Quest Love: A First Look at Blockchain Loyalty Programs

TL;DR

The paper investigates quest-based loyalty programs in blockchain ecosystems and how reward design, cost, difficulty, and monetization influence task completion. Using a proprietary dataset of 43 quests across 10 months with 80M completions, it quantifies correlations via Spearman metrics and tracks epoch-aligned events including an airdrop; retention is defined as $RR= \frac{(E-N)}{S} \cdot 100$. Key findings show that monetary rewards can spike completions but do not foster loyalty; cost and thresholds strongly deter participation, suggesting a transactional dynamic potentially driven by farming. The study discusses stakeholder incentives and outlines design considerations for anti-farming and more trustworthy metrics, while acknowledging limitations due to single-platform data and lack of ground truth on bots.

Abstract

Blockchain ecosystems -- such as those built around chains, layers, and services -- try to engage users for a variety of reasons: user education, growing and protecting their market share, climbing metric-measuring leaderboards with competing systems, demonstrating usage to investors, and identifying worthy recipients for newly created tokens (airdrops). A popular approach is offering user quests: small tasks that can be completed by a user, exposing them to a common task they might want to do in the future, and rewarding them for completion. In this paper, we analyze a proprietary dataset from one deployed quest system that offered 43 unique quests over 10 months with 80M completions. We offer insights about the factors that correlate with task completion: amount of reward, monetary value of reward, difficulty, and cost. We also discuss the role of farming and bots, and the factors that complicate distinguishing real users from automated scripts.

Figures (6)

• Figure 1: Total completions of all quests offered in each epoch. Overlay of public announcements that may impact user participation.
• Figure 2: Reward amount (in non-monetary points) of different quests offered from Epoch 5--42. Completion rates do not correlate with points, indicating other contributing factors.
• Figure 3: Quest difficulty is strongly associated with completion rates, with easy quests (purple) completed most often and difficult quests (orange) completed least often. Variance in the right tail (epochs 40+) correspond to offering medium quests (pink) with tokens of monetary value.
• Figure 4: Quest cost is strongly associated with completion rates, with cheaper quests (purple) completed most often and more expensive quests (orange) completed least often.
• Figure 5: The implementation of a minimum threshold of tokens for quest completion is associated with an immediate decline in completions for quests that previously ran without thresholds (orange segment compared to the purple segment). The grey lines represent highly completed tasks as a control group.