives are one of the fastest ways to drive conversion, increase average order value, and improve repurchase. But in practice, optimizing incentives is operationally heavy, so most teams fall back on the same static discounts quarter after quarter. The result is a costly tradeoff: brands either over-discount and erode margin, or under-incentivize and miss revenue opportunities.
Today, we're excited to announce the launch of Vincent, a conversational AI interface designed to remove these barriers. Vincent allows teams to design, test, analyze, and modify incentives using natural language, reducing the time between idea and live experiment from days to minutes.
“Voucherify has always been built for complex incentives,” said Tomasz Pindel, CEO and co-founder of Voucherify. “Vincent makes that power accessible without slowing teams down. Instead of translating intent into configuration steps, users can express what they want to achieve, launch experiments faster, and iterate in real time.”
With Vincent, we're introducing a new way to design and optimize incentives. Instead of translating marketing ideas into configuration logic across multiple interfaces, teams can describe the outcome they want to achieve. Vincent converts that intent into structured incentive logic using the same rules, validation layers, and safeguards that power Voucherify today.
.webp)
By shortening the cycle between idea, launch, and analysis, Vincent enables teams to run more experiments and continuously improve the incentives that drive conversion, repurchase, and revenue.
Vincent also connects incentive optimization with external market intelligence.
Promotions do not operate in isolation. Pricing pressure, competitive campaigns, and seasonal trends all influence how customers respond to incentives. Yet most teams still plan promotions using internal data alone, with limited visibility into how competitors structure their offers.
Vincent can incorporate external promotional intelligence sources, such as market and competitive data platforms, to provide broader context for incentive decisions.
.webp)
Instead of treating competitive research and campaign execution as separate processes, Vincent brings them into the same workflow. Market signals become actionable inputs for incentive design, enabling teams to respond faster to changing promotional landscapes.
Incentives directly influence pricing, margin, and customer experience. For enterprise teams, that makes control and governance essential.
Vincent is designed to accelerate experimentation without compromising oversight. Every proposed campaign change is surfaced for review before execution, allowing teams to approve, modify, or reject configurations while maintaining full visibility into how incentive logic is applied.
“This isn’t about removing humans from the loop,” said Pindel. “It’s about giving teams the ability to experiment faster while keeping full control over how incentives impact the business.”
Vincent reflects a broader shift in how incentives will be delivered in the coming years. As commerce becomes increasingly AI-assisted, incentive systems must evolve beyond static campaign logic. Future incentive decisions will increasingly be made in real time, responding to signals such as customer intent, purchasing context, and automated agent interactions.
By introducing natural language as an interaction layer, we're supporting both human-led experimentation today and the agent-driven commerce models emerging across digital platforms.
Vincent is currently available to selected customers, with broader rollout planned in phases.
.svg){kind=icon}
