Um, no. That’s not how it works. Loyalty programs have long been viewed as a one-size-fits-all fix for deeper growth and retention issues. However, it’s far more complex than simply “launching points” and expecting everything to fall into place.

However, if you iterate on your constructions properly, use the right tools, and work with partners that understand how to interpret the right metrics, you can achieve astounding results — not too far off from the ridiculous description I started with.

At Absinthe, we take a data-first approach. Setting up loyalty programs requires decision-makers to choose a few key performance metrics (KPIs) to track. An improvement in these KPIs directly translates to product success, indicating that the loyalty program is on the right track. Below are some essential metrics that generalize well to most of our customers, alongside some web3-specific examples.

1. TTV — Time to Value

Definition: Measures how long it takes for a user to recognize your product’s value. ‘Value’ is subjective and defined by the client or promotional event.

Goal: Minimize TTV by setting clear user expectations for achievable milestones within a set timeframe.

In a web3 loyalty program, TTV might track how long it takes for a new wallet holder to hold their first token. Suppose you launch a program where new users need to complete specific on-chain tasks to receive their first reward. If it takes too long or feels complicated, users may churn before realizing any benefit. By minimizing TTV, such as by offering low-barrier, quick-to-earn incentives (like gas rebates or free NFTs), users can experience instant gratification, pushing them further into the ecosystem.

2. UAR — User Activation Rate

Definition: Percentage of users who achieve predetermined activation milestones within a set timeframe. Critical for predicting long-term retention.

Example Formula: Divide the number of users who meet these milestones by the total users during the period, then multiply by 100.

In web3, milestones could include actions such as connecting a wallet, completing a transaction, staking tokens, or participating in a DAO vote. For example, a project could define “activation” as completing a specific number of transactions in a DeFi or NFT platform. By tracking UAR, you can measure how quickly users are becoming active participants within your platform, which is essential for predicting long-term loyalty. This is a prime candidate for being a north star KPI.

3. FAR — Feature Adoption Rate

Definition: Measures the percentage of your user base that is using a particular points-earning condition or feature.

Imagine you launch a staking feature within your loyalty program that rewards users with points for staking their governance tokens. The FAR will tell you how many users are actively staking tokens to earn these points. If adoption is low, it could indicate that the staking rewards aren’t perceived as valuable, or the process might be too complex. Monitoring FAR allows you to adjust features, making them more accessible or rewarding to improve adoption.

4. PAR — Product Adoption Rate

Definition: Measures how frequently and effectively customers are using your product.

Example Formula: Divide the number of new active users by the total sign-ups, then multiply by 100.

This might measure how many users are regularly interacting with your dApp or protocol after signing up. If a loyalty program is integrated with multiple platforms (e.g., DeFi protocols within an aggregator) PAR would tell you how well users are adopting and engaging with the product beyond the initial sign-up. High PAR could mean that users are getting enough value from the product to continue using it regularly, perhaps leveraging cross-chain rewards or participating in governance activities. You can track the PAR over time, and use this as a lagging proxy of the effectiveness of your communication and marketing efforts.

5. PUR — Points Utilization Rate

Definition: Measures how many of the total possible points users could earn are actually being earned.

If you have a daily limit on the number of points one can earn, PUR could track the percentage of points actually being earned. Users might earn points for completing actions like attending virtual events, participating in DAO governance, or engaging in social campaigns on platforms like Galxe or Zealy. If the PUR is low, users might be unaware of the available activities or rewards, or they might find the process too tedious. Increasing PUR involves better communication of rewards, simplifying processes, or creating more engaging incentivized behaviors. However keeping a controlled PUR allows you to striate your user base into power users, farmers and regular users. Leaving some breathing room with a medium PUR allows the power users to actually earn a significant lead in the loyalty program — assuming that this is your intended target behavior.

In summary, setting up points-based loyalty programs doesn’t guarantee success without a strategic and data-driven approach. These metrics offer insights into the actual performance and adoption of your program. Whether you’re operating in web2 or web3, focusing on these KPIs will allow you to tailor your program for maximum impact, ensuring that you’re genuinely driving user growth, engagement, and retention.