Mode buys JibJab for $29.5M to fuel data rewards model

Fast Company reported that Mode has acquired JibJab for up to $29.5 million in a mix of cash and stock.reported This transaction represents Mode’s eleventh acquisition since January 2025 and its largest deal of the current year.reportedMode bought JibJab to help people trade their personal data for free app features.Mode’s acquisition of JibJab expands its EarnOS platform to capture consented user interaction data for AI training tasks. The purchase targets an established e-card and video company known for viral content.

The announcement

Mode’s cofounder and CEO Dan Novaes stated the company plans to integrate JibJab into its rewards and monetization system called EarnOS. Specific integration details remain undetermined at this time. Novaes noted that JibJab is profitable and generates tens of millions of dollars in annual revenue. The deal structure includes both cash and equity components.

The context

Mode operates a business model that rewards app users for sharing their data. Users can opt in to share information with businesses conducting consumer research or AI training in exchange for premium subscriptions. Novaes explained that only about five percent of app users typically pay for premium subscriptions. The company aims to convert non-paying users into engaged participants through data sharing.

Reading between the lines

Novaes contrasted Mode’s opt-in approach with broader industry practices where AI labs acquire training data without explicit consumer consent. He described other methods as questionable, noting that most internet data was collected without users opting in. Mode emphasizes that users must always opt in to participate in its data exchange transactions.

The business case

For AI platform architects, this acquisition highlights a vendor strategy focused on sourcing high-quality, consented training data through consumer incentives. Mode’s model addresses the low five percent conversion rate for paid subscriptions by offering alternative monetization. Integrating JibJab’s profitable revenue stream into EarnOS suggests a push to scale opt-in data collection. This approach may influence how platforms evaluate data sourcing costs versus traditional scraping methods.