EARN’M is a leading DePIN rewards ecosystem with over 45M+ users, turning everyday mobile activity into onchain rewards.
Operating at this scale means running high-volume creator campaigns across multiple regions and audience segments. But with KOL marketing, surface metrics often don’t tell the full story , large followings don’t always translate into real engagement or conversions.
To improve creator selection and campaign performance, EARN’M integrated Cookie3’s KOL Intelligence, bringing structure, transparency, and data-backed decision-making into their workflow.
Results
Key Activities
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Every inbound or referred KOL was evaluated using Cookie3’s scoring system, allowing the team to filter out low-quality creators early.
Campaigns were monitored on a weekly basis, analyzing engagement trends and identifying which creators were delivering real results.
EARN’M analyzed KOLs used by other successful projects, identifying patterns and discovering new high-performing creators.
Before using KOL Intelligence, EARN’M faced several limitations:
- KOL evaluation relied heavily on manual research and spreadsheets
- Surface metrics like followers and impressions were often misleading or inflated
- It was difficult to identify high-quality micro-influencers at scale
- Campaign tracking required constant manual checks across multiple sources
Large creators with strong engagement numbers often delivered weak results, while smaller creators were harder to discover and validate.
The team needed a way to:
- identify authentic, high-performing creators
- eliminate wasted spend on underperforming KOLs
- and track campaign performance without manual overhead
Turning KOL Selection Into a Performance System
When EARN’M integrated Cookie3’s KOL Intelligence, the biggest shift wasn’t just better data , it was a complete change in how the team approached creator marketing.
Before, evaluating KOLs meant manually collecting profiles, tracking performance in spreadsheets, and relying on surface metrics that often didn’t reflect real impact. With Cookie3, that process became centralized, structured, and significantly faster.
Every KOL , whether inbound, referred, or sourced , was systematically evaluated using performance scores and audience quality insights. Instead of asking “does this creator look good?”, the team could now answer a much more important question: Does this creator actually deliver results?
This change became especially powerful at the campaign level. Using Cookie3’s tracking features, EARN’M grouped creators into campaigns and reviewed their performance weekly. This created a consistent optimization loop: underperforming KOLs were quickly identified and removed, while high-performing ones were prioritized and scaled.
Over time, a clear pattern emerged.
Many large KOLs with impressive-looking metrics failed to deliver meaningful results. At the same time, smaller creators, often with fewer than 20K followers, consistently drove stronger conversions through tighter, more engaged communities.
This allowed EARN’M to shift its strategy with confidence. Creator selection became performance-driven, budget allocation became more precise, and campaign decisions were backed by data rather than intuition.
At the same time, the operational burden dropped significantly. Tasks that previously required hours of manual tracking and comparison were replaced by clear dashboards and campaign-level visibility. This freed up the team to focus less on chasing metrics and more on strategy, creative direction, and growth.
Better ROI
~25–30% reduction in wasted KOL spend through better creator filtering
Higher conversion
1.4–1.6× higher conversions from data-selected creators
Faster campaign optimization cycles
with weekly performance tracking and manual workload significantly reduced, enabling more strategic focus.
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