One, The Core Logic of Aggregators

The essence of an aggregator is to integrate fragmented and chaotic market supply by controlling the 'shelf' (demand entry point) that users access, determining the content, method of display, and onboarding costs without needing to own the products themselves, but rather controlling the relationship with buyers.

  • Classic Cases: Rover, acquired by Blackstone, integrates pet care services, and ZipRecruiter aggregates job listings, both connecting supply and demand through a unified entry point, forming default platforms.

  • Theoretical Support: Damodaran proposed 'owning the shelf,' emphasizing control over the first touchpoint when user demand arises; Ben Thompson's 'Aggregation Theory' points out that at internet scale, aggregators connect directly with users and provide standardized experiences, allowing suppliers to compete for services, with marginal costs approaching zero while user value is immense.

  • Key Conditions: The aggregated content must be valuable, and suppliers must find it difficult to exit easily; either condition lacking leads to a weak moat. For example, Airbnb maintains a durable commission due to the uniqueness of its listings, while Uber drivers can take orders from multiple platforms, creating a vulnerability in its moat.

Two, Practices of Aggregators in the Crypto Field

In the crypto industry, liquidity is the hardest moat to shake, with aggregators competing around liquidity, forming different paths:

1. Liquidity and Moat

  • The stability of liquidity lies in the pain of 'leaving being more painful than staying.' In 2020, Sushiswap proved that liquidity can be quickly transferred by incentivizing users to withdraw liquidity from Uniswap, necessitating consolidation through network effects.

  • Hyperliquid Model: Build a deep order book that allows other applications to access its liquidity (such as Phantom accessing its order flow), to become backend support with 'liquidity as a service,' prioritizing supplier strategies.

2. The Hierarchical Leap of Jupiter

Jupiter has completed a three-level evolution of aggregators within the Solana ecosystem:

  • First Level (Price Discovery): Integrate fragmented liquidity, provide the best trading price, and address the pain point of liquidity fragmentation in Solana.

  • Second Level (Execution): Shift from guiding users to operating on their behalf, optimizing the experience through smart routing, and enhancing user stickiness.

  • Third Level (Distribution Control): Embed wallets and dApps to become the default entry point for Solana transactions, controlling liquidity distribution, with nearly half of the network’s computational load originating from its transactions.


Its growth strategy includes:

  • Launch Jupnet to build a low-latency execution layer, bridging the gap between blockchain and financial-grade performance;

  • Expand service boundaries through acquisitions (such as Moonshot, DRiP), access new user flows, and strengthen the flywheel effect.

Three, The Key to the Success or Failure of Aggregators

  • Key Success Factors: Direct ownership of user relationships, suppliers being either unique or substitutable, low marginal costs, and significant scale effects.

  • Lessons from Failure: Quibi failed due to a lack of user channels and content that strayed from user attention; Facebook Instant Articles failed to become the default platform because publishers could distribute through multiple channels.

  • Model Comparison: Jupiter focuses on 'distribution control,' managing the user interface and entry points; Hyperliquid focuses on 'liquidity depth,' serving as backend support. The two respectively bet on 'user relationships' and 'liquidity itself,' creating path differentiation in the crypto field.


The ultimate competition for aggregators lies in becoming the default choice that users cannot abandon—whether by controlling the demand entry point or becoming the irreplaceable supply core.