Web3 Growth Study Case: How Action Model Built 8,991 Verified AI Believers in One Campaign

Action Model is building the world’s first community-owned Large Action Model — an AI trained, governed, and owned by its users, not by corporations. When the team needed to grow their community in a way that matched the depth of that mission, the goal wasn’t reach. It was finding the right people and keeping them.

THE CHALLENGE

Most Web3 growth campaigns optimize for volume: impressions, sign-ups, wallet connections. The numbers look good for a week, then disappear. Action Model needed something structurally different — a way to identify users who genuinely resonated with the LAM narrative, verify that resonance through real behavior, and build a retention layer that worked independently of active campaign incentives.

THE APPROACH

Action Model deployed TaskOn’s White-Label GrowthKit directly inside its own product interface — not as a separate campaign page, but as an embedded growth layer. This distinction matters: when the growth infrastructure lives inside your product, the user never leaves, the data stays yours, and every interaction builds on the relationship rather than interrupting it.

The campaign — “Join the LAM Resistance — Build the Future of AI” — was structured across three connected mechanics.

Quest and funnel design gave the campaign its filtering function. Rather than rewarding anyone who clicked through, the quest moved users through a structured sequence of real actions. Passive observers dropped out naturally; users who completed each stage had demonstrated actual intent. The result was a 77% visitor-to-participant rate, 86% participant-to-submitter rate, and a 100% submitter-to-qualifier rate — a funnel that didn’t leak because it was designed to find genuine participants, not maximize throughput.

Leaderboard and Rewards mechanics handled retention from day one. Users had visible progress to track, meaningful incentives at each stage, and forward-looking rewards that extended past the campaign window. The retention architecture was signaled clearly before the campaign launched, so users who joined understood the full arc — not just the initial ask.

Hub and community tools anchored the acquisition layer. The campaign hub drew 37,619 visitors and converted 49% into community followers across the campaign window.

THE RESULTS

The 8,991 verified qualifiers weren’t a volume metric — they were a behaviorally filtered cohort, confirmed at every stage of the funnel. Post-campaign, Week 1 retention held at 32% and Week 2 at 28%, with Day 30 Dapp retention settling at 5% — a stable floor that reflects users who returned on their own terms, not because a campaign was still running.

WHY THE INFRASTRUCTURE MODEL MATTERS

The underlying logic across acquisition, identification, and retention is the same: growth that runs inside your product produces assets, not just activity. User data, wallet addresses, and behavioral signals stay inside Action Model’s ecosystem. The campaign results compound over time because the relationships formed during the campaign belong to the project.

TaskOn White-Label is what that infrastructure looks like in practice — a modular, embeddable growth suite that adapts to where your project is and where it’s going.

→ taskon.xyz