Friend.tech Revelation: How to Find the Next Web3 Social Hit App?
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Friend.tech Revelation: How to Find the Next Web3 Social Hit App?
This article attempts to identify the key factors behind the success of viral applications by examining the explosive popularity of Friend.tech.
Navigating Web3 tides with focused insightsPreface
Recently, many people are discussing whether the hype around Friend.tech is sustainable. But in my view, whether Friend.tech (hereinafter referred to as "FT") can sustain its success isn't the key point. What matters is that FT's sudden rise itself carries significant meaning.
FT's explosive popularity is to Social-Fi what Gol.D.Roger’s death was to the Age of Exploration. Even if FT eventually fades like a shooting star, just like its predecessors, it may have already opened the door to the era of Social-Fi.
Since a new era appears imminent, this article attempts to uncover the ingredients behind successful viral applications by analyzing the phenomenon of FT’s breakout, so we can position ourselves ahead of the curve when the next wave of application explosions arrives.
Preface II
The broad concept of Social-Fi we refer to today can be personally divided into two subcategories:
The first type is protocol-based social apps: including Lens, Farcaster, CyberConnect, Damus, etc. These aim to overthrow centralized social platforms, branded with slogans like “Twitter killer” or “WeChat killer,” attempting to build Web3 social networks from scratch.
The second type is Ponzi+ applications: Many GameFi and SocialFi projects aren’t really about gaming or socializing at all. At their core, they’re trying to run a Ponzi scheme, merely wrapping it in a game or social layer. The game or social aspect becomes the vehicle for the Ponzi. Taking social as an example, these apps typically reshape existing social relationships or add features on top of established traffic platforms, then either transition gradually after attracting enough users through the Ponzi mechanism—or collapse outright when the scheme bursts.
Blockchain purists tend to favor the first category, but I believe that given current user scale and infrastructure maturity, the first type struggles to gain traction. It's like if WeChat had launched in 2000—without widespread 4G networks or the mobile internet wave, it likely wouldn’t have beaten QQ.
Therefore, our discussion today will focus primarily on the second type.
Main Analysis
To assess whether a Web3 social application has the potential to go viral, I believe there are three key criteria:
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Does it preserve users’ existing social resources as much as possible?
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Can it draw traffic from large existing pools rather than building its own from scratch?
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Does it have strong mechanisms for viral propagation?
1. Preserving Existing Social Resources
When evaluating a new Social-Fi product—especially the second type mentioned above—it's crucial to examine whether it preserves users’ pre-existing social resources, such as reputation and social connections. Ultimately, this reduces user migration costs.
This is similar to how Web2 products often prompt you to sync your contacts upon signup. Preserving social resources benefits not only users but also helps projects shorten cold-start periods significantly.
One reason FT succeeded is that it preserved users' existing social assets. Instead of forcing users to create entirely new accounts, FT migrated their Twitter identities—using the same names and profile pictures from Twitter directly on FT.
However, FT failed to migrate Twitter follow/follower relationships.
In this migration process, users retained their reputations and personal brands from Twitter, but lost their network ties. Still, this outperforms most of its peers.
Beyond FOMO-driven investments, what FT essentially enables is the desire among people in quasi-social networks to establish real interaction with idols, media figures, and KOLs.
In parasocial relationships, the central element is the personal brand and image of KOLs. For such relationships to transfer effectively, the key nodes from the original network must be preserved. This allows users to avoid rebuilding their personal brands from scratch when switching platforms, enabling rapid re-establishment of relational networks via these influential figures.
The smallest account unit should ideally be a social account, not a wallet.
Many current Web3 social products use wallets as the smallest account unit—wallets represent identity, and users build new accounts and accumulate social capital from there. During DeFi’s rise, this made sense because asset migration cost was far lower than social resource migration.
But in social contexts, using wallets as the base unit is suboptimal. Doing so forces users to abandon accumulated social assets. Even with systems like ENS or Lens handles, the social value carried pales in comparison to a Twitter handle. A better approach is binding wallets to social accounts—not building social relationships around wallets.
This touches on the concept of DID (Decentralized Identity). In Web3, we advocate for a unique, soul-bound decentralized identity—a DID that manages identity and serves as a universal access key across applications. Yet in practice, Twitter accounts function more like true DIDs today, since people recognize them better. When buying Keys on FT, users trust Twitter profiles—not Base wallet addresses. Thus, creating a viable DID product requires massive user traffic and scale; you don’t become an entry point because you built a DID—you earn that status by achieving dominant adoption. WeChat and Alipay have already proven this model.
2. Ability to Tap Into Large Traffic Pools Rather Than Building One From Scratch
Here we discuss relative ease of success. Why are Ponzi+ apps more promising than protocol-based ones? Because the former can leverage existing ecosystems. Draining water from a large reservoir into your small pond is far easier than digging a new lake and carrying water bucket by bucket yourself.
For example, suppose China Unicom and China Mobile phone numbers couldn't call each other. Two solutions exist:
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Solution One: Solve it at the foundational level—either get both carriers to modify their tech, negotiate profit-sharing, optimize infrastructure for interoperability; or start a new telecom operator capable of connecting both; or develop a protocol layer for integration. However, this is extremely complex—first requiring clarity on whether the issue stems from technical limitations, business unwillingness, or both, along with historical context.
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Solution Two: Create a dual-SIM phone. Users buy cards from both operators. They no longer need to know which carrier the recipient uses—the phone automatically selects the correct SIM. Seamless experience achieved, requiring only purchasing two SIMs.
Solution Two doesn’t fix root causes, but when resources and capabilities are limited, it’s far more achievable.
Today, many Web3 social projects jump straight to Solution One—aiming to dethrone giants like WeChat and Twitter immediately. While noble, industry infrastructure remains underdeveloped, creativity constrained. Even basic UX principles—like making operations seamless, something every Web2 PM knows intuitively—we still need to formalize concepts like “Intent” to barely implement. It’s too early to talk about disruption, though I still believe blockchain was born to transform foundations. The timing simply isn’t right yet.
DeFi’s success has created a false assumption: that anything can be perfectly replicated on-chain and attract mass adoption. But in social, incremental improvements or plug-in-style enhancements addressing niche needs may work better for now.
One reason FT succeeded is that it bridged big traffic pools to smaller ones by fulfilling specific user demands (albeit minor ones)—such as monetizing KOL influence, satisfying vanity during the NFT downturn, catering to admiration for influencers, etc. Moreover, FT converts public traffic into private traffic—even diverting 1% of mainstream traffic would sustain our industry for a long time.
3. Leveraging Viral Network Effects
Whether a social app’s mechanics or economic design naturally incentivize users to bring in external traffic is a critical factor for success.
Both protocol-based and Ponzi-type social apps face the same challenge: how to encourage organic external traffic acquisition. Protocol-based apps require massive user bases to achieve basic network effects. Ponzi models depend on continuous inflows to pay early adopters.
Take FT: KOLs earn revenue from Key sales, creating a natural incentive for them to drive traffic from external platforms. This results in free, widespread promotional outreach—effectively a zero-cost cold launch powered by KOLs. Once initial buyers join, they’re inherently motivated to promote FT to attract newcomers who provide exit liquidity.
Ponzi-style social apps excel at harnessing viral dynamics because their core mechanics align user and project incentives into a shared interest group. Users promote externally even without explicit encouragement from the team. Hence, when evaluating future apps, scrutinize whether their design motivates self-driven external traffic generation.
Protocol-based apps struggle here. Their goal is decentralized social utility, so driving external growth usually relies on subsidies or referral rewards. Though tokens or airdrop points are nearly free for teams, this leads to linear growth—proportional input yields proportional output—unlike the exponential, network-effect-driven explosion seen in Ponzi models.
Conclusion
While seeking insights from FT’s breakout, I believe FT reached its current status largely due to luck. From product design to economic modeling, the team clearly didn’t anticipate this level of success. Without Paradigm stepping in that weekend, FT might have vanished like so many predecessors before it.
This industry is full of randomness and coincidence. The same product, launched at a different time or involving different players, could end up with completely divergent outcomes. Such unpredictability—and sometimes arrogance—is precisely why we miss major opportunities. Those who missed StepN surely said, “Isn’t this just another Qubu?”
So perhaps trying to extract universal lessons from FT’s rise may not yield reliable formulas. If a great era is approaching, all we can do is dive in—with openness and humility—experience every possibility firsthand, and inch toward the final answer through repeated trial and error.
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