Start Smart FA Series - Lesson 11: Crypto Competitor Analysis, How To Compare Crypto Projects Properly

Key Points

• Crypto competitor analysis is how you avoid falling for a project that sounds unique but is actually replaceable.
• To compare crypto projects properly, you must define the category first, then compare on the same job-to-be-done.
• A project’s edge is usually distribution, liquidity, developer mindshare, or unit economics, not a nicer narrative.
• “Cheaper”, “faster”, and “more scalable” are weak claims unless the project proves adoption and switching costs.
• Use a repeatable competitive analysis checklist so every altcoin gets judged with the same standard.
• If any terms feel unfamiliar, keep the Crypto Glossary open while you read.

Quick Answer

To evaluate crypto competitors, define what the project actually does, identify direct competitors that solve the same user problem, then compare them across five areas: product wedge, distribution, liquidity and network effects, developer activity, and token value capture. The strongest projects win because they are harder to replace, not because they are louder.

Where This Lesson Fits

Lesson 10 covered community and development activity. Lesson 11 shows you how to compare crypto projects against competitors, so you can see whether a project has a real edge or is just one of many similar options.

This lesson is part of the Fundamental Analysis for Beginners series. For the full lesson map and all supporting guides, visit the Fundamental Analysis hub.

Step 1: Define The Category Before You Compare Anything

Most bad competitor analysis starts here.

A project might describe itself as “AI”, “DePIN”, “Layer 1”, “RWA”, or “Web3 infrastructure”. Those labels are too broad to be useful.

Instead, define the category by the user problem:

• What is the user trying to do?
• What do they use instead if this project does not exist?
• What outcome are they paying for, time saved, cost reduced, risk reduced, revenue created?

If you cannot answer that, competitor analysis becomes random comparisons.

Step 2: Separate Direct Competitors From Narrative Neighbours

Direct competitors solve the same job for the same user.

Narrative neighbours share the same story, but serve different users or do different work.

Example

• An oracle network and a data indexing tool may both be called “infrastructure”, but they are not direct competitors.
• Two perpetual DEXs are direct competitors because they compete for the same trader behaviour and liquidity.

You want to compare direct competitors first.

Step 3: Use A Five Part Competitive Checklist

This is the framework to use every time you compare crypto projects.

1) Product Wedge

What is the clear reason a user picks this over alternatives?

A real wedge is specific, for example:

• Best liquidity for a trading venue
• Best developer tooling for an ecosystem
• Best distribution channel for onboarding
• Best performance for a specific workload

A weak wedge sounds like:

• “More scalable”
• “More decentralised”
• “Next generation”
• “Powered by AI”

If the wedge is not measurable, it is not a wedge yet.

2) Distribution

Distribution is how a project gets users without begging for attention.

Examples of distribution advantages:

• A wallet pre-install or default placement
• A major exchange or platform funnel
• A large ecosystem of apps that forces exposure
• A strong enterprise channel

When you compare projects, ask:

• Where do new users come from?
• Is there a funnel that exists even when marketing slows down?
• Is user growth paid for with incentives, or earned?

3) Liquidity And Network Effects

For many categories, liquidity is the moat.

If a project is a DEX, perp venue, money market, or stablecoin rail, the “best tech” often loses to the venue with deeper liquidity and better execution.

Ask:

• Where does the liquidity live today?
• How hard is it for users to switch?
• Does the project get better as more users join?

4) Developer And Builder Gravity

A project can have a nice product and still lose if nobody builds around it.

Use the Lesson 10 checks:

• Developer activity signals
• Grants and hackathon footprint
• Docs and tooling improvement
• Repeat contributors and ecosystem growth

Ask:

• Is this a one-team project, or an ecosystem?

5) Token Value Capture

A competitor can win the product and still have a weak token.

Tie back to Lesson 3 tokenomics and Lesson 8 adoption.

Ask:

• Does the token capture any real economic value, fees, security budget, governance power that matters?
• Or is the token mostly a narrative wrapper around the product?

This is where many altcoin comparisons fall apart.

Worked Example 1: Ethereum Layer 2s, Arbitrum Vs Optimism Vs Base Vs zkSync

These projects compete for Ethereum scaling users and developers, but they are not identical.

How to compare them properly:

Product wedge

• Arbitrum is often positioned around strong performance, mature tooling, and an ecosystem that has been live long enough to develop depth.
• Optimism is often positioned around the OP Stack and the broader “superchain” idea, meaning other chains can adopt shared infrastructure.
• Base has a distribution advantage because it sits inside Coinbase’s orbit, even if the underlying tech choices overlap with the OP Stack approach.
• zkSync positions around ZK technology, with a different long-term end state and different trade-offs during the journey.

What to learn
If you compare these only on “TPS” or “fees”, you miss the real contest, distribution, developer gravity, and ecosystem depth.

What to check next

• Where are the sticky apps and liquidity actually living?
• Which chain is the default for new users in the next cycle phase?
• How centralised are the upgrade controls today, and what is the path to improvement?

Worked Example 2: Oracles, Chainlink Vs Pyth

Both live in the “oracle” category, but they can differ in data sourcing, update mechanics, and integration patterns.

How to compare properly:

Product wedge

• Chainlink’s strength is broad integration, long-standing mindshare, and a wide surface area of services across chains.
• Pyth is known for market data distribution patterns that have become popular in certain trading-heavy ecosystems.

What to learn
An oracle’s moat is not a logo list alone. It is:

• How widely integrated it is
• How reliable it is under stress
• How easy it is for developers to adopt it by default

What to check next

• Which ecosystems are integrating it at scale?
• Is usage organic, or grant-driven?
• Does the token capture meaningful value, or is it a governance wrapper?

Worked Example 3: Perpetual DEXs, dYdX Vs GMX

These are often discussed in the same breath, but the user experience and risk model differ.

How to compare properly:

Product wedge

• dYdX has historically focused on a more exchange-like trading experience and order book style execution.
• GMX became known for a simplified perps experience with a different liquidity model and different trade-offs.

What to learn
Perps adoption is about trader experience and liquidity depth, not slogans.

What to check next

• Does volume persist through quiet periods?
• Is liquidity deep enough for real size, or does it slip on stress days?
• Does the model concentrate risk in a way that can break during volatility?

Common Traps That Ruin Crypto Competitor Analysis

• Comparing projects across different categories because they share a narrative label
• Using one metric only, TVL only, users only, volume only
• Confusing partnerships with distribution, a headline is not a funnel
• Assuming the best tech wins, in crypto, distribution and liquidity often win
• Ignoring switching costs, if users can move instantly, the moat is thin
• Ignoring token value capture, a strong product does not always mean a strong token

The One Page Competitive Snapshot Template

Use this template for every project you research.

• Category and user problem:
• Direct competitors:
• Product wedge, measurable:
• Distribution channel:
• Liquidity and network effects:
• Developer and ecosystem signals:
• Token value capture:
• Biggest weakness versus competitors:
• What must be true for this project to win:

If you fill this out, you will quickly see whether you are looking at a real contender or a replaceable clone.

Mini FAQs

What is crypto competitor analysis?
Crypto competitor analysis is comparing a project against direct alternatives that solve the same user problem, using measurable factors like distribution, liquidity, and adoption.

How to compare crypto projects properly?
Define the category first, list direct competitors, then compare product wedge, distribution, liquidity and network effects, developer gravity, and token value capture.

How do you evaluate crypto competitors?
Focus on who wins the user, who wins distribution, who has the deepest liquidity where relevant, and who has the strongest ecosystem footprint.

What is a crypto project competitive analysis checklist?
A checklist that covers product wedge, distribution, liquidity, developer signals, and token economics, so you do not get swayed by marketing.

Why do similar crypto projects exist in the same category?
Because categories are early, moats are still forming, and different teams compete on trade-offs like performance, security model, and distribution strategy.

Next Lesson

In this lesson you learned how to evaluate crypto competitors and compare projects using a repeatable framework that prioritises measurable edges over narratives.

In Lesson 12 you will learn how to put the full fundamental analysis process together, so you can run a complete, consistent evaluation on any altcoin.

For the full lesson map and all supporting guides, visit the Fundamental Analysis hub.

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The edge is the process… repeated.

Legal And Risk Notice

This content is for education and information only and should not be considered financial advice. Crypto assets are volatile and high risk. You are responsible for your own research and decisions, and you should consider seeking independent financial advice where appropriate.