Many thanks to Haseeb & Tom from Dragonfly, Jai from Royco, DQ from Definitive, Peter from Nascent, Hemanth/Jeff from Goldsky, Derek from Variant, Chudnov from 3Jane, BlockEnthusiast, Kirk of Credit Guild, Steven Becker from UDHC, and others for their generous comments, and discussions that contributed to this post.

A new era of digital loyalty is dawning in Web3, powered by innovative point systems. Since Blur's seminal points program in 2022, teams have rushed to adopt the new incentive primitive and utilize its benefits. With each new point program, projects push the incentive design space a little further, uncovering new reward mechanics and behaviors to incentivize. As we stand in 2024, a diverse ecosystem of point programs has blossomed, each adding unique flavors to the evolving points meta. This rapid evolution has created a rich tapestry of reward mechanics and targeted behaviors, offering unprecedented opportunities for user activation and retention. However, for new builders, navigating the intricacies of “pointenomics” can be daunting. That's about to change.

Informed by dialogues with point issuers and analysis of 20+ point programs, this guide unveils the benefits, criticisms, and practical applications of pointenomics for both new and existing point issuers.

Section 1 provides a primer on points, while Section 2 offers a comprehensive overview of pointenomics in Web3.

Ready to level up your incentive program? Let's dive in.

Section 1: Point Primer

What are points?

At its core, a point is a digital reward unit, valued for its utility or convertibility into tangible benefits - be it exclusive access, product discounts, or direct monetary value. Projects deploy point programs strategically, not just to foster loyalty, but to drive product adoption, amplify network effects, and shape user behavior in ways that accelerate product growth.

Why are points important?

Point programs create a mutually beneficial relationship between brands and users. Companies gain loyalty, growth, and data, while users are rewarded for repeat usage. Well-designed point programs help to drive long-term engagement and deepen emotional connections, both of which are fundamental to product defensibility.

In general, both Web2 & Web3 companies/projects can reap the following benefits from point programs:

1. Marketing - When paired with a referral program, points widen the marketing funnel.

2. Growth - Because points provide value, they lower the effective price of a product/service, allowing point programs to boost the conversion rate within the marketing funnel, leading to growth in core KPIs, such as number of active users.

3. Stickiness/Loyalty - Point programs can improve the stickiness of products, leading to higher user Life Time Value (LTV) and less churn. Studies show loyalty members spend 27% more on average, so product stickiness is achieved when the average LTV exceeds the cost of a loyalty member.

4. GTM timing - Dynamic point programs can help bootstrap products with network effects, such as social media platforms and financial markets. By rewarding early adopters, companies can improve the product’s UX long enough to reach critical mass.

Users also find utility in point programs through:

1. Incentive value - This value can come in the form of discounts, free products, exclusive access & perks, and money.

2. Brand appreciation - Effective loyalty programs go beyond transactional rewards to make customers feel valued and emotionally connected to brands. The pinnacle of loyalty occurs when a customer feels a sense of psychological ownership of a brand.

Section 2: Pointenomics for protocols

Traditional Point Programs

While point programs have been a staple in Web2 for decades, their adoption in Web3 has introduced new dynamics and opportunities. In Web2, we're familiar with airline loyalty programs like Delta SkyMiles and credit card rewards like Chase Ultimate Rewards. These programs have successfully driven customer retention/spending & are valued in the billions of dollars per year — sometimes the loyalty program brings in more money than a company’s core business! Web3, however, has taken the concept of points to new heights.

The Web3 Points Revolution

The first Web3 project to introduce points was Blur in 2022, setting off a chain reaction in the crypto space. Many projects followed suit, with some reaching impressive scales.

For instance, Eigenlayer's point program is currently emitting an annualized $1.8 billion worth of points per year, if its $18b of TVL has a cost of capital of 10% APR. Other notable programs include Ethena, LRT programs (EtherFi, Swell, Kelp), and Blast.

Unique Benefits for Web3 Projects

In addition to the general benefits, Web3 projects gain several unique advantages from point programs:

1. Day-one incentives - Projects can launch point programs much faster than tokens. This allows projects to provide user incentives immediately, driving growth from the outset. Tokens, however, require careful crafting, allocation planning, and timing considerations, which can be challenging to prioritize during a protocol launch. Tokens are products too and mustn't be rushed.

2. Token Conversion Potential - Points can be designed with the possibility of converting to tokens in the future, which increases their implied monetary value. This allows teams to effectively "borrow" liquidity from their future Token Generation Event (TGE) to fund current incentives.

3. Increased Agility - Point programs offer teams the flexibility to fine-tune their TGE timeline, airdrop allocation, and incentive structure without impeding growth. This agility enables more effective go-to-market (GTM) strategies. Moreover, as opposed to governance-ratified incentive programs, teams can adjust point programs freely. While token governance is the idyllic endgame, team agility can be their competitive advantage in the early days.

4. Market Timing - Token launches tend to perform better in bull markets. Point programs allow projects to build momentum and community during bear markets, positioning them for a successful token launch when market conditions improve.

It's worth noting that these benefits aren't limited to pre-TGE scenarios. Projects like Ethena and EtherFi have captured similar benefits for their season 2 point programs, even post-token launch.

Point Program Design

Point programs in Web3 have evolved to include various sophisticated mechanisms, many of which are used in conjunction. The most effective programs have Behaviors, a Base, and Boosts, and some have begun experimenting with Program Rewards. Let’s dive into each.

Program Behaviors

Program behaviors detail user behavior & actions rewarded with points, such as depositing on an L2 or trading on a new AMM. They include:

• Holding unlocked assets - assets where users can freely deposit & withdraw (e.g. LRTs, Pendle YTs, Ethena sUSDe collateral deposits on Morpho)

• Holding Locked assets - assets where users need to wait sometime to withdraw (e.g. Locked Ehtena USDe, native restaking on Eigenlayer, Karak, and Symbiotic)

• Providing Liquidity - Just like unlocked assets, but with the risk of passively selling your deposit asset (e.g. Thruster LP positions staked in Hyperlock)

• Social engagement - Likes, RTs, Comments, and Follows

Program Base

The Program Base includes the most important details of the point program, such as the point emission schedule, timeline, and airdrop size in some instances. Most point programs are broken up into seasons, ranging anywhere from 3-6 months, each with unique base terms.

1. Emission schedule - how often and in what size points accrue to holders

   1. Discrete Rewards - One-off point allocations for specific actions. Useful for kickstarting behavior & marketing. Examples include Blur’s one-off reward for listing an NFT within 14 days, Lyra’s one-off reward for attending a Twitter/X spaces event, and Napier’s rewards for social engagement and referrals.

   2. Continuous Rewards

      • Fixed supply emissions - The total supply of points is fixed within either the entire program (e.g. Hyperliquid) or within an epoch/season (e.g. Morpho*). While both reduce dilution for the user, a fixed program supply offers the least unknowns, whereas the fixed epoch supply allows teams to be more flexible with their emission schedule. Teams generally use a fixed supply emission base to provide additional reassurances to the user.

      • Variable emissions - (e.g. Eigenlayer, all major LRTs, Ethena, etc). The total supply is variable and a function of TVL. Accruing at some point per $ or ETH per day in participation, variable emission schedules dynamically dilute earlier depositors. Although the perceived airdrop payout (in $) attracts new deposits, users who want to eliminate dilution must increase their participation in lockstep with total deposit growth. Teams like this emission schedule because it removes the operational complexity of ensuring fair point distribution to all participants. To reduce dilution for the earliest users and induce urgency, teams will publish a declining accrual rate schedule (e.g. 25 pts/day for July, 20 pts/day for Aug, etc).

2. Timing - how long points will be issued for

   1. Explicit vs vague - most projects give a fixed points program/season duration (e.g. 6 months), but some give a range (e.g. 3-6 months). Teams who want additional flexibility will opt for the vague timeline, even though it could hamper growth.

   2. Conditional - some programs/seasons are designed to stop short if a key milestone is reached before the original end date. If the expected season airdrop allocation is fixed, then this builds urgency for participation. For example, Ethena had a $1b TVL milestone in Season 1 — it was reached in an extraordinary seven weeks.

*while Morpho distributes non-transferrable $MOPRHO tokens as incentives, their operation mimics that of a point issuer.

Program Boost

Program Boosts are the team’s first-to-adjust levers that award users with a higher relative point share for specific, targeted behaviors. Below is a list of different boost mechanisms:

• Quality of Service Boosts - Projects can improve a product’s quality for one user group (e.g. traders) by incentivizing the “quality of service” from another user group (e.g. liquidity providers). For systems where users can differentiate in “service”, such as a Univ3 pool, projects can distribute points as a function of one’s contribution to a product’s UX (e.g. liquidity). Examples include Blur, which rewarded LPs more for quoting closer to NFT floors, and Merkl whose incentive mechanism favors Univ3 LPs that quote competitively and earn more trading fees.

• Referrals - Refer others and earn a share of their points (e.g. 10%). This helps with marketing & incentives acquisition of whales / high volume users. Carries risk of sybils, since they could refer their own addresses. Some projects will require referral codes for app access to generate additional marketing buzz, though the conversion rate to usage will drop. Examples include Ethena and Blackbird.

• Staged Referral Boosts - Extension on the simple referral system. Instead of just earning a share of your referral’s points (ie 1st degree), users will earn a share of their referees’ points (ie 2nd degree). The goal is to encourage users to refer others who are expected to aggressively refer. Carries risk of sybils, since they could refer their own addresses. Examples include Blur and Blast.

• Base Boost - Projects can add an amplification boost to attract & cultivate power usage. The basic idea is that your base point accrual rate increases with underlying usage, thereby earning rewards at a faster rate for the same amount of usage. Non-power users will be under-compensated and will be difficult to attract. For example, Aevo had a Base Volume boost for traders.

• Market Initiation Boosts - Projects will use initiation boosts to attract liquidity and bootstrap a new market before network effects kick in. An initiation boost usually has an expiry, but other thresholds can be explored. For example, some LRT projects (e.g. EtherFi) use a 2x two-week initiation boost for LPs whenever a new Pendle market is initialized.

• Loyalty Boosts - Give extra points to users who pledge allegiance to a product (ie provably use product A and not B). Works especially well for products that rely on network effects; the relative value proposition of a product gets an extra boost when a competitor’s network shrinks. Blur utilized this boost to rapidly pull in market share from OpenSea after launch. This boost works better for NFTs because of their scarcity, especially when owners of a collection typically own one unit each, forcing them to choose allegiance; for fungible tokens, however, users can break up their balance across any number of addresses to avoid undue pressure.

• Random Reward Boosts - Drawing inspiration from Skinner’s Box Experiment, some projects incorporate reward randomness, in either reward size or timing, to attract greater participation and attention. Blur’s care package reward system used a loyalty score for determining rarity *luck* when awarding a care package. While users didn’t know the absolute reward size, they knew the relative amounts between each care package. Similarly, Aevo uses a “Lucky” Volume boost system where any one of a user’s trades may hit a volume boost, amplifying the rewards of said trade; both projects use a tiered boost system, where the highest boost is awarded at the lowest frequency (e.g. 1% chance for a 25x boost).

• Leaderboard Boosts - To encourage competition among users, projects have a leadership boost for being among the top e.g. 100 point earners. This centralizes point ownership among the top power users, but this could lead to higher absolute KPIs as users compete. While it wasn’t marketed much, Blur used this boost in Season 3.

• Native token lockup Boosts - Projects with existing native tokens will give a boost to point earners who demonstrate their commitment as long-term believers. Because this could decrease the outstanding float, teams should expect their token’s volatility to increase. Examples include Ethena, $ENA, and Safe, $SAFE.

• Aggregate TVL Boosts - Projects can incentivize user advocacy and marketing by awarding a point boost based on TVL growth. Examples include 3Jane, whose AMPL-style point program rebases point ownership as a function of TVL, and Overload, who’s made a promise to bump the airdrop allocation when certain TVL milestones are reached.

• Group Boosts - Incentivize social pressure and coordination to gain group-wide boosts. AnimeChain is the first to try this with Squads, a group for sharing boosts with others.

• Locked Boost - In addition to a decaying Program Base schedule, which rewards for past stickiness & is purposed to get users in early, some projects have begun experimenting with boosts that reward future stickiness. Examples include EtherFi’s StakeRank 1- 2x boost in its Season 2 and Hourglass’ liquidity locked 1-4x boost for various term lengths.

Program Rewards

Finally, program rewards are other immediate benefits, in addition to the airdrop expectation. The speculation of a future airdrop drives most of the demand for points, but some projects are experimenting with additional utility for point holders, such as Rainbow Wallet’s ETH rev share for point holders.

While this component is still small, I believe more teams will experiment with point-holder rewards, drawing inspiration from Web2 mechanisms, such as product fee discounts, event access, and other perks.

Putting it all together

The versatility of these building blocks allows for creative point program designs. Once a team defines its goals (in user acquisition, product improvement, marketing, etc), it can compose multiple building blocks in sequence or parallel for maximum effectiveness. Here are examples of creative use cases, outside of vanilla “deposit here” point strategies to boost TVL:

• Ethena's strategy of giving points to USDe holders and boosting yield for sUSDe holders.

• Napier’s strategy of incentivizing social engagement and asset holders of other projects to increase partnerships and boost marketing reach.

• Blur's GTM strategy leveraged various point mechanisms across multiple airdrops to build supply & demand and rapidly gain market share in the NFT marketplace sector at their public launch. With the use of random-boost care packages, their high-level strategy was the following:

  1. User acquisitions - Airdrop 0 rewarded private alpha testers to attract the most active NFT traders

  2. Kickstart supply - Airdrop 1 rewarded new listings from existing NFT traders

  3. Build supply from loyal users - Airdrop 2 was larger than Airdrop 1, rewarded more listings, and gave a boost to loyal listers who moved liquidity from other NFT marketplaces to Blur

  4. Spur demand - Airdrop 3 rewarded competitive bidding to incentivize volume

After a project designs its points program & GTM, it’ll shift its attention to program implementation. Point accrual calculations, data pipelines, price feeds, and point data storage are all components of a point program backend. Once the backend is complete, projects will focus on the consumer-facing implementation, typically a public dashboard showing a user’s point balance as well as a point leaderboard. Many projects build their implementation from scratch, but some have outsourced the work to dev shops and other infra providers.

Next, when a project is ready for their TGE and first airdrop, they’ll explore methods of distributing tokens to their point holders. While airdrop mechanics are not included in this post, teams should consider airdrop tokens vs option form, fixed vs dynamic allocation, linear vs. nonlinear distributions, vesting, lockups, Sybil prevention, and distribution implementation. Those interested in learning more can refer to this post to get up to speed.

Criticisms & Shortcomings of Points

While point programs have proven effective, they're not without criticism. Point programs are an entirely centralized incentive mechanism. Point accrual calculations, data storage, program timelines, and criteria are often opaque and hidden from the user, typically in an offchain database. Therefore, point issuers must prioritize transparency as much as they can to build trust with their user base. If users can’t trust the terms of the point program, they won’t value the points and chase the carrot in haste.

While pre-TGE teams usually can’t unveil the existence of an imminent airdrop or allocation for point holders, due to legal reasons, they can invest in concise communications, prompt disclosure of program adjustments, and quick fixes whenever mistakes occur; EtherFi set a good example for handling calculation mistakes.

Other public criticism, such as ungenerous point holder allocations and Sybil-prone airdrop distributions, unfairly blames point programs, when instead it’s the fault of airdrop planning. Points are simply a way to incentivize with precision and record how much of the “point pie” a user owns. The airdrop terms dictate the how, when, and what of point holders getting paid.

As we saw with Eigenlayer, users were not upset about their point balance. They were upset with how much of the airdrop their points converted into and the undisclosed claim criteria. Earning 5% of TGE for 11 months of deposit, point holders felt like they were the ones being farmed, earning much less than the market average at the time. Moreover, many point holders were unexpectedly geo-blocked from claiming their slice of $EIGEN. While teams have full discretion over the token allocation, they can easily avoid the latter issue in advance by geo-blocking the product. The same can be said for Blast -- users were not upset about their point balance. Blast airdropped 7% to point holders, and required partial 6 mo vesting for the top 1k wallets. For a program under 6 months, this was pretty in line with other airdrop seasons (e.g. Ethena, EtherFi, etc).

While not a criticism of program design, point fatigue is a growing issue in the ecosystem, as seen in public forums and private discussions with DeFi whales. It takes time & effort to understand the value of a point. For every new program, users need to build an initial model and constantly update its assumptions to ensure they’re earning the best return on their capital or behavior. As new point programs flood the ecosystem, users struggle to keep up, leading to fatigue and lethargic migration between point programs. For example, imagine you have two options, 1000 units/day of Point A vs 2m units/day of Point B — which one is more valuable? Is the more valuable one still valuable enough to risk one's capital? The answers are not immediately clear. Projects that can’t immediately differentiate their point program from all others will have points with less influential power.

A final important, and rather insidious, side effect of point systems is their propensity to mask Product Market Fit (PMF). Points are great bootstrapping mechanisms, but they risk hiding organic interest that’s instrumental in finding PMF. Even after PMF is validated, teams need to build enough organic traction to find sustainability in their product/service before tightening their incentives. Mason Nystrom of Variant has called this the “Hot Start Problem”. For pre-PMF teams, I recommend introducing points after validating PMF in a closed alpha program. Post-PMF teams have it a little trickier, but Mason recommends teams “take extra steps to ensure that token rewards are going towards organic usage and driving important metrics like engagement and retention.”

Future Outlook

Looking ahead, I anticipate that point programs will evolve to address the most pressing issues, such as program transparency and point fatigue.

To bring greater transparency in total point supply, distribution logic, and accrual history, future point programs, or parts thereof, will exist onchain. Examples of onchain point implementations include 3Jane’s AMPLOL and Frax’s FXLT points. Another point software provider is Stack, which builds infra to manage onchain point programs.

Addressing point fatigue presents a more complex challenge. While discussions in private chats & CT often focus on differentiating program designs, the key to reducing fatigue likely lies in empowering users to quickly and confidently assess point valuations. This capability would significantly ease the comparison between various point opportunities, making participation decisions more straightforward and less overwhelming. While not part of point program design, a secondary market, such as Whales Market, can help users price points and reduce fatigue, though it’s not liquid enough to support most point exit strategies. As these markets mature, however, they'll likely become invaluable for price discovery, offering exit strategies, and creating a more dynamic point economy.

Conclusion

Points have emerged as a powerful tool in the Web3 ecosystem, offering benefits that extend beyond traditional loyalty programs. They enable projects to reward loyal power users, bootstrap network effects, and fine-tune their go-to-market strategies in more predictable ways. This leads to more effective product development and, ultimately, drives value to end users.

As the space matures, I expect to see further innovation in point program design and implementation. The key to success will lie in balancing transparency with flexibility, and in aligning point programs closely with overall project goals and user needs.

For builders and projects in the Web3 space, understanding and leveraging the power of well-designed point programs can be a crucial factor in achieving sustainable growth. As we move forward, points are likely to remain a fundamental component of crypto incentive structures, continuing to shape the landscape of DeFi and beyond.

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If you’re a prospective/existing point issuer or point program designer eager to jam on different mechanisms and GTM strategies, I’d love to hear from you!