This is the second part in a three-part series on data analytics in Web2 vs. Web3, written by Matteo Titta for Third Academy. In the first part, we analyzed the challenges faced by Web3 operators who need to learn from customer data.
Web3 models — including NFTs and DeFi, and DAOs — continue to gain traction despite the bear market. As teams work to grow these products, it's important to track the right metrics so they can make informed strategic decisions.
In this blog post, we’ll cover a framework to track product performance based on three main outcomes — acquisition, retention, and monetization. We'll then look at the key metrics for these categories across main Web3 models, like NFTs, DeFi, and DAOs.
1. The Analytics of Growth: Acquisition, Retention, and Monetization
To develop a successful analytics strategy, metrics across acquisition, retention, and monetization are key. These three categories are lagging indicators that provide valuable insights into how effectively the product reaches new customers, retains its user base, and monetizes its features. Let’s look at each more closely.
Customer acquisition refers to the process of attracting and engaging new customers — marketing, advertising, and outreach with the goal of driving new customers to the website, creating an account, and making a purchase. Among the must-track acquisition metrics, there are typically:
- Website visitors: number of potential new users visiting the website.
- Signups: number of customers who create accounts.
- Activations: number of signed up customers who experience core product value (eg. reach the so-called ‘aha moment’).
- Cost Per Acquisition: dollars needed to acquire and activate a new account.
- Time-to-Activation: number of days between signup and activation.
Retention & engagement
Retention and engagement are the processes of keeping existing customers actively using the product over time, by nurturing them with regular updates, new features, and support to ensure they continue to derive value from it. Retention is generally hard to define and track without a solid method. However, every team should track these basic metrics in this category.
- Retained Customers: number or percent of customers who come back to the product, perform a core action, and eventually build a habit around it. Retention determines the breadth of how many customers are active over a specific period of time.
- Engagement: if retention measures product breadth, then engagement signifies depth — how much, time or value, customers are spending on the product over a period of time. Engagement can be measured by:
- Active Customers: number of customers who perform a core action during a specific amount of time (eg. daily, weekly, or monthly active customers).
- Intensity: average time spent by each active customer on the product.
- Frequency: number of times customers come back to the product and reach an active state.
- Churned Customers: number of customers who stop using the product and eventually become dormant — the opposite of retention.
Monetization refers to generating revenue from customers for access to features, with the goal of creating a sustainable set of revenue streams that supports ongoing product growth. To track monetization, growth teams should look at:
- Total Revenue: this can take various forms based on the business model:
- Recurring Revenue: regular income from subscriptions, typical of SaaS (eg. MRR, Monthly Recurring Revenue).
- Gross Merchandising Value (GMV): the total value of goods and services sold on the product before costs and expense, typical of online marketplaces.
- Average Basket Size: the average value of a transaction made on the product, like an order on a marketplace, or the average contract value in SaaS.
- Payback Period: number of days, weeks, or months to make back the cost per acquisition.
- Take Rate: percentage of the transaction retained by the product, typical of transactional marketplaces.
- ARPPU: average revenue generated per paying user over a specific period of time.
- Revenue Retention: amount of revenue retained over time from paying customers at the net of churned customers.
These metrics are not exhaustive and might change for different products and models, but are designed to keep you focused on the main outcomes of a product — acquiring, retaining, and sustainably monetizing customers.
By using this framework, teams can identify areas for improvement and grow their products.
2. Unpacking the Metrics of Web3 Models: DeFi dApps, NFTs, and DAOs
Equipped with a first principles, outcome-based approach to analytics, let’s now apply it to unpack innovative Web3 models. In this article, we’ll focus on DeFi dApps, NFTs and DAOs.
DeFi dApps (Decentralized finance applications) are blockchain-based applications that enable users to access financial services, such as lending, borrowing, and trading, in a decentralized and trustless manner. Notable DeFi names include UniSwap, Aave, MakerDAO, and Lido Finance. These dApps are built on blockchain platforms, such as Ethereum, and use smart contracts to automate the terms of each transaction.
That’s why dApps have very similar engagement and monetization models to Web2 SaaS-enabled marketplaces, except for the fact that where Web2 models focus on tracking individual customer accounts, Web3 ones track wallets. This causes the identity fragmentation and attribution challenges we analyzed in the previous post of this series.
Let’s take Robinhood (Web2) and UniSwap (Web3) as an example and apply our analytics framework to compare the two.
Other than focusing on wallets vs. accounts, and adding protocol-level TVL as an additional measure of consumer confidence in the product, there are no great differences between Web2 marketplaces and Web3 DeFi models from an analytics standpoint.
NFT projects (Non-Fungible Tokens) are digital assets that are unique, scarce, and programmable. They signify ownership of digital items, such as art, collectibles, or in-game items, and may grant access to physical or digital items, experiences, and more.
NFT projects are a completely different beast from existing models. In this article, we’ll focus on its main category, digital collectibles. The most popular collections include Crypto Punks, BAYC, Azuki, Doodles, and NOUNS, where NFTs represent virtual trading cards that provide access to token-gated communities, benefits, and experiences.
These NFTs are designed by artists and creators, ‘packaged’ in collections by smart contract developers, and then minted (aka ‘created’ on the blockchain) directly by collectors at a pre-determined mint price. NFT creators can then give NFT owners the ability to mint additional collections — called companion NFTs — so collectors can expand their collection and make more NFTs interact among each other.
Because NFT models constitute a hybrid model between digital products and community, things get a bit more complex here. In acquisition, it’s important to track the following:
- NFT owners constitute new signups, as one owner can own more than one NFT.
- Every time a (companion) NFT is minted, there is a new activation.
- To measure time-to-activation, it’s important not only to track days-to-mint, but also the overall time needed for the collection to sell-out. This is fairly important if your strategy is to drop the overall collection all at once, as most projects hope to sell out on the first day.
In retention and engagement, we need to distinguish between two core use cases:
- NFT traders: these people are interested in continuously trading NFTs from multiple collections — so we can measure engagement and activity by understanding how many people are trading every day, the number of sales per day, and the overall trading volume.
- NFT community members: these people are long-term holders of the NFT as they are keen to stay within the community — here, we can measure retention by tracking the percent of holders, their contribution in the community (eg. how many messages they send in Discord), how many NFT benefits they redeem (eg. how many token-gated events they participate in), and how many governance proposals they submit (if that’s part of the NFT community). In this segment, it’s important to also understand the distribution of ownership of the collection to gauge how concentrated ownership is within the collection, as this might skew decision-making power in governance and make the community exclusionary.
In monetization, it’s important to track:
- Total revenue from both NFT mints and trades, based on the royalty percentage (the equivalent of the marketplace take rate) embedded in the smart contract, which defines where fees will go (eg. to the creators, designers, etc.).
- The collection market cap, which gives an overall value for how much the collection is worth, given its average sales price. Floor and ceiling price are also important as they determine how exclusive the NFT collection is and its barriers to enter the related community.
- The community treasury (also based on the specific royalty percentage allocated to it), which determines how much crypto the community has gathered to fund their initiatives, like additional mints, events, partnerships, and experiences.
DAOs (Decentralized Autonomous Organizations) are networks of people that come together based on ownership of crypto tokens or NFTs and interact directly, without the need for central authority or intermediaries. These networks are owned and controlled by their users, who can participate in governance and decision-making to drive their specific community mission. DAOs may be used to create and manage a wide range of applications, including DeFi dApps, NFT collections, and community. Notable examples are UniSwap DAO, where $UNI token holders vote on which new features to build on UniSwap, or FriendsWithBenefits, a community of $FWB token holders who organize creator-focused events and experiences.
DAOs are still at the very early-stages of their potential, but their acquisition and engagement model is very similar to Web2 communities. Also, because you can become a member of a DAO by owning a token or NFT, there are many crossovers with both NFT and DeFi projects.
Overall, the specific metrics that teams choose to track will depend on the nature of their product and the goals and objectives of their project.
However, by using this framework and tracking metrics across acquisition, retention, and monetization, teams can analyze the main outcomes any tech product should drive — that is, acquiring, retaining and monetizing its customers. So, whether you are building DeFi dApps, NFT collections, or DAOs, you can apply this framework to work back to your metrics and make informed decisions about product and marketing strategy.
In the next article of this series, we’ll cover emerging tools helping teams track these metrics to help inform their decisions.
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