Points Systems: The Good, The Bad, and How To Improve Them

Gamification has been a staple in the consumer industry forever. Whether XP, badges, or monetary rewards, gamified elements are used to nudge users into desired behaviors. Duolingo employs a streak mechanic, daily challenges, and chests filled with bonuses like gems to keep language learners coming back daily. Airlines offer miles to reward frequent travelers for their loyalty.

Of course, crypto has caught up, offering points to early adopters - for providing TVL, trading, or playing web3 games. In short, users accumulate points for doing X, Y or Z, which at TGE convert into tokens. Oh, if it only were that simple!

What once started as a more transparent and meritocratic version of airdrops turned into a speculative attention economy of heavily inflated points, diluted participants, points on top of points, and a game of protocols farming the farmers through opaque systems.

In this piece, we’ll dive into the good side of points, what’s wrong with the current points meta, and how to improve it going forward.

Reading glasses on … yeah, it’s research time!

The current points systems were born in DeFi and were seen as a way to solve the trifecta of problems that founders were coming up against: 

• Attracting TVL in the early months of their protocol’s life before they can offer any meaningful rewards.

• Rewarding users for their participation and ongoing commitment.

• Minimizing mercenary liquidity flying out en masse post TGE.

By offering incentives, point systems aimed to recognise and compensate those who contributed to the success of innovative projects, during the very fragile early development stage.

At their core, modern points systems are frameworks designed to incentivise a certain desired user actions. Academics call this “behavioral economics” and it’s an actual field of study. These actions can be:

• Providing liquidity

• Staking or locking tokens

• Trading

• In-game activity

• Repeated logins

• Referrals

• Token locks

Once a protocol knows what it needs from its users, it can quantify and incentivize this behavior. Back in the day, airdrops were, in good part, allocated semi-randomly among wallets that were active within a protocol. The fine quantifiable fine-tuning that took that semi-rando to deterministic is essentially what points systems are.

And then the game got really greedy really fast.

The current points meta often makes use of boost multipliers, whereby users who perform a greater magnitude of desirable actions receive x times more points applied to their respective base rate. For example, users providing liquidity for a certain volume of tokens, for a certain length of time might receive 3-5 times more points, depending on how early they are to the party.

It didn’t take long for the whole points meta to become a casino, where large whales or funds want to dilute others the most by stacking boosts negotiated in OTC deals that retail would never have access to. All of this hustling and bustling over non-transferrable magic points that might turn into a decent airdrop.

However, not all is bad when it comes to points. Protocols can now much more effectively allocate their initial vulnerable capital to attracting support and interest. This has allowed LRTs and other areas of DeFi to be able to raise funds without depending solely on private investors for example. 

Ok, now let’s dissect the pros and the cons of token-centric incentive architectures.

Separating incentives from sell pressure

Incentives are required in the beginning to bootstrap network effects. But network effects take time to materialize and to create network value. Value that can then be captured by a token, making it more valuable. 

There’s a time mismatch between token emissions as incentives (sell pressure) and network value (token demand). As users do not deem the token valuable, it’s a race to the bottom who can dump first. As the token price decreases, incentives become unattractive. This game theory problem is arguably the main reason why most projects see that large red candle of death at launch before price starts to reach its organic equilibrium.

Points bridge that time gap by incentivizing early users with an IOU for future tokens, which can be released once sufficient network value has been created. This way, teams can better match token supply with demand.

Source: Inspired by https://insights.deribit.com/market-research/why-i-have-changed-my-mind-on-tokens/

Broader design space

Points are one abstraction layer removed from tokens. That gives teams more flexibility. They can collect data on user behavior to adjust points rewards and, for example, dilute non-desired users over time. Or they can retroactively determine the size of the token airdrop based on the performance of the points campaign to control for customer acquisition costs.

Of course, it’s important to also manage user expectations. Hiding details to maximize flexibility comes with a tradeoff. Information, for instance about airdrop size, makes points systems more attractive to users. And dissatisfied users will never come back after they claimed and dumped their airdrop. Points are designed on a spectrum between flexibility (for teams) and transparency (for users).

Ultimately, points should provide users with more transparency than retroactive airdrops, allowing them to see how different actions are rewarded. However, teams have to be aware that known actions are easier to game than unknown.

As we’ll discuss in a second, the current meta has swung the pendulum far to the protocols side, lacking transparency for users. For example, teams add extra conditions retroactively before the airdrop, making the points-to-tokens conversion incomprehensible for the average user.

As with any idea, the added sophistication offered to the average user has created purposely complex and vague reward structures. Many point systems have been designed to be inflationary, confusing and lack key elements of transparency, notably how points received at one time actually translate into value at a later date. Much of the following information is usually not known to most users::

• How many points will there be in total? How will points be distributed over time (e.g. new pool launches with 10x boost mid-season)?

• How big will the token reward pool be?

• Will there be additional conditions that change the logic of token distribution and make it non-deterministic.

This has led to points evolving from being a tool where people were more fairly rewarded for early adoption to one where teams seek to hype up their protocol with notional points, boosts and the promise of big, future rewards but without having to really promise anything. The farmers are getting f… farmed.

Protocols want to attract the most amount of TVL and users,  and the vast majority aren’t shy about promising ludicrous boosts to funds and DeFi integrations. This basically ping-pongs the small degen’s position and makes the ROI on the initial deposit or activity drastically lower.

One might think this is an inflation issue. You might be subjected to a slight feeling of tomfoolery to hear that inflation isn’t technically the problem. Dilution is. An airdrop’s amount, considering it fixed, doesn’t move. Points translate into a percentage allocation of that same airdrop. Whether a user gets their 100 $DANK tokens for having held 10,000 points or 10^23 points is irrelevant. What does matter, is by how much their position has been diluted. 

Usually, protocols only give out one form of points for all user activities. That led to situations where the same points are awarded for in-app activity, referrals, social engagement and other types of more or less valuable behavior.

The challenge here becomes that these actions are mainly valuable if done by the same user. For instance, someone uses the product, is highly satisfied, and then recommends it to friends. The recommendation works because it’s authentic, not due to a monetary incentive. Most points systems fail to capture that context and award points for actions independently from one another.

Furthermore, the more actions are rewarded with the same form of points, the riskier. When one rewarded action can be exploited, it has ripple effects throughout the whole system. For example, social engagement can be easily botted. This results in an ineffective allocation of tokens as real users get diluted.

An analysis of the nominal value of a protocol’s points versus its value after inflation and TVL adjustments shows a marked dilution in almost all cases. Even in the case of Renzo, which has had somewhat limited dilution, almost half of their points value has been shaved off. In the worst case, in this instance Etherfi S2, almost 90% of the points’ value has been diluted. If that was a token, it’s unlikely many would flock to buy it.

The main drivers of usage are, and have been for a long time, financial incentives. Points weren’t able to solve this, they just added another layer of speculation. That makes retaining users after incentives dry up a challenge. Points have become the product.

Of course, teams are aware of all of this. They know that users won’t stick around, that sybil attackers will try to get a majority of the airdrop, but they have to accept it as the crypto industry as a whole still likes to look at vanity metrics. Want a CEX listing? Get your follower number up!

In a struggle to keep the token from getting dumped into oblivion, teams reduce transparency to allocate tokens as best as possible based on collected data.

This concludes in a race to the bottom where real users feel like they’re getting farmed and lose interest in points. Only sybil attackers remain.

This wraps up part 1 of our article, diving into the basics, the pros, and the cons of points systems currently live on the market. In part 2, we will provide suggestions on how to improve points and better allocate incentives while providing users with more transparency.

Absinthe Labs is building the first incentives affiliate network, and our first product is a no-code points-as-a-service platform. In addition to rewarding on-chain actions, it makes tracking campaigns easy by aggregating points from questing platforms like Galxe and Layer3 into the project's native points. Absinthe also allows for easy allocating to communities such as token holders, stakers, NFT holders, and Discord roles.