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Blur's Token Incentive Model

Key Insights

  • Blur's gradual token incentive airdrop model has proven successful thus far, catapulting it to an industry-leading position by fostering both user acquisition and retention.
  • With 10% higher retention rates among high-volume traders, Blur's case emphasizes that long-term user engagement is maintained by offering a superior user experience and not just token incentives.
  • In the wake of Blur's success, copycat projects have surfaced, yet their growth and market dominance will require these projects to go beyond Blur and introduce distinctive features while adapting to changing user needs and market trends.

Token incentives play a vital role in attracting and retaining users. Blur popularized the use of the campaign airdrop system. Rather than the conventional one-time lump sum airdrops, the campaign system promotes long-term engagement by tying future airdrops and token emissions to customer loyalty programs. This initiative has propelled Blur into an industry-leading position, creating a shift in the user acquisition and retention paradigm.

Nonetheless, the success of token incentives, while instrumental in fueling Blur's ascension, has not generally translated into noteworthy retention within post-incentive programs across the broader cryptocurrency industry. Granted, Blur's model of sustained loyalty and ongoing incentives seems like a promising stride towards fostering persistent customer engagement. The question, however, remains: is it just a step in the right direction, or has it arrived at the destination? To measure the efficacy of Blur’s model compared to previous incentive models, we measured the user retention patterns across different user segments. Additionally, we used the rate of new users joining to determine how attractive Blur’s program has made the product.

Blur’s Token Incentive Model

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Ally is a Research Analyst on the Enterprise team at Messari. Prior to joining the team, Ally worked as a Structural Engineer at Magnusson Klemencic Associates. Ally graduated from the University of Illinois in 2018 with a master’s degree in Civil and Structural Engineering.

Mentioned Assets
Outline
  • Key Insights
  • Blur’s Token Incentive Model
  • User Retention on Blur
  • Market Comparisons
  • Final Thoughts
Author
Ally is a Research Analyst on the Enterprise team at Messari. Prior to joining the team, Ally worked as a Structural Engineer at Magnusson Klemencic Associates. Ally graduated from the University of Illinois in 2018 with a master’s degree in Civil and Structural Engineering.
Mentioned Assets