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[TL;DR]
- In blockchain, users are identified by wallet addresses and token incentives are involved, which makes it difficult to apply existing metrics like CAC and LTV as-is.
- Depending on the project type (L1/L2, protocol, wallet, game), the core metrics you should track are completely different, and you must choose the right channels and strategies for each growth stage.
- Quantitative metrics alone are not enough: you need to combine them with qualitative analysis such as community sentiment and user feedback, and distinguish between incentive-driven activity, bot traffic, and real growth.
1. The Basics of Crypto Growth Metrics
1.1 Why You Can’t Reuse Web2 Metrics As-Is
In traditional web service marketing, there are already well-tested methodologies. Metrics like the cost to acquire a single user, the value that user will bring over their lifecycle, and conversion rates are widely shared across industries, and most marketers use these numbers to judge the state of their product. But in blockchain projects, these familiar formulas don’t work properly.
First of all, the very concept of a “user” is different. In conventional services, one account registered with an email or phone number usually means one user. In blockchain, users are identified by wallet addresses. The problem is that a single person can use multiple wallets for different purposes, and exchange wallets can be shared by many people through one address. In short, it’s hard to map wallet addresses one-to-one to actual users.
The way data is collected is also fundamentally different. In traditional web environments, you could track how users arrived and what they clicked using cookies or login records. In blockchain, the path from website visit to wallet connection is broken, making it difficult to understand which channel brought the user in. On the other hand, there is a unique advantage: all on-chain transaction records are public, so you can analyze even your competitors’ user behavior patterns.
Above all, once tokens are involved, everything becomes more complex. It’s hard to tell whether users who flock in for an airdrop are genuinely interested in the product or solely chasing rewards. It’s common to see metrics grow explosively for a while and then drop off once the incentive program ends. If you look only at the numbers in this situation using existing methods, it’s easy to misjudge and think the product has achieved product–market fit.
1.2 Core Metrics by Project Type
The metrics you should track differ completely depending on the type of blockchain project. The performance metrics watched by teams building blockchain infrastructure and those watched by DeFi services running on top are not even comparable to begin with, because the nature of the value they create is different.
For Layer 1 and Layer 2 blockchain infrastructure, ecosystem growth is the primary goal. The key metrics are how many addresses are active each month (MAA), and how many applications are being built on top. These two metrics only have meaning when they grow together. If there are many users but few apps, it may mean traffic is concentrated in a single popular app or that activity is bot-driven. Conversely, if there are many apps but few users, it means real adoption is not happening. In this context, the marketing lead is not just promoting a single protocol but acting as the engine that activates the entire ecosystem.
Protocol projects focus on the number of users, transaction volume, and total assets under management. TVL (Total Value Locked) is the value of assets deposited in smart contracts, converted into dollars, and TVS (Total Value Secured) represents the total value of assets secured by the protocol. TVL is a controversial metric in many ways, but when combined with other numbers, it’s still useful for getting a sense of the project’s overall state. One founder explained that they calculate the grant cost required to secure “active TVL,” and then measure the fees and asset scale they actually gained relative to that investment.
In infrastructure and developer tools, metrics are tracked in a way similar to typical software companies. Developer platforms like Alchemy track how customers and revenue grow by product, following a classic SaaS model. The important metrics here are the rate of recurring revenue retained from existing customers (GRR) and revenue growth achieved through upsells to the existing customer base (NRR). The former shows how “sticky” your product is, and the latter shows the potential to grow revenue within the existing customer relationships.
Wallet and game projects use more intuitive metrics. They look at how many addresses are active daily (DAA), how many of those addresses actually generate revenue-producing transactions (DTU), and the average revenue per user (ARPU). If there is a native token, they also look at token price and holder distribution, again depending on their goals. Whether it is better to have many small holders or a few large ones depends on the project’s stage and strategy.
2. Decomposing the Core Metrics
2.1 CAC: Redefining Customer Acquisition Cost
Customer Acquisition Cost (CAC) refers to the total cost of acquiring one user. In traditional businesses, this concept is relatively clear, but in blockchain you must first rethink what counts as “cost” and how you define “customer.”
Blended CAC is the total acquisition cost divided by the number of new customers. It shows how much you spent per customer on average across all channels. The problem is that it does not distinguish between users acquired through paid marketing and those acquired organically. As a result, it’s hard to know which marketing strategy actually worked.
By contrast, paid CAC is calculated only for customers acquired via paid marketing. Many teams spend budget indiscriminately without measuring real performance, but paid CAC makes it very clear whether a specific campaign was effective.
In blockchain, the scope of “cost” is wider than in traditional settings. Advertising expenses, sponsorships, and marketing content production are just the basics; token rewards for quests on platforms like Galxe or Layer3, as well as airdrops to specific wallet addresses, all count as costs. Early-stage blockchain projects often focus on token rewards but fail to understand which tactics are actually effective.
The definition of “customer” also needs to be reset. In blockchain, a new wallet address that has executed a transaction on your protocol can be considered a customer. For an infrastructure project, developers using your platform may be your customers. Ultimately, each project must clearly define what a customer is based on the value it provides, and then calculate CAC accordingly.
Blockchain’s unique incentive structure makes CAC calculation even more complicated. If many users come in via airdrops or points programs, CAC may appear low in the short term, but if most of them leave once the rewards end, the true cost of acquiring real customers is much higher. Therefore, when including token incentives as costs, you must consider long-term retention to accurately understand CAC.
2.2 LTV: Reframing Around Wallets
Lifetime Value (LTV) is the present value of the net future profit a customer will generate over the course of their relationship with you. It measures how long a customer stays and how much value they create during that time. It is already a complex concept, and in blockchain it becomes even harder to calculate because the “customer” is an anonymous wallet address.
Traditional LTV calculations assume a clear customer ID and repeat purchase patterns. In blockchain, a single person can use multiple wallets with different purposes. They may have one wallet for main asset storage, another for DeFi, and yet another for NFT trading. In such a situation, calculating the LTV of a single wallet doesn’t necessarily reflect the real value of the underlying user.
For DeFi protocols, LTV can be interpreted differently. You can calculate it by combining the asset amount a wallet has deposited into the protocol (its contribution to TVL), the fees generated from that, and the duration of its activity. TVL shows “how much is here now,” while LTV shows “how much value this wallet will contribute to the protocol over its lifecycle.” Of course, if a user participates through multiple wallets, the actual LTV is higher than what any single wallet captures.
The multi-wallet environment is the biggest challenge in measuring LTV. Recently, as on-chain analytics tools advance, technologies for linking multiple wallets to the same user have emerged. They cluster wallets by analyzing trading patterns, fund flows, and activity time windows. Platforms like Nansen label wallets across multiple chains to enable more accurate analysis. But these methods are still not perfect, and privacy-conscious users try to evade such tracking.
2.3 LTV:CAC Ratio and the Lack of Benchmarks
The LTV:CAC ratio compares the cost of acquiring customers with the value those customers will bring. It’s a key metric for assessing the efficiency of new customer acquisition and the payback potential of your investments. In traditional SaaS, a 3:1 ratio is considered a good benchmark: you earn three times what you spend to acquire a customer, leaving enough margin to reinvest in growth.
In blockchain, there is no such clear benchmark yet. The industry is not mature enough, and project types are too diverse for a single standard to apply. The business models of L1 blockchains, DeFi protocols, and games are all fundamentally different, so you can’t evaluate them with the same yardstick. For now, each project must set its own target ratio and track how it changes over time.
Once token incentives are involved, interpreting this ratio becomes even trickier. If an airdrop or points program brings in a large number of users quickly, CAC may look low and LTV may appear high. But if most of these users leave once the rewards end, the real LTV is much lower. The ideal scenario is to use incentives to bring users in and let them experience the product, then retain them through the product’s intrinsic value. In that case, over time CAC falls and LTV rises, improving the ratio.
Ultimately, when looking at the LTV:CAC ratio, the trend matters more than the absolute number. If the ratio is improving, it may indicate that the team is moving toward product–market fit. If the ratio worsens even as you increase incentives, it suggests that fundamental product improvements are needed. Blockchain projects must interpret this ratio together with other metrics—especially organic growth rate and retention—to make sound decisions.
3. Crypto Growth Funnel Strategy
3.1 Awareness
The first stage of the funnel is making people aware that your project exists. Regardless of whether it’s blockchain or not, building brand awareness is the starting point of all marketing. At this stage, CAC measurement begins, and reach also becomes an important metric. Reach is the number of unique users who have seen your content, and it’s useful for assessing the impact of broad marketing channels like media coverage and PR.
The challenge here is distinguishing between fleeting attention and genuine interest. You may attract an influx of people during a brief moment of hype, but you need to know how many of them are actually willing to use the product. In blockchain projects, curiosity alone is not enough. You need people who are willing to connect a wallet and move assets, and there are various channels to reach them.
Many projects start with influencer marketing. This comes with plenty of pitfalls. Paying random influencers simply because they have many followers is mostly ineffective. If the influencer has no real connection to the project, neither will their followers. It’s more important to find influencers whose values align with the project. It can also be effective to work with micro-influencers who have small but loyal audiences, or to leverage people inside the team who naturally build influence over time.
If influencer marketing is challenging, you might consider paid advertising, but the options are limited in blockchain. Major platforms like Google and Meta have ambiguous and frequently changing crypto ad policies, and many blockchain companies can’t run ads at all. Even when they can, there’s a trust issue within the community. Scammers often use similar ad formats to lure people to malicious sites, so even legitimate project ads are viewed with suspicion. That’s why many teams turn to alternative channels like X, LinkedIn, Reddit, TikTok, and the Apple App Store. There are also crypto-native channels like Brave browser ads, spindle ads inside apps like Coinbase or Base, and mini-apps or sponsored posts on Farcaster. Recently, some teams have begun optimizing to appear in AI search results as well.
Teams that hit the limitations of paid channels often shift focus to referral marketing. The basic structure is similar to traditional referral programs, but in blockchain it can be much more powerful. Someone gets rewarded when a new user signs up through their link, but the difference is that the reward is sent on-chain immediately and is verifiable. This makes the incentive structure transparent and the entire process smoother. Projects like Blackbird show how on-chain referrals can become not just one-off acquisition campaigns, but compounding loyalty programs and community growth engines.
When referral programs work well, they naturally evolve into word-of-mouth, which is arguably the most powerful growth driver in crypto. For consumer products, this happens when users enjoy the product, find value in it, and recommend it to others. For infrastructure projects, existing customers and developers become your advocates. The simplest way to measure word-of-mouth growth is to track Net Promoter Score (NPS) at each touchpoint, or to ask new users directly who referred them. Referrals do not end at the conversion stage—they form a reverse funnel where converted users bring new prospects into the top of the funnel. Early users become evangelists, bring more people into the network, and get rewarded for their contributions, spinning the flywheel.
What accelerates this growth flywheel is token-driven network effects. Tokens are the most effective way to bring users, developers, and liquidity into marketplaces struggling with cold-start problems. This is not about speculation per se. When token prices rise, new users want to join “something that is growing.” Developers also pay attention. Price appreciation signals an active community and real demand, making it more attractive to build there.
But it’s equally important to verify whether the users coming in through all these channels are real. Distinguishing between genuine users and bots is a challenge in every industry, but blockchain has unique identity verification methods. Human-proof systems and zero-knowledge proof–based verification help differentiate real users from bots and airdrop farmers. These tools are not just for defending against Sybil attacks during airdrops. They can also be used to accurately understand your real user base, develop retention strategies, and evaluate which channels bring in high-quality users.
3.2 Consideration
The consideration stage is when prospective customers become interested in a product and evaluate it while comparing alternatives. In blockchain, this stage is particularly important. Whether buying a token or ordering a hardware wallet, every decision requires a substantial amount of learning. Since blockchain is still relatively new and complex, providing the right level of information to both users and developers has a decisive impact.
Educational content must go beyond listing product features and benefits. It should explain how the product works, how security is handled, how assets are stored, how community and treasury governance work, and how the token economics are structured. Developers need deep technical documentation and tutorials, while general users need explanations that they can understand before moving real funds between wallets or across chains. From Coinbase to Alchemy, many companies invest in educational content for both consumers and developers for exactly this reason.
There are many ways to deliver educational content. You can educate users through email campaigns at key steps like sign-up or purchase, or use in-product prompts and tooltips to provide real-time guidance. Interactive onboarding that lets users experience the product directly, or letting them try functions on a testnet before moving real assets, can also be effective. Recently, teams have begun optimizing educational content for LLMs, since having your content surface in search or AI answers itself becomes a powerful education channel.
Equally important is reducing onboarding friction. Traditionally, getting started with blockchain required creating a wallet, writing down a seed phrase, buying assets on an exchange, and moving them—an inherently complex process. Many people drop off here. Today, social login wallets and WaaS solutions that create wallets without seed phrases are lowering the barriers to entry.
Successful teams do not judge interest solely by clicks or downloads. They look at intermediate actions that signal trust and intent, such as joining a waitlist with a wallet, or depositing a small amount of funds for testing features. These signals help distinguish between mere curiosity and serious interest. Of course, to know whether these efforts are working, you need to track them by channel. Each channel has its own metrics, and ultimately, you must confirm whether the engagement led to actual conversions.
3.3 Conversion
Conversion is the stage where you take the attention of potential users, engage them, provide information, and finally get them to act. It’s the moment a user completes a defined goal action. In traditional marketing, this can mean a purchase, demo request, or meeting request with sales. In blockchain, things are similar: wallet downloads, token purchases, or deploying code on a platform can all count as conversions.
The definition will vary by product and goal, but it’s crucial to define what “conversion” means. Only then can you choose the right measurement methods. Tracking conversion by marketing channel is also essential. For example, if you know how many wallet downloads came from an offline event, you can identify which channels drive real outcomes and optimize budget allocation and messaging.
Accurate conversion tracking heavily depends on attribution, which is tricky in blockchain. It is still hard to fully track user journeys that begin off-chain (e.g., on a website or social media) and end with on-chain actions, or vice versa. Traditional web tracking tools like Google Tag Manager can track website conversions, and wallet-targeting tools like Addressable help bridge the gap. They allow you to track campaign performance across journeys that start on websites or Web2 ads and end in on-chain behaviors.
The problem is that user journeys are rarely linear. Someone might see a post on X, attend an offline event, and then only make their first transaction much later. Historically, attribution has been especially difficult in blockchain, but it’s gradually improving. While many people use multiple wallets, analytics tools are getting better at linking multiple wallets to a single user. This makes it possible to trace specific actions back to real users. Interestingly, while privacy regulations like GDPR and cookie restrictions have made attribution harder in Web2, blockchain’s on-chain transparency makes it possible to track behavior while preserving identity.
3.4 Engagement & Retention
In traditional marketing funnels, you measure pre-purchase interactions to see whether initial interest develops into active engagement. In blockchain, it’s also valuable to measure post-conversion engagement. By tracking user participation online and offline, on-chain and off-chain, you can gauge not only retention but the overall health of your community.
Online engagement appears in many forms: Discord or forum activity, X posts, reactions across social channels, and governance voting. Many marketers use traditional social listening tools, but they must adjust their interpretation to the blockchain context. For instance, sentiment analysis can show how the community feels about a project directionally, but it shouldn’t be the sole decision input. Blockchain communities are spread across multiple platforms, and a small number of highly active accounts can exert outsized influence, adding noise to the data.
Offline engagement also matters. Conferences and events are opportunities to build deeper connections. Traditionally, this meant scanning badge QR codes to collect email addresses, but now teams use tools like IYK to embed NFC chips into merch and run campaigns that prompt taps and scans. Online platforms like Discord and Towns provide dedicated spaces for ongoing relationship building, where you can analyze not just frequency but also the quality and sentiment of participation.
Retention shows who sticks around. You can measure it as the percentage of users who continue on-chain activity after a certain period, or more broadly by tracking sustained activity over time. The basic calculation compares the number of users at the start of a period with the number remaining at the end. Wallet downloads or mailing list subscriptions are just the beginning; true retention is about users who remain active after a meaningful amount of time.
In blockchain, you must distinguish between short-term and long-term users. A spike of airdrop farmers at launch may look like growth, but most of them leave once rewards end. That’s why you need to define an “ideal” user and measure retention based on that segment. You need to measure organic interest in the product itself so you don’t confuse reward-driven activity with genuine product usage. When retention improves, LTV naturally rises, because users who stay longer use and transact more.
Churn is the counterpart to retention and should be viewed alongside it. It measures how many users you lose over their lifecycle and when. In blockchain, you can approximate churn by looking at the percentage of wallets that become inactive after a certain period. These are the users who created wallets during a hype cycle or marketing campaign and then never came back. Some may return later, but the key is to focus on active, returning users rather than one-time participants.
Share of wallet is another way to track churn and retention. It represents the share of a user’s total spending in a category that goes to your product. In blockchain, you can see this literally. By examining a wallet’s composition, you can see what assets they hold and where their activity is directed. If a user stops using your protocol, you can check on-chain data to see whether they switched to a competitor.
If many token holders also own tokens from related projects, that can indicate co-marketing opportunities. You can run joint events with those projects or grant your tokens to their holders. Tools like Dune make this type of analysis possible. Since most users utilize multiple wallets, tools like Nansen can link wallets across chains for more accurate insights.
4. Practical Application and Caveats
4.1 Balancing Quantitative Metrics and Qualitative Analysis
It’s risky to look only at numbers when building a growth strategy for blockchain. Metrics show what is happening, but not why. Quantitative data points in a direction, but without qualitative insight you can’t interpret the numbers correctly.
Community sentiment is one of the most important qualitative signals. The buzz around a project, memes, and overall mood are especially important in the early stages. The energy you feel at events or the instinct that “something is working” matters too. These signals often indicate early signs of product–market fit before they’re visible in the data. In early stages, the behavior of a small group of power users can be more meaningful than aggregate statistics.
Numbers can be misleading. A surge in active addresses is not necessarily a good sign. It might be driven by bots, airdrop farming, or a passing fad. Qualitative analysis helps distinguish these. You can look at whether people are having meaningful conversations in Discord or whether the channel is filled with bot spam. You can check if more people are mentioning the product organically on X or if only incentivized accounts are talking about it.
Dashboards are necessary, but not sufficient. The most successful teams regularly talk to users directly. User interviews, feedback sessions, and community calls provide insights that numbers alone never will. Understanding how users actually use the product, where they get stuck, and what they expect is essential for deciding what to build next and where to focus marketing resources.
The most effective approach combines both. Use data to identify patterns, and use qualitative research to understand why those patterns appear. If retention drops, the numbers show that there is a problem, but you need user conversations to find the cause. If a particular feature is popular, usage data confirms it, but user feedback explains why it’s attractive. Balancing short-term buzz with long-term community building follows the same logic.
4.2 Dealing with Bots and Sybil Attacks
Bots and fake accounts are a problem on every platform, but in blockchain they’re even more severe. Once token incentives are involved, Sybil attacks—where one person creates many accounts or wallets to unfairly capture rewards—skyrocket. This distorts metrics, wastes resources meant for real users, and damages community trust.
On-chain behavior patterns are the first way to identify bots. If hundreds of wallets execute exactly the same transactions at the same time, that’s suspicious. If wallets that receive funds from the same address all act in identical ways, there’s a high chance they’re part of a Sybil cluster. On-chain analytics tools are getting more sophisticated at detecting such patterns by analyzing transaction timing, gas settings, fund flows, and contract interaction patterns.
Blockchain also offers unique identity verification tools. Human-proof systems use biometric verification to confirm that there is a real person behind an account. Zero-knowledge–based solutions allow identity verification without exposing personal data. These tools can be used to build Sybil resistance into airdrop campaigns and also to better understand the real user base.
There is no perfect solution, though. Attackers constantly evolve methods to bypass verification, and overly strict checks can lock out legitimate users. Privacy-focused users may refuse to go through verification altogether. So you must strike a balance between security, accessibility, and privacy.
Layering in behavior-based analysis is also effective. Real users engage in diverse activities, evolve naturally over time, and interact meaningfully with the community. Bots tend to be repetitive, predictable, and aimed at getting maximum rewards for minimal effort. Looking at on-chain activity together with off-chain participation leads to more accurate judgments. If a wallet has made hundreds of transactions but has never engaged in any community channel, that’s a red flag.
You should consider Sybil attacks from the incentive design stage. If you reward only transaction counts or deposit amounts, incentives are easy to exploit. Instead, requiring diverse actions, spreading rewards over time, and weighting long-term participation more heavily can reduce the economic appeal of Sybil behavior. You can’t fully eliminate Sybil attacks, but you can make them hard and expensive enough that they’re not worth attempting.
4.3 The Growth Cycle Driven by Token Price
Token price is a unique factor in blockchain project growth. When the price goes up, it does more than increase existing holders’ wealth; it becomes a magnet for new users and developers. This is not just about speculation. It’s about the psychology of wanting to join something that is clearly growing.
Rising prices send multiple signals at once. They signal that the market values the project positively, that the community is active, and that there is real demand. New users see these signals and join not just to make money, but because they want to be part of a growing ecosystem. The same is true for developers. A project whose token price is steadily rising is perceived as well-funded, community-rich, and more likely to be sustainable.
This creates a positive feedback loop. Price increases boost interest, increased interest brings more users and developers, more activity raises the network’s value, and that in turn pushes the price higher. When this cycle functions in a healthy way, it can drive sustainable growth. But the loop works in reverse too: when prices fall, interest fades, users churn, activity drops, and the price falls further.
That’s why making token price the core of your marketing strategy is risky. Price is the result of many uncontrollable factors and is heavily influenced by broader market cycles. Instead, you must focus on value, not price. The priority is to build real utility, solve real problems, and cultivate a strong community. When these foundations are solid, token price tends to follow.
Tokens can still be useful in growth strategies. For two-sided marketplaces facing cold-start problems, tokens can bootstrap initial liquidity, reward early contributors, and kickstart network effects. But this only works if the product itself provides real value. Growth sustained solely by token incentives collapses when those incentives end. If people stay only for rewards, not for the product, there is no real foundation.
4.4 Breaking Free from Incentive Dependence
Token incentives can accelerate blockchain project growth but can also become a trap. Airdrops and points programs can quickly attract users in the early stages, but it’s hard to tell whether they care about the product or just the rewards. Many projects only later realize they can’t retain users without incentives.
There are clear signs of incentive dependence. Activity drops sharply once reward programs end. Users don’t truly use the product; they do the bare minimum to earn rewards. Community conversation orbits around reward size and distribution timing, rather than the product itself. When you see such signs, you’ve found incentive–market fit, not product–market fit.
To measure true product value, you must look at behavior in the absence of incentives. You can offer the product to some user segments without incentives or gradually reduce incentives while tracking retention. This tells you how attractive the product really is. Ideally, incentives help users overcome initial friction and experience the product, after which they continue using it without rewards.
When designing incentives, it’s important to reward long-term behavior. If you only reward sign-ups or first transactions, you encourage one-off actions. Instead, you can reward continuous usage, community contributions, and bringing in other users to encourage healthier behavior. Reward magnitude should also decrease over time. You can be generous early on, then gradually reduce rewards and shift growth to the product’s intrinsic value.
The most successful projects use incentives as an initial catalyst. They gather enough early users to kickstart network effects, then let product value and community dynamics drive further growth. Protocols like Uniswap started with early liquidity mining but ultimately kept users through superior trading experience and deepest liquidity. Incentives helped at the start, but the product eventually stood on its own.
5. Conclusion
Measuring growth in crypto projects is still a work in progress. There are no clear benchmarks and no universally accepted standard metrics. But that doesn’t mean you can give up on measurement. The key is choosing metrics that fit your project’s stage and goals and understanding what those numbers really mean. The same growth curve can mean very different things depending on whether it’s driven by incentives or organic adoption.
Blindly transplanting Web2 methodologies doesn’t work—but discarding them entirely is also a mistake. Basic concepts like CAC and LTV are still valid, but they must be reinterpreted in a wallet-centric environment with token economics. On-chain transparency opens up new analytical possibilities, but also introduces new complexities like multi-wallet usage and anonymity. Each team must build its own measurement framework, and the industry as a whole is learning together.
The biggest danger is being fooled by the numbers. If you mistake incentive-inflated metrics for real product success, or interpret bot activity as genuine growth, you will end up pouring resources into the wrong direction. You need to synthesize dashboard data with community voice, user feedback, and direct experience. Data tells you where you are right now, but deciding where to go is still up to people. Metrics are just tools, and how you use them makes the difference between success and failure.
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