Token launches in 2025 were brutal. Altcoins launched, spiked, and collapsed — often within hours. Most founders blamed macro. Most missed the real problem: they were flying blind on market making, picking firms based on anecdotal case studies and aggressive pitch decks, with no way to verify whether any of it was true.

Forgd, a Web3 investment bank and capital markets advisor, is changing that. The firm has spent years quietly building what is now a first-of-its-kind dataset: standardized, historical market maker performance data drawn from live engagements across hundreds of token projects. That data is now powering a new layer of the Forgd platform — letting any project compare market makers head-to-head on the metrics that actually matter.

The problem that’s been hiding in plain sight

Market makers are integral to every token launch. They’re responsible for providing liquidity — the resting orders on both sides of a trade that let buyers and sellers transact without massive price swings. Choose the wrong one, or structure the engagement badly, and a launch can crater in its first hours and never recover.

But for most of crypto’s history, founders have had almost no information to make that choice. Market makers submit proposals with tight spreads and big depth commitments. They share case studies. They reference successful projects. And because there’s no standardized record of what actually happened post-launch, founders can’t verify any of it.

Forgd’s platform monitors live market maker engagements across its user base, collecting three core metrics for every engagement: bid–ask spreads, order-book depth at various thresholds from mid-price, and fill order volume broken down by maker and taker activity. Over hundreds of engagements, these data points accumulate into a longitudinal record of how each firm actually performs — not just on launch day, but across weeks and months of live trading.

Two models, two very different risk profiles

Before a project can even think about which market maker to pick, it needs to understand the two engagement structures that define the industry.

Forgd strongly advises against mixing the two structures within a single project’s market-making setup. The incentive misalignments between the two models can compound in ways that make performance evaluation nearly impossible. Most projects today work with two to three market makers, all under the same structure, across three to four centralized exchanges.

Why launches fail — and why they rarely come back

The structural shift that made 2025 so brutal for altcoins wasn’t just macro. It was a fundamental change in what retail and speculative investors expect from a token at the moment of launch. In 2021, it was acceptable to launch pre-revenue, pre-product, even pre-business model. That window has closed.

Today’s market demands proof. Users want to see a product that’s live, tested, and attracting organic activity before the token enters secondary trading. If demand isn’t there to absorb the natural sell pressure that comes from airdrop recipients, exchange counterparties, and early investors, price decays — and it rarely recovers.

What Forgd’s data makes visible

The new analytics capabilities center on four standardized indicators that Forgd tracks across every market maker engagement on the platform.

Bid–ask spread measures the gap between the best available buy and sell prices in real time. Tight spreads signal a healthy, active market maker; wide spreads indicate withdrawal or failure to perform. Order-book depth captures how many resting orders exist at various price thresholds — the difference between a market where liquidity evaporates on moderate volume and one that absorbs selling pressure without significant price impact.

Uptime tracks whether the market maker is actually active and quoting during live trading hours, including through volatile periods. And fill order volume breaks down trading activity into maker and taker categories — revealing whether a market maker is building depth or extracting value from it.

What makes this dataset genuinely new is its longitudinal dimension. Forgd isn’t showing a snapshot of how a firm performed for one project on one launch day. It’s showing patterns across hundreds of engagements, across different tokens, market environments, and venue types. That allows founders to ask not just “did this firm perform well?” but “does this firm consistently perform well when conditions get difficult?”

The RFQ process — and where founders get trapped

The standard way a project hires a market maker is through an RFQ process: the project circulates a brief to multiple firms, receives proposals with spread targets, depth commitments, and fee structures, and picks a winner. The problem is structural. RFQ dynamics create strong incentives for firms to submit aggressive bids — tight spreads, large depth commitments — that they may not be able to sustain once trading goes live.

When founders compare proposals through Forgd, they can now see each firm’s historical adherence to the kinds of KPIs they’re proposing. A firm bidding 0.15% spreads that has historically delivered 0.4% spreads on comparable tokens is a very different proposition from one with a consistent track record of hitting or beating its targets. That context changes the negotiation entirely.

Signals every founder should track before signing

East and west, CEX and DEX

One structural reality Forgd emphasizes with every founder: geography matters, and so does venue type. The speculative trading ecosystem in Asia — particularly Southeast Asia — generates significantly more volume and activity for newly listed altcoins than Western markets. A project with a North American founder base that skips Asian exchange listings is leaving a major portion of its potential buyer base untouched.

Similarly, Forgd advises against launching exclusively on centralized or decentralized venues. CEXs bring scale and distribution — large quantities of users who provide volume. DEXs attract a smaller but more sophisticated, protocol-native audience — the early adopters most likely to become power users of the underlying product. Market makers must cover both, and they approach the two venue types differently: centralized exchanges use continuous limit order books, while most DEX liquidity operates through concentrated liquidity AMM pools that require active management as price moves.