Overview

Conversion tracking allows advertisers to measure user actions (such as sign-ups, purchases, or installs) that occur after interacting with an ad.

To ensure accurate attribution, Slise provides dynamic tracking tokens that can be appended to landing page URLs. These tokens are replaced in real-time with actual values when a user clicks an ad.

How It Works

1. A user clicks on an ad.

2. The click URL includes one or more tracking tokens.

3. Slise dynamically replaces these tokens with real values.

4. The user is redirected to the advertiser’s landing page.

5. The advertiser records these values and attributes conversions accordingly.

Example

Tracking URL

https://example.com/?click_id={click_id}&campaign={campaign_id}&geo={geo}

After Click (Resolved)

https://example.com/?click_id=abc123xyz&campaign=9876&geo=NG

Available Tokens

Below is the full list of supported tokens on the Slise platform:

Most Important Tokens

While all tokens can be useful, the following are critical for proper conversion tracking:

1. {click_id}

• Unique identifier for each click

• Must be stored and passed back on conversion

• Enables precise attribution

2. {publisher_id}

• Identifies the traffic source

• Important for partner-level performance tracking

3. {campaign_name} or {campaign_id} Or both concatenated together

• Identifies which campaign generated the conversion

• Useful for reporting and optimization

Example Conversion Flow

1. User clicks ad → redirected with:

?click_id=abc123&publisher_id=4

2. Your system stores:

click_id = abc123 & publisher_id = 4

3. Conversion occurs → you report:

click_id=abc123 & publisher_id = 4

4. Slise matches conversion to the original click and publisher

Notes

• Tokens are case-sensitive

• Missing tokens may result in incomplete attribution

• Some tokens are optional but recommended for deeper analytics

Wallet-first distribution map

There are only so many ways to reach a user: you either can use permissionless public channels, create your own medium with the traffic, or partner with someone who has the traffic.

1. Public channels. Aka airdrops—present the simplest way to send your message directly to a wallet. This is the beauty and the curse of this channel. Something that works for everyone ends up working for no one. Simplicity and lack of control made it lucrative for spammers, and the amount and risks associated with everything landing in the user's wallet made airdrops completely useless. dApps and wallets hide airdrops to protect users from spam, and in the end, such ads receive no impressions. Projects building in this category include: Venly, Novel, WalletAds, Flambo, SuperDAO, and others.

   Realistic coverage: next to nothing

   Lookout for:

   1. What creative ways to get to the user's eyeballs did the team come up with?

   2. Since there are no ways to track views, what CTR and ROI does the product show with respect to the initial budget / number of airdrops sent?

2. Creating your own traffic. Why then, not create your own managed platform, where wallets could be reached for a fee, that will help to curate serious advertisers and limit spam—that must’ve been what the founders of Dispatch, Salsa, DeBank Hi, and other direct-to-wallet messengers alike thought.
   There’ve also been other experiments with finding ways to make users connect their wallets and watch ads, like putting ads on the user’s homepage through a Chrome extension, to the extent that even Brave browser follows this model if you think about it.
   The problem with this model is that a large user base is hard to build, especially in web3, while any adtech business requires millions of impressions to be a meaningful distribution channel. Furthermore, If this is just a spam mailbox where the user receives ads—no one is going to open it in the first place, so fundamentally, the team needs to build another successful product that the user will want to use, and then place ads in it (like a browser, publication, or a social platform).

   Realistic coverage: tens to hundreds of thousands UAW

   Lookout for:

   1. How many real active users does the project have? What’s the UAW (Unique Active Wallets)?

   2. What does economics (CAC) look like? Advertising through DeBank Hi will cost you $1000 in CPM minimum, what returns does it show?

   3. Is the traffic limited to a single chain?

The teams that were not ready to build their own Facebook turned to a much more scalable and less risky option, that is to mediate traffic between a large number of publishers and advertisers while focusing purely on adtech functionality and leveraging the economy of scale.

3. Placing ads in the Metaverse. What’s a metaverse in the first place, you may ask. For the sake of simplicity, here we’ll consider Blockchain-based 3D Online MMORPGs, which allow proving ownership of in-game assets, like Decentraland or The Sandbox. Considering that the main idea of the metaverse is that a lot of people will hang out there, it makes sense to advertise on the available in-game surfaces. The prominent players who are trying to tackle it are Anzu, Landvault, AdShares, and MetaAds (different Meta).
   The limitations of this method are straightforward: 1) there is no real traffic in the Metaverse today; 2) creating and placing in-game content requires much higher upfront investments than display banners or even minting NFTs, while also closing the door for compatibility across platforms. This leaves metaverse at the position of an overpriced niche channel for clout chasers, but not an efficient adtech platform. At least for now.

   Realistic coverage: thousands to tens of thousands UAW
   Lookout for:

   1. How many real active users does the project have? Does it have access to the main user wallet?

   2. What does it take to place the ads there? Do you have to hire anyone to do development for you?

   3. What tracking and reporting are available? How will you know what you’ve paid for?

4. Placing ads in the dApps. By far, the largest of web3 distribution channels, as it unites a large number of dApps with existing traffic on the terms of partnerships, allowing dApps to monetize without dealing with the adtech part. This allows compatibility and optimization of traditional web2 Ads through standardized display banners and hence the highest efficiency and CAC per wallet.
   The obstacles of working with ad networks like Slise.xyz, HypeLab, Pr3sence, BlockchainAds, and others who do exactly this, is that direct web3 traffic is difficult to acquire (try to recall how often you see the ads in dApps). The total dApp market is still small and amateur, and it will take for projects to open up to placing ads and for the volume of traffic to grow.
   On the bright side, most of these providers are multichain, meaning that unlike other channels it can work if for your edgy and cool layer 1, or even allow to target users from other chains!

   Realistic coverage: millions to tens of millions UAW
   Lookout for:

   1. How many wallets on your target chain does the network cover?

   2. Does it have personalization and targeting, or simply charges CPM without using wallet data?

   3. What are the publishers in the network? Are they credible? What kind of audience do they have?

4. Finding Web3 users in Web2. The most edgy and technically complex channel of all, but also the one with the highest potential volume, is tapping into the audience of Web2 publishers.
   In this scenario, you’re still able to target users based on their wallet, but on the surfaces where they don’t connect it, e.g. web2 social media, crypto-publications, web2 ad networks, or even email! Solutions of this kind offer to connect web3 and web2 identifiers, and each of them has its own way to make it possible.
   For example, Addressable allows re-targeting web3 users in social networks, while Slise can help you reach wallet owners on web2.5 platforms with a lot of hits like media publications and coin trackers. Another seemingly tangent vertical is whitelisting and giveaway platforms like Premint and Quest3. You may know them as tools for attracting large volumes of untargeted cheap traffic, but if you look at them closer, they’re harvesters of user identifiers like twitter, discord, and email id’s that potentially can be used for targeted outreach (to the best of our knowledge none of them provide such functionality yet).

   Realistic coverage: millions to hundreds of millions UAW
   Lookout for:

   1. With no two solutions alike in this category, it will be difficult to compare them head-to-head, but metrics and case studies on coverage, CTR, CAC, and ROI are still your best friends.

   2. Take note of the quality of the traffic, does it represent your audience or made out mostly of quazi-bots hunting for freebies?

   3. Make sure to understand how the data is collected to not stain your brand reputation.

You’ve made it to the end, what a true legend!

If you want to test advertising to a particular audience of token-holders, don’t hesitate to contact us at Slise.xyz, where we work hard to create the largest network of web3-native publishers. Want to place the ads and monetize? Reach out to us as well!

The advertiser's dream is to target only the "whales"—the high-value users most likely to convert. But this dream creates a complex, often hidden, economic nightmare for the ecosystems that facilitate this targeting, namely ad networks and publishers. The very act of hyper-targeting fragments the market and creates a paradoxical pricing problem.

This article delves into the intricate economics of pricing targeted ads. We will move beyond simplistic calculations to explore a sophisticated analytical model that predicts the fair market price for any audience segment. For advertisers, this knowledge is power—it allows for smarter budgeting and strategy. For publishers, it’s survival—ensuring their most valuable asset, user attention, is priced correctly and profitably.

The Core Problem: The Illusion of Uniform Value

Imagine the entire internet-using population as a vast ocean. Each user is a drop of water, but not all drops are equal. Advertisers, using sophisticated sonar, are no longer interested in the ocean itself; they are hunting for specific, rare species of fish that live in its depths.

The initial, simplistic view of advertising assumed a somewhat uniform ocean. A publisher would sell a million impressions at a flat $5 CPM (Cost Per Mille), grossing $5,000. An ad network could then resell these impressions at the same rate and break even. The value of an impression was the value of an impression.

Targeting shatters this illusion. An advertiser now doesn't want the ocean; they want a specific, one-liter bottle of water drawn from a particular coral reef off the coast of Vietnam. The immediate, naive calculation is that if this Vietnamese-specific segment represents 1% of the total traffic, its effective cost must be 100 times higher to cover the cost of processing the other 99%—a staggering $500 CPM.

This calculation is mathematically sound but economically blind. It assumes the other 99% of the traffic is worthless garbage to be discarded. In reality, it represents a vast inventory of attention that can be sold to other advertisers targeting India, Brazil, or users interested in sports, cooking, or finance.

The true challenge, and the heart of the pricing problem, lies in answering this question: What is the fair market value of a specific audience segment, given that the rest of the traffic has a compensating, but often lower, value?

The Ice Cream Truck Analogy: The Cost of Unwanted Inventory

Why then Googles and Metas of the world are still not out of business? Because they have an enormous scale which allows them to find demand even for the most unusual audiences, but more importantly—allows them to run an auction where free market decides how each audience should be priced, and at the right price (of pennies vs dollars) even the least desirable long tail of the users find its buyers.

That being said, an auction is impossible for local networks where the number of potential segments easily surpasses the number of individual bidders. And here comes our problem statement—how can we analytically predict a fair market price for an arbitrary segment of the audience an advertiser wants to target?

The simplistic approach

We take as given that all the traffic has some value, whether it’s an opportunity cost for a publisher or the actual price ad providers pay publishers before distributing traffic further to advertisers.

Say, a publisher sold 1M of impressions to an ad network at $5 CPM, charging for it $5k. An ad network can sell them at $5 for the whole audience and break even. But what if a sophisticated advertiser wants to target a smaller segment that makes up only 1% of the whole audience? (Take for example Vietnam vs global.) First, there will be only 10k of such impressions, but more importantly, to find them an ad platform still needs to buy all 1M of impressions from all over the world and pay for them, making the break-even CPM of such an audience proportionally larger to its size. If the segment is 100 times smaller, advertisers will be paying an effective CPM of $500, and if you target 100 whales in a network of millions of users—well, good luck.

The weakness of such logic is in what happens to the nonrelevant 99% of the traffic. Can’t it be recycled or sold to someone who has different targets? Talking about the world without Vietnam (Ed.: we wouldn’t like to live in such a world), there is still a lot of opportunity, someone else may target India or the US. There is a compensating demand, which will lower the predicted CPM, by generating revenue from the other parts of the traffic, but it will never compensate 100%. In reality, it’s very hard to find enough buyers to sell each unique segment other buyers turned down. And more than that, the segments that get sold first are the highest paying and the most valuable users, making it almost impossible to sell traffic bundled up from third-world countries and empty wallets. So, it won’t be $5 for everyone either. It will be somewhere in between and we need a more complicated model to find it.

The Slise’s funny little model

What if we forget about the ice cream and present demand as a fluid creating pressure on the bottom of a fixed container? Sounds schizo, but this is exactly what the brightest brains in Slise Research did to discover an elegant dependency between traffic, target size, and compensating demand.

The size of the container is all the available traffic, and the pressure of a fluid is, well, dollars/impressions—the exact formula of CPM. This way of finding CPM from the actual demand corresponds better to a free market auction model for advertising where a fixed asset is priced according to the demand for it. If the demand increases—the pressure goes up, if we take a larger container—the pressure goes down. So far so good.

For visualization, let’s take the same 1M impressions total, and the demand made of not one but 10 advertisers willing to spend $1,000 each. Given there is no targeting and $10k being spent on 1M all users uniformly, everyone will get the same $10 CPM (Pic. A). If we fantasize that given a full freedom advertisers will find their ideal audience not overlapping with others and utilizing fully available inventory we can imagine something like Picture B, giving the same $10 CPM for everyone, however, it’s not likely to happen, and in the real world we need to work with something more like Picture C.

In this representation, we can even model how the distribution of demand changes more generally if we fix some of the parameters and change the others. Inevitably, with more variables given freedom, the distribution converges to a power law distribution and exposes “empty” areas with no demand—a terrifying situation for any publisher (unless the number of advertisers is high enough to cover it fully).

In the same manner, moving iteratively, we can solve for particular cases of one new advertiser of the same budget running a targeted campaign with specific parameters. Say, only for half of the audience, or even 1% of the audience as we explored earlier.

Looking at Picture D we can clearly say that the resulting CPM of $12 for a new campaign is much smaller than what we would get by just calculating the proportion of the audience size (twice smaller audience should give double the price). The same happens in the case E where an audience of 1%-size results in $110 CPM and not $1,000 CPM, roughly ten times lower. This happens thanks to amortization from the other advertisers who run campaigns for a broad audience or other segments.

In fact, there is a dependency between new demand and compensating demand, and in case F, when we add two new advertisers for the same target, an amortization of $9.9K is much weaker now versus $2K than it was versus $1K and CPM grows to $210, a mere five times lower value than we would get by buying out all of the traffic:

Even from such simple examples, we can note many interesting patterns:

1. The rest of the (untargeted) audience is not affected by the new players adding pressure to the target segment, its demand changes proportionally to supply and CPM stays at $10, just as if the containers got completely separated.

2. When new demand appears, it affects this whole audience segment and everyone who has exposure to it increasing the price for everyone. For example, in Picture D, the final CPM of the whole audience will be 0.5*$10 + 0.5*$12 = $11 which makes sense given that total demand grew to 11k but supply stayed at 1M.

3. If other players want to target other segments they will act as separate containers with their own demand. The combination of the two containers would produce a sum of the budgets and a sum of the areas, allowing us to find new CPM for any number of complex segments.

To generalize our conclusions, we can describe the price of a targeted segment by a simple formula:

where D—is a coefficient describing the share of new demand (d) to the total demand (budget), and T—is the share of target traffic (t) to all traffic. In Pic. E, d = $1K/$10K, and t = 0.01, giving 11*$10 or $110.

Going multi-dimensional

So far we’ve discussed the segmentation of the audience along one axis, it can be location, device, net worth, trading volume, or anything that can be sliced from the total without overlap. But different axes can overlap: if iOS users make up 25% of the total traffic and Vietnam makes 1% of the total traffic, the share of iOS users from Vietnam will be around 0.25% or 2.5K impressions in our example.

The same can be done with the budgets if we know how much is allocated for each segment. Let’s say it’s still $1K for Vietnam and $5K for iOS users, the demand creating buying pressure on the overlapping segment will be 0.25*$1K + 0.01*$5K + 0.25*0.01*$10K (let’s not forget broad campaigns) bringing demand (budget) for this tiny segment to $325. If we divide one by another we’ll end up with a cumulative CPM.

The beauty of math behind this approach lies, of course, not in the ability to describe such, even though the more complicated but still simple, case, but in its prediction power to find CPM of overlapping segments across any number of dimensions (audience properties). If you play with variables instead of numbers you’ll quickly arrive at a simple but precise formula like this:

Which, finally, gives us a good proxy to estimate the market price of an arbitrary audience segment simply by knowing the budget currently competing for this segment and its size relative to the total audience.

Final advice to advertisers

1. Increase the size of your audience to lower the CPM.

2. Look out for undervalued segments with low demand as their price may be even lower than the broad audience.

3. When playing with multiple overlapping filters try to understand which one of them brings the largest contribution to the price.

4. Diligently monitor performance to see if the extra spend on targeting justifies itself in final conversions. Paradoxically, when the broad audience is concentrated enough (like in the case of Slise for crypto-users) broad campaigns can drive better performance due to the lower cost.

Final advice to publishers

1. Attract better users.

2. Attract users better.

3. If you wonder how profit margins change in the case of targeting, our model only helps to find equilibrium, i.e. minimum price to be charged for a targeted campaign without incurring a loss in comparison to just selling traffic broad.

P.S. It took so long to write this article that by the time of publishing this model has already been developed and deployed to production in Slise targeting estimator and is currenly making us lose money every day. Slise Research department has been disbanded and all employes transitioned to engage in physical labor.

Don’t miss a chance to play with it in our interface!

FAQ

What's the difference between CPM, CPC, and CPA?

• CPM (Cost Per Mille): You pay for every 1,000 impressions (views) of your ad. The publisher is paid for generating attention.

• CPC (Cost Per Click): You pay for each click on your ad. The risk of low click-through rate shifts somewhat to the publisher/ad network.

• CPA (Cost Per Action/Acquisition): You pay only for a specific action (e.g., sale, sign-up). This shifts almost all the risk to the publisher, which is why it's harder to get them to accept such deals for unproven offers.

Why is targeting so expensive on small ad networks compared to Facebook?

Facebook has millions of advertisers, creating liquid, efficient auctions for nearly every possible user segment. A small network has fewer buyers, making it harder to sell the "non-targeted" portion of the inventory. The cost of that unsold inventory gets factored into the price of the targeted segment, making it more expensive.

How can I estimate the cost of a targeted campaign before launching?

• Use the platform's built-in audience sizing and estimation tools.

• Work backwards from your target CPA. If you know your conversion rate, you can calculate the maximum CPC you can afford. Then, use estimated CPMs and CTRs to see if it's feasible. (e.g., Target CPA = $50, Conversion Rate = 2%, so Max CPC = $1. If estimated CTR is 1%, then Max CPM = $10).

• Start with a small test budget to gather real-world data on CPMs and conversion rates for your segment.

What is an "undervalued audience segment"?

It's a group of users that has a high potential conversion value but currently has relatively low advertiser demand competing for it. This could be users in emerging markets, users on specific device types, or users with niche interests that are not yet saturated by advertisers. Their CPM is lower than their potential value would suggest.

As a publisher, should I avoid selling targeted deals?

No. Targeted deals are often your highest-value transactions. The key is to price them correctly using a smart yield management system that accounts for the opportunity cost of your inventory. Avoid deals that cherry-pick your best users without compensating you for the loss of value on the rest of your traffic.

On the surface, its logic is impeccable. "Why pay for mere impressions or clicks," the argument goes, "when you can pay only for proven results?" It positions you, the advertiser, as a shrewd businessperson, eliminating waste and aligning incentives perfectly with your partners. It’s the ultimate "win-win."

Except it’s not. In reality, that "win-win" proposal is often perceived on the other side as a raw deal, a fundamental misreading of how the digital advertising ecosystem functions. If you've ever struggled to get publishers, ad networks, or influencers to use your referral links, you've experienced this firsthand. The silence or polite decline isn't a sign of lazy partners; it's a rational economic response to a flawed proposition.

This article deconstructs the pervasive myth of CPA as a universal advertising solution. We will delve into the brutal economics of user attention, the critical roles each player fulfills in the conversion funnel, and why asking a publisher to bear your product's risk is a recipe for rejection. Finally, we will explore the specific conditions under which CPA can work and provide a realistic blueprint for structuring offers that partners will actually want to promote.

The Fundamental Flaw: A catastrophic Misdistribution of Risk and Reward

At its core, the standard CPA model suffers from a critical imbalance. It attempts to shift 100% of the execution risk onto the publisher or advertiser, while the advertiser retains 100% of the product risk. This is not a partnership; it's a gamble where only one party has dice.

A more accurate name for the typical CPA offer would be "Heads I Win, Tails You Lose" for the publisher.

Think of it this way: You are essentially asking a publisher to use their hard-earned, finite resource—their audience's attention—to bet on your product's ability to convert and retain users. They are investing their capital (traffic) upfront. They must trust that:

1. Your landing page is optimized.

2. Your sign-up process is smooth.

3. Your product actually delivers on the promise made in the ad.

4. A user will find enough value to complete the specific action you've defined.

The publisher has control over none of these variables. Yet, they are expected to foot the bill for every click that doesn't convert. This isn't just unfair; it's commercially nonsensical.

A more vivid analogy: It’s like asking a world-class chef to prepare a meal for your important guest using a mystery box of ingredients you provide. You’ll only pay them if the guest declares it the best meal of their life. The chef bears the cost of their time, expertise, and overhead, while you bear no risk if your ingredients were spoiled or simply unappealing.

Deconstructing the Funnel: Why "The Action" is Not Created Equal

To truly understand why publishers balk at blanket CPA deals, we must dissect the user journey from casual browser to converting customers. This journey is a multi-stage funnel, and each stage has a different owner who assumes risk and deserves compensation.

The Value Chain of Digital Advertising:

1. The Publisher: Generating Raw Attention

   • Role: Publishers (bloggers, app developers, video creators, news sites) invest immense resources into creating valuable content or services that attract a specific audience. Their product is user attention in the form of ad impressions.

   • Risk & Reward: They risk capital and time on content that may not attract an audience. They are compensated for successfully generating and aggregating attention, typically through flat-rate deals (e.g., CPM - Cost Per Mille) or revenue share from ad networks.

   • Key Fact: According to a 2023 Pew Research study, over 70% of publishers cite audience acquisition and retention as their biggest challenge. Their traffic is their most valuable asset, not a limitless commodity.

2. The Ad Network: Refining and Distributing Attention

   • Role: Networks like Slise, Google Ads, or Meta act as sophisticated intermediaries. They take "raw" traffic from thousands of publishers, clean it (fraud prevention), enrich it with demographic and behavioral data (targeting), package it into accessible inventory, and provide analytics tools for advertisers.

   • Risk & Reward: They build and maintain complex technology platforms, manage publisher relationships, and guarantee brand safety for advertisers. Their margin is a fee for creating efficiency and scale in the market. They are paid for processing inventory, not for your product's performance.

   • Key Fact: A study by Juniper Research estimated that ad fraud would cost advertisers over $68 billion globally in 2023. Ad networks invest heavily in mitigating this risk, a cost baked into their pricing models.

3. The Media Buyer/Marketer: Optimizing the Click

   • Role: This can be an in-house team or an external agency. Their expertise lies in crafting compelling ad copy, designing converting creatives, A/B testing campaigns, and strategically bidding to maximize Click-Through Rate (CTR). They transform impressions into clicks.

   • Risk & Reward: They risk their time and their client's advertising budget on campaign strategies. They are judged on their ability to lower Cost Per Click (CPC) and increase CTR. Their compensation is often tied to these metrics or a managed service fee.

4. The Advertiser (You): Converting the Click

   • Role: Once the click is achieved, the baton is passed to you. The user lands on your landing page. Now, your product, your UX/UI design, your value proposition, and your onboarding process take over.

   • Risk & Reward: You assume all "product risk." Is the page fast? Is the value proposition clear? Is the sign-up form too long? Does the product actually solve a user's problem? This is where the final conversion happens—or doesn't.

5. The Product & Onboarding Team: Securing the Value

   • Role: After the sign-up, it's up to the product itself to deliver value and ensure user retention. A clumsy onboarding flow or a buggy app can kill a customer relationship instantly, nullifying all the previous work.

   • Risk & Reward: This is 100% internal risk. The publisher's ad didn't promise a clunky experience; your product delivered one.

The entire chain is multiplicative. The final number of conversions is a product of each step's success rate:

Impressions × CTR × Landing Page CVR × Onboarding Success Rate = Conversions

If any single part of this chain fails, the final result is zero. The CPA model, however, asks the first link in the chain (the publisher) to bet their compensation on the flawless execution of all subsequent links, which they have absolutely no control over. It’s not just unfair; it’s a terrible business decision for them.

If Your CPA Rate is Profitable, You Should Capture the Margin Yourself

Let's move from theory to cold, hard economics. Consider the types of products that thrive in traditional affiliate networks: gambling, "miracle" weight loss pills, questionable finance schemes, and adult content. What do they have in common? They are often:

• High-Intent, Low-Friction: The user knows what they're getting and the action is simple (e.g., placing a bet).

• High Customer Lifetime Value (LTV): A converted user is worth a lot of money.

• Often Controversial or Restricted: They face limitations on mainstream ad platforms, forcing them to pay a premium for access to traffic.

Crucially, they are not typically innovative SaaS platforms, complex B2B services, or new consumer social apps.

Now, ask yourself: If your product has a proven, highly profitable advertising funnel where you earn $100 for every $10 you spend on ads (a 10:1 ROAS), why on earth would you offer a CPA deal?

Imagine this scenario:

• You determine that a new user is worth a Lifetime Value (LTV) of $150.

• Through testing, you know you can acquire a user for a Cost Per Acquisition (CPA) of $15 via Google Ads.

• This means you have a profit of $135 for every user you acquire yourself.

In this scenario, offering a publisher a CPA bounty of $25 per sign-up is irrational. You are giving away $25 of your profit for a service you can perform yourself for $15. The rational move is to double down on your own successful marketing channels, scaling them until they saturate. You should be capturing that entire margin.

Offering a CPA deal only makes financial sense in two situations:

1. You Cannot Scale Your Channels: You've maxed out your available inventory on your most efficient channels and need to tap into new, unfamiliar traffic sources. You are willing to pay a premium (the publisher's profit) for access to this new audience.

2. Your Internal CPA is Higher Than The Bounty You're Offering: This is the most common, and most problematic, scenario. If it costs you $50 to acquire a user, but you offer a $20 bounty, you are asking a partner to lose $30 on every conversion for you. No sane business will do this.

The Publisher's Calculus:
A publisher or media buyer will instantly evaluate your offer against their known costs. They know the average CPM and CPC for their traffic.

• Example: If their average CPC is $0.50, and your landing page has a historical conversion rate of 2%, their expected cost to generate one conversion is $0.50 / 0.02 = $25.

• If your CPA bounty is $20, they lose $5 per conversion.

• If your bounty is $30, they make $5 per conversion.

Their traffic is a valuable asset with opportunity cost. Why would they run your loss-making campaign when they could run another advertiser's campaign that generates a positive ROI?

The Expertise Gap: No One Knows Your Product Like You Do

This leads to the third fatal flaw of the poorly conceived CPA model: the expertise fallacy.

It is naive to expect that a publisher who juggles dozens or hundreds of advertisers will suddenly become an expert on your specific product, your unique value proposition, and your niche audience. You and your marketing team are the world's leading experts on your product. You have the deep domain knowledge, the customer insights, and the passion necessary to craft the most compelling message.

"You provide the creatives!" is a common retort. But performance marketing is not about providing a single set of pretty banners. It's a dynamic process of data-driven optimization. It involves:

• Continuous A/B testing of ad copy, visuals, and calls-to-action.

• Deep audience segmentation and targeting adjustments.

• Analyzing funnel drop-off points and iterating.

• Adapting to real-time feedback and market fluctuations.

This optimization loop requires rapid iteration and financial stake. When you, the advertiser, spend your own money, you are highly motivated to find what works. You feel the pain of wasted ad spend immediately and react.

When a publisher spends their money on your campaign, that feedback loop is broken. They have no insight into why an ad underperforms. Is it their audience? Their placement? Or is it your confusing landing page or mediocre product? They won't spend weeks and thousands of dollars to find out; they'll simply shut off your campaign and move on to one with a clearer path to profitability. Their incentive is not to make your product a success; their incentive is to maximize ROI from their traffic.

This idea of outsourcing the entire marketing function without ceding any control or data, and expecting a partner to be okay with assuming all the financial risk, is the fundamental reason why the dream of "easy CPA" is dead on arrival for most advertisers.

When CPA Does Work and A Blueprint for Successful Partnerships

Despite its pitfalls, the performance-based model isn't inherently evil. It powers the entire affiliate marketing industry, which is worth billions. The key is understanding that successful CPA deals are not built on shifting risk, but on aligning incentives through transparency, data, and shared opportunity.

The Hallmarks of a Successful CPA Offer

For a publisher to genuinely embrace your referral link, your offer must be commercially viable. This means it must be:

1. A Proven Winner with Data: You can't offer a mystery box. Distributors must be able to choose your offer based on its proven profit potential. This requires transparency. Top affiliate networks provide deep data on offers: historical EPC (Earnings Per Click), conversion rates, approved lead rates, and average payout amounts. This allows a media buyer to model their ROI before they spend a dollar.

2. A Clearly Defined and Achievable Action: The action must be simple, trackable, and relevant. "Purchase a $2,000 software license" is a high barrier. "Sign up for a free trial" or "Download a whitepaper" are lower-friction actions that are easier to promote. The higher the barrier to entry, the higher the bounty needs to be to compensate for the lower conversion rate.

3. A Competitive and Realistic Bounty: The payout must adequately cover the publisher's estimated acquisition cost and leave them a healthy margin. This often means you need to understand the CPCs in their niche. A $2 bounty for a finance app might be laughable, while a $2 bounty for a mobile game download might be competitive.

4. Supported by High-Quality Marketing Assets: Don't just provide a link. Provide a swath of proven creatives—banners in multiple sizes, email swipe copy, pre-landing pages, and video scripts. You've done the testing, so give them the winners to start with, accelerating their path to profitability.

5. Backed by Reliable Tracking and Timely Payments: Nothing kills trust faster than broken tracking links or delayed payments. Use reputable affiliate software (like HasOffers, PostAffiliatePro) or work with established networks that provide impartial tracking and payment guarantees.

The Special Case of Crypto and High-Risk Verticals

The original article mentioned crypto, which is a perfect case study. The crypto space is notoriously overheated with funding, leading advertisers to believe they can throw money at any problem, including user acquisition. They often show up with ludicrously complex offers: "Get a user to deposit 0.1 ETH, swap it for three different tokens, provide liquidity to a pool, and then stake the LP tokens—we'll pay you $50!"

This is the "lift a rock from the ground" analogy perfected. The funnel is too long, the action is too complex, and the user education required is immense. The publisher's traffic would be better spent on a simple "Sign up for an exchange" offer with a clear bounty.

For CPA to work in crypto or any complex vertical, the action must be simplified to its bare minimum, and the bounty must be astronomical to compensate for the low conversion rates and high support burden. Even then, most savvy publishers would prefer a RevShare model on trading fees, aligning long-term incentives rather than a one-time CPA.

Conclusion: From Entitlement to Partnership

The core issue with the refrain "no one wants my referral links" is often a mindset of entitlement. It's the belief that your product is so inherently wonderful that publishers should be grateful for the opportunity to promote it, even on your skewed terms.

The reality is the opposite. User attention is the scarcest commodity in the digital world. Those who hold it—the publishers—are in the power position. They are not waiting around for your offer; you are competing for their attention and their traffic.

To succeed, you must shift your perspective from "How can I get publishers to work for me on my terms?" to "How can I structure a mutually beneficial partnership that respects the value of their traffic and shares the risk appropriately?"

This means:

• Start with CPM or CPC deals: Prove your product's conversion capabilities yourself first. Own the risk on your landing page and product experience. Gather the data that proves your funnel works.

• Build a track record: Once you have a proven, profitable funnel, you can then approach publishers with a compelling CPA offer. You can say, "We know a user is worth $150 to us. We can acquire them for $50 on our own. We'll pay you a $70 bounty to acquire them from your unique audience, giving you a healthy profit and us a new channel."

• Be transparent and supportive: Provide data, creatives, and support. Treat your publishers as true partners, not as customer acquisition vending machines.

The dream of risk-free customer acquisition is just that—a dream. Sustainable growth is built on shared success, not on foisting your risk onto others. Build a great product, prove you can convert traffic yourself, and then you’ll find that partners will be lining up for a piece of the action—on terms that work for everyone.

FAQ

What's the difference between CPA, CPC, and CPM?

• CPM (Cost Per Mille): You pay for every 1,000 impressions (views) of your ad. The publisher is paid for generating attention.

• CPC (Cost Per Click): You pay for each click on your ad. The publisher/media buyer is paid for generating traffic.

• CPA (Cost Per Action/Acquisition): You pay only for a specific action completed by a user (e.g., sale, sign-up). The advertiser pays only for a concrete result, but the publisher assumes all the upfront risk of generating the clicks.

Isn't affiliate marketing based on CPA? Why does it work there?

Yes, but successful affiliate marketing operates under the principles outlined in Part 3. Affiliate marketers are not passive publishers; they are active media buyers and content creators. They meticulously choose offers with proven high EPC (Earnings Per Click) from networks. They often create their own landing pages, reviews, and content to pre-sell the product, effectively taking control of the parts of the funnel they can influence. They also have the freedom to drop underperforming offers instantly.

What should I do if publishers are rejecting my CPA offers?

• Audit your own funnel: What is your internal CPA? If it's high, your offer is likely unprofitable for others.

• Increase your bounty: Make the offer financially irresistible. If you can't, it's a sign your product economics may not support paid marketing yet.

• Provide better assets: Give partners a head start with high-converting creatives and copy.

• Consider a different model: Start with a CPC deal to let the publisher win while you assume the conversion risk. This builds trust and gives you valuable data.

Are there any tools to help me manage CPA affiliate programs?

Yes, using professional affiliate tracking software is crucial. Platforms like ShareASale, Impact, PartnerStack, PostAffiliatePro, and HasOffers provide reliable tracking, attribution, reporting, and payment processing, making you look more professional and trustworthy to potential partners.

My product is new and I have no conversion data. What can I do?

You are not ready for a CPA program. Your first step is to use your own budget on self-serve platforms (like Facebook Ads, Google Ads) to validate your product, messaging, and landing pages. Once you have a predictable cost of acquisition, you can then explore partnerships.

In the early days of Web3, the focus was squarely on on-chain analytics. Teams spent countless hours dissecting wallet data, creating intricate charts, and segmenting audiences based on transaction history, NFT holdings, and DeFi activity. But a critical question always remained: What do we do with this list of wallet addresses now?

The industry has since matured. The pioneers who built those analytics engines have diverged, applying their expertise to new frontiers. Some developed sophisticated Web3 CRMs, others built the analytics APIs that power the ecosystem, and a third group tackled the most challenging problem of all: the consumer-facing distribution layer—the actual art and science of reaching a wallet owner with a message.

This evolution marks a fundamental shift from passive analysis to active engagement. In 2025, simply knowing your audience is no longer a competitive advantage; it's table stakes. The true differentiator for Web3 growth teams is mastering the distribution channels that allow for precise, effective, and ROI-positive engagement with on-chain audiences.

This guide serves as your updated 2025 map to the landscape of on-chain distribution. We will explore the five primary channels to reach wallet owners, analyzing the realistic reach, strategic value, and critical pitfalls of each, empowering you to navigate beyond analytics and into actual growth.

The Core Challenge: Attention is the New Scarce Resource

The foundational principle of Web3 marketing is that on-chain data is behavioral data fused with financial data. A wallet's history is a transparent ledger of intent, loyalty, and capability. However, this rich data is useless if you cannot get your message in front of the wallet owner in a way that captures their attention and drives action.

The channels available for this task vary wildly in their scale, precision, and complexity. Choosing the right one is not just a tactical decision; it's a strategic imperative that will define your customer acquisition cost (CAC), lifetime value (LTV), and ultimately, your project's success.

The Five Channels of On-Chain Distribution – A Detailed Analysis

1. Permissionless Public Channels (Airdrops 2.0): The Spam Graveyard

The concept is seductively simple: acquire a list of target wallets and broadcast your message or token directly to them. This is the purest form of permissionless, direct-to-wallet communication.

The 2025 Reality: This channel has largely collapsed under the weight of its own abuse. What was once a novel growth mechanism has become a vector for spam and scams. In response, wallet providers and dApps now aggressively filter and hide these unsolicited messages to protect users. The result? Abysmal impression rates and near-zero ROI.

• Realistic Coverage: Next to nothing. Your message is likely to be automatically flagged and never seen.

• Key Players (2025 Update): While projects like Venly and Novel attempted to build here, the model has proven commercially unviable. The space has moved on.

Strategic Lookout Points:

• Creative Bypass: Has a project developed a truly novel way to bypass spam filters and reach a user's primary interface? Most haven't.

• ROI Transparency: Since tracking views is nearly impossible, demand clear, auditable case studies on click-through rate (CTR) and conversion against budget. If they can't provide it, steer clear.

Verdict: In 2025, this is a channel for gamblers, not growth marketers. Avoid it for any serious user acquisition strategy.

2. Owned & Operated Platforms (Direct-to-Wallet Messengers): The Scale Problem

This approach involves building a dedicated platform where users willingly connect their wallets to receive messages, often in exchange for some utility or reward. Think of it as a Web3-native inbox or notification center. Projects like Dispatch and DeBank Hi pioneered this model.

The 2025 Reality: The fundamental challenge remains achieving critical mass. Building a large, active user base on a new platform is incredibly difficult in Web3. Any viable adtech business requires millions of monthly active wallets (MAW) to be a meaningful distribution channel. Furthermore, if the platform's sole purpose is to deliver ads, users simply won't use it. Success requires embedding ads within another must-use product (e.g., a portfolio tracker, a news aggregator, or a social platform).

• Realistic Coverage: Tens to hundreds of thousands of Unique Active Wallets (UAW). A respectable niche, but not mass-market.

• Key Players (2025 Update): The landscape has consolidated. Some early players have pivoted, while others have been absorbed into larger suites of tools.

Strategic Lookout Points:

• Real MAW Figures: Scrutinize claimed user numbers. Ask for verified, on-chain proof of active engagement, not just download counts.

• Cost Analysis: Advertising here is often prohibitively expensive. For example, DeBank Hi has been known to command a $1000+ CPM. You must calculate if the LTV of the acquired users justifies this extreme cost.

• Chain Agnosticism: Is the traffic limited to a single chain (e.g., Ethereum-only), or does it provide cross-chain reach relevant to your strategy?

Verdict: A potential high-cost, high-precision channel for reaching a specific, engaged niche. Demand absolute clarity on actual reach and costs before committing.

3. The Metaverse (Virtual Worlds): The Premium Niche for Branding

The "Metaverse" here refers to blockchain-based virtual worlds like Decentraland and The Sandbox where users own digital assets. Advertising involves placing branded billboards, building virtual experiences, or sponsoring events within these worlds.

The 2025 Reality: The grand vision of a billion-user metaverse has not yet materialized. Concurrently, user bases remain small. Furthermore, creating and placing ads is not as simple as uploading a banner; it often requires custom 3D development, making it expensive and lacking cross-platform compatibility.

• Realistic Coverage: Thousands to tens of thousands of UAW. It's a boutique channel.

• Key Players (2025 Update): Anzu, Landvault, and AdShares remain prominent players facilitating virtual land deals and ad placements.

Strategic Lookout Points:

• True Activity: How many daily active users does the platform genuinely have? Does the ad solution have direct access to the user's wallet for targeting and measurement?

• Development Overhead: Will you need to hire a dedicated development team to create your virtual ad placement? This can add significant time and cost.

• Tracking Capabilities: How will you track impressions, clicks, and conversions? Is there a clear analytics dashboard, or are you buying a "brand experience" with no measurable ROI?

Verdict: An overpriced niche channel for brand awareness and "clout" rather than performance marketing. Only consider it if your goal is prestige branding within a very specific community and you have a budget to match.

4. Decentralized Applications (dApps): The Workhorse of Web3 Advertising

This is the largest and most effective channel for performance-based marketing in Web3. Ad networks like Slise (now part of W3M Ventures) and Blockchain-Ads act as intermediaries, aggregating inventory from thousands of dApps—DeFi protocols, NFT marketplaces, blockchain explorers, and gaming platforms—and allowing advertisers to buy targeted placements across them.

The 2025 Reality: This channel wins on quality and intent. To even see an ad, a user must have a connected wallet, meaning every impression is delivered to a verified, active crypto user. The targeting is unparalleled: you can target based on wallet history, token holdings, and specific on-chain behaviors. The main limitation is the total size of the on-chain audience, though it's growing steadily.

• Realistic Coverage: Millions to tens of millions of UAW. This is where the core Web3 audience lives.

• Key Players (2025 Update): The industry has consolidated. Slise's acquisition by W3M Ventures has created a powerhouse combining on-chain data with traditional crypto ad inventory (like AADS). Blockchain-Ads is another major player, offering robust targeting and reporting.

Strategic Lookout Points:

• Network Reach: How many wallets on your target blockchain (e.g., Solana, Base, Arbitrum) does the network actually reach?

• Targeting Sophistication: Are you paying for blunt CPM, or can you leverage precise on-chain behavioral targeting to maximize ROI?

• Publisher Quality: What are the dApps in the network? Are they reputable, high-traffic sites, or a long tail of low-quality inventory? Demand transparency.

Verdict: The essential channel for any performance marketer in Web3. It offers the best combination of reach, targeting precision, and measurable ROI for acquiring high-intent users.

5. Finding Web3 Users on Web2 Platforms: The Frontier of Scale

This is the most technically complex but potentially highest-reward channel. It involves using on-chain data to target users on traditional Web2 platforms where they don't have their wallets connected—like Twitter, crypto publications, and programmatic ad networks.

The 2025 Reality: Solutions like Addressable have matured significantly. They use advanced heuristics to anonymously connect wallet addresses to social media profiles and other Web2 identifiers. This allows you to create a lookalike audience of your best wallet-based customers and target them with ads on major social platforms, effectively bridging the Web2-Web3 gap.

• Realistic Coverage: Millions to hundreds of millions of users. This is the channel for mass-scale reach.

• Key Players (2025 Update): Addressable is the leader in wallet-to-social targeting. Furthermore, platforms like Quest3 and Premint, while primarily used for giveaways, are effectively harvesting Web2 identifiers (Twitter, Discord, email) that could be used for future targeted outreach.

Strategic Lookout Points:

• Apples-to-Apples Comparison: Different providers use different methods. Demand case studies with clear metrics on CTR, CAC, and overall ROI.

• Traffic Quality: Is the audience made up of real potential users or just airdrop hunters and quasi-bots? Scrutinize the data.

• Data Ethics: Understand how the data is connected. Is it done in a privacy-compliant way that won't damage your brand's reputation?

Verdict: The strategic growth channel for 2025 and beyond. It allows you to apply Web3 intelligence to Web2 scale, making it indispensable for projects looking to break out of the core crypto niche and into the mainstream.

Strategic Integration and Future-Proofing Your Growth Engine

Choosing a channel isn't an exclusive decision. The most sophisticated growth strategies in 2025 involve a sophisticated mix:

1. Precision Acquisition: Use dApp ad networks (Channel 4) to acquire your first 10,000 high-LTV, core users cost-effectively.

2. Audience Analysis: Analyze the on-chain and social behaviors of your best converts using tools like Cookie3 or Spindl.

3. Scaled Expansion: Feed these insights into a platform like Addressable (Channel 5) to find and target lookalike audiences at scale on Web2 social platforms.

This creates a powerful, data-driven feedback loop where your on-chain results directly inform your off-chain acquisition strategy.

Conclusion: Distribution is the Final Boss of Web3 Growth

The journey from raw on-chain analytics to effective distribution is the defining challenge of Web3 growth. The map is complex, and each path has its own costs and trade-offs.

The key takeaway for 2025 is this: Move beyond the spammy, one-size-fits-all approaches of the past. The future belongs to strategies that respect user attention, leverage quality inventory, and use data not just for analysis, but for intelligent, cross-channel execution.

By understanding the realistic capabilities of each distribution channel, asking the right tough questions of providers, and integrating these tools into a cohesive strategy, you can finally unlock the true promise of on-chain data: not just to see your audience, but to truly reach them.

FAQ

What is the most cost-effective channel for early-stage Web3 projects?

For early-stage projects targeting genuine users, dApp ad networks (Channel 4) are typically the most cost-effective. They allow for hyper-targeted campaigns to users who are already actively using wallets and dApps, ensuring higher intent and better conversion rates despite a smaller overall audience size than Web2 channels.

How can I track the ROI of on-chain advertising campaigns?

This requires Web3-native attribution tools like Spindl or Cookie3. These tools can track a wallet's journey from seeing an ad in a dApp to ultimately completing a desired on-chain action (e.g., a swap, mint, or deposit) days or weeks later, providing a true measure of LTV and campaign ROI beyond last-click attribution.

Can I use these channels for non-financial dApps, like Web3 games or social apps?

Absolutely. The principle is the same: target wallets based on relevant behavior. For a game, you might target wallets that hold specific gaming NFTs or have interacted with similar game smart contracts. For a social app, target wallets active on platforms like Lens or Farcaster. The targeting is behavioral, not limited to DeFi.

What's the biggest mistake projects make with on-chain distribution?

The biggest mistake is prioritizing low cost over quality. Opting for channels with cheap CPMs (like some airdrop platforms or unvetted quests) often leads to acquiring a large volume of low-intent, mercenary users who drain resources and provide no long-term value, destroying your CAC/LTV ratio.

Is email marketing still relevant in a wallet-based strategy?

Yes, but through a Web3 lens. Platforms like Quest3 collect emails as part of giveaway mechanics. While primarily used for untargeted outreach now, this harvested data has the potential to be used for targeted email campaigns in the future if platforms develop that functionality, allowing for a Web2/Web3 hybrid approach.

These walled gardens are closed ecosystems where platforms aggregate vast troves of exclusive first-party user data—search histories, social connections, purchase behaviors, and content interactions. For advertisers, this data is the key to effective targeting. However, access is granted only through each platform's native advertising solution and is confined within their digital borders. An advertiser cannot use Facebook's rich social graph to target users on Google Search; the walls are designed to be impermeable.

This model created a devastatingly efficient moat. Independent ad networks, lacking direct access to user data, were left to compete with crumbs—inferior targeting based on third-party cookies and shady tracking, yielding poor results. The impending death of the third-party cookie in major browsers was the final act of this centralization play, a move that further cemented the oligopoly by destroying the independent ad tech that relied on them.

The Web2 advertising world is thus a kingdom divided into a few powerful fiefdoms, each ruled by a data baron. The user, whose data is the source of all value, is merely a serf—a product to be sold, with no ownership or control over their digital identity.

The Core of Monopoly: Exclusive Control of Scarce Data

The economic principle behind this dominance is simple: whoever controls the scarce, valuable resource controls the market. In Web2, that resource is behavioral and intent data. By hoarding this resource within their walls, Google and Meta became not just participants but the market makers, the rule setters, and the primary beneficiaries.

The network quality and algorithms are the cornerstones of ad giants of the future. And not an association with a particular consumer interface.

At 8:29 David Friedberg shares how the efficiency of Google’s ad exchange helped them build an actual monopoly around their ad network and lock the publishers in.

The Web3 Revolution – Permissionless Data and the Leveled Playing Field

Web3 introduces a fundamental paradigm shift that dismantles the very foundation of the Web2 advertising monopoly. The core tenet of Web3 is decentralization, and its most powerful weapon against data oligarchy is permissionless, public on-chain data.

On a blockchain, every transaction, every NFT mint, every DeFi interaction, and every governance vote is recorded on a public ledger. This doesn't just reveal a user's balance; it reveals a rich tapestry of their behavior, loyalty, financial capacity, and genuine interests.

• A Web2 data point: "Users are interested in sports cars." (Inferred from clicks and likes)

• A Web3 data point: "This wallet owns a Ferrari-themed NFT, has provided liquidity to a luxury car fractional ownership platform, and regularly trades on a Formula 1 prediction market."

The difference is not just quantitative; it's qualitative. On-chain data is behavioral data fused with financial data. It is more accurate, more action-oriented, and, crucially, it is not owned by any single corporation. It is a public good.

This accessibility neutralizes the Web2 moat. A new Web3 social media dApp doesn't need to build a data empire from scratch to compete with a giant. It can plug into the same rich, on-chain data universe that everyone else can access. The playing field is leveled. The question is no longer "Who owns the data?" but "Who can use the data most intelligently?"

The Publisher's New Power: Multi-Homing and Yield Optimization

This shift fundamentally changes the power dynamics for publishers (website and dApp owners). In Web2, publishers were often locked into a single ad network due to exclusive data partnerships. In Web3, because data is open, a publisher can simultaneously integrate multiple ad networks or decentralized exchanges (SSPs).

This practice, known as multi-homing, is rational and profitable. It allows publishers to:

• Auction inventory across multiple demand sources, driving up prices through competition.

• Ensure maximum fill rates by having backup demand sources.

• Optimize yield per user: Once a user is shown an ad from one network, their value to that network's algorithm might decrease. The publisher can then route the next impression to a different network, effectively selling the same user as "fresh" again and maximizing revenue.

This behavior alone makes a Google-like monopoly impossible. Why would a publisher be exclusive to one network when it can get a better deal by playing the entire field?

The New Battlegrounds – Algorithms, Privacy, and Infrastructure

In a world where data is a commodity, competition shifts to higher-order value propositions. The Web3 ad networks that thrive will be those that excel in three key areas:

1. Algorithmic Intelligence and Matching Efficiency

With data universal, the winner is the network with the most sophisticated algorithms to interpret it. Superior AI and machine learning will be needed for:

• Predictive Profiling: Forecasting a wallet's future actions and value based on its history.

• Real-Time Bidding Optimization: Dynamically matching the right ad with the right user at the right price across a fragmented network of publishers.

• Fraud Prevention: Using on-chain analysis to identify and filter out bot farms and sybil attacks, ensuring advertisers pay for real human attention.

As one source notes, "The network quality and algorithms are the cornerstones of ad giants of the future. And not an association with a particular consumer interface".

2. Privacy-Preserving and User-Centric Models

Web3 is inherently aligned with user sovereignty. The most successful networks will be those that embrace this ethos, moving beyond the "user as product" model.

• User-Owned Data: Projects are exploring models like DataDAOs, where users can pool their anonymized data and earn fees from advertisers who want to access it, fundamentally flipping the value equation.

• Zero-Knowledge Proofs (ZKPs): This technology will allow users to prove they belong to a valuable target demographic (e.g., "I am a whale in DeFi") without revealing their specific wallet address or transaction history, enabling privacy-focused hyper-targeting.

• Tokenized Incentives: Users may choose to opt-in to ad viewing in exchange for token rewards, creating a transparent value exchange rather than non-consensual tracking.

3. The Infrastructure Hurdle: The Need for Ad-Tech Specific Scaling

The original article correctly identified the primary obstacle to a fully decentralized vision: transaction speed and cost. Running a real-time ad auction on a mainnet like Ethereum is financially ludicrous for low-value impressions.

However, the landscape has evolved since 2023. The solution now points toward application-specific scaling:

• Ad-Tech L3s & Rollups: The development of specialized Layer 3 solutions or rollups built specifically for the ad tech industry is inevitable. These chains would be hyper-optimized for high-volume, low-cost, fast finality transactions, making micro-payments for impressions feasible.

• State Channels: Networks could use state channels to conduct thousands of off-chain auctions between participants, only settling the final net results on-chain, drastically reducing overhead.

This infrastructure is no longer a fantasy; it's a necessary evolution that is actively being built.

The Future Landscape – A Thriving Ecosystem of Specialized Networks

So, if not a monopoly, what will the Web3 advertising landscape look like in 2025 and beyond?

We will see a highly competitive and fragmented ecosystem of numerous players, each competing on specialization and value-add:

1. Vertical-Specific Networks: Networks that specialize in targeting specific sectors—e.g., one for DeFi power users, another for NFT collectors, another for gamers—will develop deeper expertise and better algorithms for their niche than any general-purpose network could.

2. Privacy-First Networks: Networks that build their brand on ZK-technology and user-centric data models will attract advertisers who value trust and compliance.

3. Decentralized Exchanges (DEXs) for Ads: Fully automated, smart contract-based ad exchanges (true "AdChains") will emerge for transparent, permissionless ad trading, though likely for specific, lower-fraud use cases initially.

4. Infrastructure Players: Companies that provide the critical L3 scaling, oracle data, and analytics APIs will become the hidden giants, powering the entire ecosystem.

This vision aligns with the broader Web3 ethos of composability and modularity. Growth will become "protocol-native," integrated into the very fabric of how dApps operate, through quests, rewards, and on-chain loyalty programs, moving far beyond mere banner ads.

Conclusion: A More Equitable and Exciting Future

The future of advertising is not a single walled garden grown to engulf the world. It is a vast, open forest with many different species of trees, each thriving in its own niche.

Web3, by its very architectural design, prevents the re-emergence of the data monopolies that defined Web2. The key ingredients of monopoly—exclusive data ownership and platform lock-in—are technologically impossible in a world of open ledgers and composable protocols.

The competition won't be about who builds the highest walls, but who builds the smartest algorithms, the fairest economic models, and the most scalable infrastructure. This means a better deal for everyone: publishers earn more, advertisers achieve higher ROI through better targeting, and users finally transition from being the product to being valued participants and stakeholders in the digital economy.

The path is clear. The future of advertising won't be built by a new Google; it will be built by a thriving, decentralized ecosystem where value is distributed, not hoarded. And that is a future worth building for.

FAQ

If data is open, won't the biggest network still win due to scale?

Not necessarily. In Web2, scale mattered because it created exclusive data. In Web3, scale without efficiency is meaningless. A smaller, specialized network with superior algorithms for a specific vertical (e.g., NFT gaming) will consistently outperform a larger, less efficient general network for advertisers seeking that audience. Competition will be on merit, not on data ownership.

How can users control their data without hurting advertising effectiveness?

Through selective and compensated participation. Users can opt-in to share specific data segments via privacy-preserving tech like ZK-proofs or join DataDAOs, earning revenue from their data. This ensures ads are highly relevant (because users consciously allow it) and ethical, creating a more engaged and positive response than invasive tracking.

Are there any real-world examples of successful Web3 advertising models?

Yes. Protocols like Optimism and LayerZero have pioneered "protocol-native growth." Instead of buying ads, they use targeted airdrops and reward programs based on precise on-chain actions (e.g., bridging assets, using specific dApps). This has proven to drive higher retention and more valuable user acquisition than traditional advertising.

What is the biggest technical challenge facing decentralized advertising?

Transaction throughput and cost. Mainnet blockchain transactions are too slow and expensive for real-time ad auctions. The solution lies in application-specific L3 rollups—blockchain layers built solely for ad tech that can handle millions of low-cost transactions per second, making micro-payments for impressions feasible.

How will we measure success in this new paradigm?

Success metrics will shift from vanity metrics like impressions and clicks to on-chain conversions and lifetime value (LTV). The focus will be on tracking a wallet's journey from seeing an ad to performing a valuable on-chain action (e.g., a deposit, trade, or mint), allowing for true ROI calculation based on blockchain-attributable outcomes.

In a move that signals both maturation and consolidation in the nascent Web3 advertising sector, investment firm Web3 Media Ventures (W3M Ventures) has announced a definitive agreement to acquire Slise.xyz, the largest and most innovative Web3-native advertising platform. This acquisition, finalized in December 2024, is far more than a simple business transaction; it is a strategic gambit to unify and dominate the future of privacy-focused, on-chain digital marketing.

For years, advertising in the crypto and blockchain space has been a paradox. While the industry is built on data-rich, transparent ledgers, its marketing efforts have largely relied on the same blunt, privacy-invasive tools of Web2: social media blasts, influencer promotions, and traditional ad networks that fail to leverage the unique potential of on-chain behavior.

Slise, founded in 2022 by a team of Y Combinator alumni, emerged as a pioneer to solve this exact problem. By leveraging anonymized on-chain data, Slise provided a way for brands to deliver hyper-relevant ads across a network of decentralized applications (dApps), blockchain explorers, and Web3 gaming platforms—all without relying on cookies or compromising user privacy. Their client roster, including giants like PayPal, MetaMask, Revolut, and OKX, is a testament to the product's market fit and effectiveness, reaching over 6 million active crypto-users.

This acquisition by W3M Ventures, a firm with deep roots and a diverse portfolio in crypto ad tech (including the legacy network AADS), represents a pivotal consolidation of power. It combines Slise's cutting-edge, data-driven technology with W3M's extensive resources, market reach, and strategic vision. This article provides a comprehensive analysis of the deal, the players involved, the technology at its core, and the profound implications for advertisers, publishers, and the entire Web3 ecosystem.

"The acquisition of Slise represents a pivotal moment in our journey to revolutionize digital advertising for the Web3 era," the spokesperson for W3M Ventures said. "Their groundbreaking technology aligns perfectly with our vision of creating more effective, privacy-centric advertising solutions for the decentralized web."

Oleksii Sidorov, Co-founder & CEO of Slise, added, "W3M Ventures is the perfect catalyst for Slise’s growth as they have experience and resources to accelerate the adoption of onchain data in digital advertising space for a more fair and transparent future. The team and I couldn’t be more excited to make our contribution to this change."

Reflecting on the journey, Oleksii shares insights into the growth and development of the company during crypto-winter:

“The beginning of Slise coincided with the collapse of Luna and later FTX which initiated a downturn of the crypto market. Economically, it didn’t make any sense, only our belief in the potential of onchain data for ads pushed us forward.

It wasn't a smooth journey, very few VCs shared our beliefs. Slise didn’t close huge rounds despite later having 6-digit revenue, neither did we receive countless grants, we were underdogs, surviving, while our token-first competitors raised tens of millions before even having a product.

I don’t think the crypto market incentivizes building good products. Only independent thinking from first principles took us where we are now. We’ve never sponsored a side event or entertained people on X, instead, we stayed frugal and focused on client acquisition and operational efficiency. This all helped us build a business value and a dominant market position which W3M Ventures acquires today.”

The Strategic Rationale: Why This Deal Makes Sense

For W3M Ventures: Acquiring the Future

W3M Ventures' acquisition is a masterclass in strategic portfolio development. Their existing holdings, like AADS, represent the "old guard" of crypto advertising—effective for broad reach but lacking the sophisticated targeting capabilities of modern Web2 platforms. By acquiring Slise, W3M instantly:

1. Captures the Technological High Ground: Slise's on-chain data targeting engine is its crown jewel. Instead of building this complex, defensible technology from scratch, W3M acquires a proven, market-leading solution.

2. Future-Proofs Against Privacy Regulations: With the demise of third-party cookies and increasing global data privacy laws (GDPR, CCPA), the industry is scrambling for solutions. Slise's privacy-centric model, which uses public, anonymized blockchain data rather than personal information, is inherently compliant and positioned for the future.

3. Unlocks Cross-Selling Opportunities: W3M can now offer a full-funnel advertising solution. Advertisers can use AADS for broad brand awareness campaigns and Slise for hyper-targeted, performance-driven campaigns based on precise user behavior, all under one corporate umbrella.

4. Consolidates Market Leadership: Bringing the largest Web3-native platform under its wing establishes W3M Ventures as the dominant force in the space, creating a powerful moat against competitors.

For Slise: Scaling with Amplified Resources

For Slise's founders and team, the acquisition is a validation of their vision and a catalyst for accelerated growth. As co-founder and CEO Oleksii Sidorov hinted, the journey was arduous. Building B2B infrastructure during a brutal "crypto winter" required immense grit and frugality.

By joining W3M Ventures, Slise gains:

• Significant Capital and Resources: Access to deeper pockets for R&D, sales expansion, and marketing, far beyond what was possible as a lean, bootstrapped-focused startup.

• Established Industry Connections: W3M's vast network within the crypto and advertising worlds opens doors to larger enterprise clients and premium publisher inventory.

• Operational Support: Back-office functions like legal, HR, and finance can be handled by the parent company, allowing the Slise team to focus purely on product and technology.

The Technology Behind the Headline - On-Chain Advertising Explained

To understand why this acquisition is so significant, one must understand the technological leap that Slise represents. Traditional digital advertising relies on a fragile ecosystem of cookies, device IDs, and trackers that follow users across the web, building profiles often without their explicit consent. This model is crumbling.

Web3 advertising, as pioneered by Slise, is fundamentally different. It is built on three core principles:

1. Permissionless, Public Data: Every transaction on a blockchain is public. While wallet addresses are pseudonymous, they represent a rich tapestry of behavior: which DeFi protocols a user interacts with, which NFTs they collect, which chains they prefer, and their level of experience (e.g., a wallet that uses advanced protocols like EigenLayer versus one that just holds ETH).

2. Anonymized Targeting: Slise's genius lies in its ability to analyze this public data without needing to know who the user is. They can identify clusters of wallets that exhibit similar behaviors (e.g., "users who provided liquidity on Uniswap V3 in the last 30 days" or "holders of a specific NFT collection"). Ads are targeted to these behavioral clusters, not to individual identities.

3. Contextual Placement in Web3 Environments: Slise's ads are natively integrated into the Web3 user experience—inside dApp interfaces, on blockchain explorer sites, and within crypto gaming platforms. This ensures ads are not just targeted but also contextually relevant, appearing where users are already engaged in financial or exploratory activity.

A Practical Example:
Imagine a new, sophisticated DeFi protocol that wants to attract knowledgeable liquidity providers. On a Web2 platform, they might target users who visited CoinGecko or searched for "APY." It's imprecise.

Using Slise, they can directly target wallets that have:

• Interacted with similar DeFi protocols (Compound, Aave).

• Have a history of providing liquidity above a certain threshold.

• Hold governance tokens from other DeFi projects.

This targeting is infinitely more precise, privacy-preserving, and likely to yield a higher ROI for the advertiser. This is the technology W3M Ventures has now acquired.

Leadership and Market Context: Building Through the Crypto Winter

The backstory of Slise is a classic tale of resilience and conviction. Founded at the precipice of a major market downturn following the collapses of Luna and FTX, the company defied economic logic. As Sidorov noted, "Slise didn’t close huge rounds despite later having 6-digit revenue, neither did we receive countless grants, we were underdogs, surviving, while our token-first competitors raised tens of millions before even having a product."

This focus on product-market fit and operational efficiency over hype and fundraising is what ultimately built a sustainable business. They proved that there was real, monetizable demand for effective advertising in Web3, even when token prices were down. This profitability, announced in February 2024, made them an exceptionally attractive acquisition target—a real business with real revenue, not just a whitepaper and a token.

The acquisition also highlights a broader trend in the Web3 space: the shift from speculative tokenomics to sustainable B2B SaaS models. While the flashy, token-funded projects often falter post-hype, the quiet builders solving real business problems (like Slise) are becoming the most valuable assets.

What This Means for Different Stakeholders

• For Advertisers (Brands like OKX, MetaMask): This is unequivocally positive. They can expect a more robust, integrated suite of advertising tools from the W3M portfolio. The targeting will become even sharper as Slise's technology is enhanced with W3M's resources. They gain a one-stop-shop for both broad and targeted Web3 campaigns.

• For Publishers (dApps, Explorers): Publishers in the Slise network can expect greater stability and potentially higher yields. With W3M's sales force, more major brands will be onboarded onto the platform, increasing demand for premium ad inventory. The technology stack is also likely to see accelerated development.

• For Users: The core value proposition remains: relevant ads without privacy invasion. Users see offers for products and protocols they are genuinely likely to be interested in, based on their on-chain actions, without their personal data being bought and sold behind the scenes.

• For Competitors: The bar has been raised significantly. Smaller, independent Web3 ad networks will now be competing with a behemoth that combines legacy reach with next-generation technology. This acquisition will likely spur further consolidation in the market as others seek similar partnerships.

The Future: Integration and Innovation

The official press release notes that the integration is expected to be completed within the next quarter. The key challenges and opportunities will be:

1. Technical Integration: Merging Slise's advanced platform with W3M's existing properties like AADS to create a seamless experience for advertisers.

2. Cultural Integration: Ensuring the innovative, agile spirit of the Slise team thrives within the larger W3M structure.

3. Product Expansion: The mention of Slise's core team moving to a new non-competing product, Dise.app (an AI-powered Sales CRM for crypto teams on Telegram), is fascinating. It suggests W3M primarily acquired the Slise business and technology, not necessarily the entire team long-term, though they will aid the transition. This allows the founders to innovate anew while W3M's dedicated management scales the advertising platform.

Conclusion: A Watershed Moment

The acquisition of Slise by Web3 Media Ventures is a watershed moment for Web3 advertising. It validates the entire premise of on-chain, privacy-centric marketing and moves it from a niche experiment to a mainstream, scalable business model within the portfolio of a major industry player.

It proves that sustainable growth, even in a bear market, built on real revenue and a superior product, is the most reliable path to success. For the entire ecosystem, this deal promises a more professional, effective, and privacy-respecting future for how projects find their users and how users discover new opportunities in the decentralized world. The race to build the advertising infrastructure of Web3 is on, and with this move, W3M Ventures has taken a commanding lead.

FAQ

What does W3M Ventures do?

Web3 Media Ventures (W3M Ventures) is an investment firm with a focused portfolio of equity and digital asset holdings in Web3 and advertising technology (adtech) companies. They have expertise in crypto-enabled advertising and invest in platforms that shape the future of digital marketing.

What was Slise's business model?

Slise operated as a programmatic advertising platform. They monetized by acting as an intermediary between advertisers (e.g., crypto wallets, exchanges) and publishers (e.g., dApps, blockchain websites). They likely used a model based on CPM (Cost Per Mille) or CPC (Cost Per Click), taking a fee for facilitating the targeted placement of ads using their on-chain data technology.

How does on-chain advertising protect privacy?

It uses public blockchain data that is already anonymous. Slise's system analyzes transaction histories and behaviors linked to wallet addresses, but it does not require or use personally identifiable information (PII) like names, emails, or IP addresses. The targeting is based on what a wallet does, not who the user is.

Will Slise's platform change after the acquisition?

Clients and partners should expect the platform to be enhanced. In the short term, the service will continue as normal. In the long term, W3M Ventures will likely integrate Slise's technology with its other properties (like AADS) to offer a more comprehensive suite of advertising tools, potentially under a new unified brand.

What is Dise.app?

Dise.app is a new, separate venture by the original co-founders of Slise. It is an AI-powered Customer Relationship Management (CRM) tool designed specifically for sales teams operating on Telegram, a key communication platform in the crypto industry. It is stated to be non-competing with Slise's advertising business.

For press inquiries:
founders@slise.xyz

However, this scale masks a critical, profit-draining flaw: the profound disconnect between impression volume and user quality.

The core issue lies in the audience itself. The vast majority of these Web2 websites, while rich in pageviews, are poor in on-chain intent. They are informational hubs, not transactional platforms. A user reading an article on "The Future of DeFi" is not necessarily a DeFi user. They might not even own a cryptocurrency wallet.

Consider this stark reality: A top-tier crypto news site might attract 100 million monthly visits, but the actual number of daily active on-chain wallets historically sits in the range of a few million (as per DappRadar and other analytics firms). This means that without hyper-specific targeting (which traditional Web2 networks like Coinzilla struggle to provide), a staggering 98% or more of your advertising budget is likely being spent on users who lack the basic qualification for using your product: an active wallet and the intent to use it.

You're not just paying for irrelevant clicks; you're funding a digital facade. This leads to abysmally low click-through rates (CTRs), minimal engagement, and a cost-per-acquisition (CPA) that makes sustainable growth impossible. Your dashboard might show "impressions," but your treasury shows an outflow with little to show in return.

This guide is the red pill. We will expose the limitations of the easy path and chart a course toward authentic, valuable user acquisition by exploring five powerful alternatives to Coinzilla, complete with their own sets of advantages and harsh realities.

1. The Web2 Fallacy: When "Crypto-Related" Isn't "Crypto-Capable"

The first alternative many consider is simply shifting budgets to other Web2 ad networks like Bitmedia or Cointraffic. On the surface, this seems logical. They operate on the same model, often even sharing similar publisher inventories, and they are notoriously lenient with token offerings and gambling ads.

The Bitter Truth:
You are playing a game of musical chairs within the same crowded, noisy room. You're competing for the same broad, often unqualified attention. These networks excel at generating volume—Bitmedia alone claims over 1 billion monthly impressions —but they inherit the same fundamental weakness: an audience that is passively informed rather than actively engaged.

The good:
Such solution have their benefits: they have a huge volume of traffic that you won’t be able to exhaust, and can sell it quite cheap. Also, they seem to have no limitations to working with token offerings and gambling ads.

The bad:
But they also inherit all the drawbacks of web2-native traffic, with its low quality, minimal engagement and bottom-low CTRs, and little relevancy for Web3 projects. As a result, they got used mostly for casinos and token pumps.

When to Use It: This approach can be marginally useful for top-of-funnel brand awareness campaigns for exchanges or wallets targeting the curious-but-not-yet-active crowd. It is virtually useless for performance-driven goals like driving protocol interactions, NFT mints, or dApp usage.

2. Web3-Native Advertising: Targeting the On-Chain Elite

This is the paradigm shift. Instead of chasing the masses on Web2 sites, Web3-native ad networks like Slise and the now industry-leading Blockchain-Ads flip the script. They focus exclusively on placing ads within dApps—the decentralized applications where real on-chain activity happens.

Think DeFi protocols like Uniswap or Compound, NFT marketplaces like OpenSea, blockchain explorers, Web3 games, and analytics dashboards. To even see an ad here, a user must have a connected wallet. This single requirement acts as a perfect filter.

The Audience: This is the 2 million-strong core of the crypto economy. They are not readers; they are actors. They hold assets, provide liquidity, trade NFTs, and govern protocols. Their lifetime value (LTV) is orders of magnitude higher than a casual reader's.

The Bitter Truth:
You pay a premium for this privilege. CPMs on these networks are significantly higher than on Web2 networks. Furthermore, the total reach is limited by the entire population of active on-chain users. You cannot scale to 100 million users here because they don't exist yet.

The good:
Highest-quality traffic of crypto-natives that is impossible to find otherwise, much higher CTR, and the possibility to do targeting based on the wallet history and onchain assets. High LTV of the acquired users for the project in comparison to users who don’t have crypto assets and have to be onboarded.

The bad:
Rather limited reach due to the small size of the whole Web3 space, and a higher price of CPM than in Web2 sources, which could go even higher for targeted segments. Although, it should be compared, and sometimes the price can be on par with traditional Web2 traffic.

When to Use It: This is the optimal channel for performance marketing. Use it for driving high-value actions: smart contract interactions, premium NFT minting, protocol deposits, and targeted user acquisition for B2B2C products (wallets, infrastructure). The case study of Blockchain-Ads driving a 340% increase in protocol interactions for Compound is a testament to its power.

3. Twitter ads

Twitter remains the unofficial town square of crypto. It's where news breaks, communities gather, and influencers hold court. Unlike Google and Meta, its advertising policies are far more accommodating to crypto projects.

The Bitter Truth:
Twitter is still a Web2 platform. While you can target users based on their interests (e.g., "follows Vitalik Buterin" or "interested in NFTs"), you are targeting their social persona, not their on-chain identity. A prolific crypto Twitter user might have a wallet with $10 in it, or they might be a bot farm designed to farm airdrops. The platform is also rife with spam and scams, which degrades overall user engagement with ads.

The good:
Good chance to find real crypto users with precise targeting, but expect that CPM in that case will be comparable to Web3 ads. Best place to promote your Twitter account and build a social presence. Less so acquire paying customers.

The bad:
Hard to segment real crypto-users from all the other users of twitter and especially bots. More often than not twitter accounts do not translate into active wallets and exist purely for social activity and rewards. A high amount of spam and scam that lower user engagement with paid ads.

When to Use It: Excellent for brand building, announcing news, and driving traffic to your website or Twitter profile. It's less effective for directly acquiring paying customers or driving on-chain actions unless paired with a very compelling offer and a highly optimized funnel.

4. Rewarded-Quest Platforms: Buying Vanity Metrics

Platforms like Galxe, QuestN, and Zealy offer a seductive proposition: rapid user growth. They incentivize users to complete tasks (follow on Twitter, join Discord, make a small deposit) in exchange for points, tokens, or eligibility for future airdrops.

The Bitter Truth:
You are not building a user base; you are renting a mercenary audience. The vast majority of participants are airdrop hunters operating dozens of accounts and users from developing nations seeking micro-rewards. Whales, serious traders, and developers do not spend their days clicking through quests for petty rewards. The retention rate is catastrophic.

The good:
Very cheap cost of acquisition (CPA), and a quick way to bump up the vanity metrics for social proof or other needs. Ability to grow your social channels as well as your product.

The bad:
Close to zero retention and almost no difference from the bot traffic. Be assured, even that small fraction of real users that will come from quests will come for a reward, not for the product. Such users do not build a strong user base and do not improve important product metrics. Easy come—easy go.

When to Use It: Use it with extreme caution, only for specific, short-term goals like boosting initial Discord member numbers for social proof or running a known, one-off promotional campaign. Never consider it a core user acquisition strategy.

5. Doing an airdrop

Airdrops is by far the most mysterious user acquisition channel in crypto. The process implies spending money not on the traffic, but on the rewards to your existing users and expecting that a wider audience will get to know about it through word-of-mouth and will want to become your users to not miss another airdrop.

There are a lot of fundamental problems with the model, but what’s the worst, is that it actually works. For a crypto audience mostly driven by financial incentives and a chance to get rich, such an opportunity sounds really sexy, and the FOMO pushes even adequate users to simulate activity on a protocol to get the chance to receive the next drop.

To be more realistic, airdropping means giving away money, and not cents, as you would pay for an ad impression, but hundreds of dollars to a single user. How this works out in the CAC model nobody really counts, but hey, the numbers go brrr, just as with quests, making middle-level marketers looks genius for growing the KPI.

The good:
It’s an efficient way to grow your short-term user base via social FOMO and by “buying” users. Huge benefit: you can do it with your token and not real money, which is easier to print.

The bad:
Users that come for airdrop come for a reward, not your product, and they will leave even faster than they came once they are able to cash out that reward.

When to Use It: Airdrops should be treated as a strategic economic event, not a marketing tactic. They should be designed with vesting schedules, sybil resistance mechanisms (like those used by LayerZero), and a clear goal of rewarding true, loyal early users, not just anyone who performed a one-click interaction.

Conclusion: Building Authentically in a World of Quick Fixes

The path to sustainable crypto growth is not paved with vanity metrics and low-cost clicks. It is built by strategically investing in channels that deliver valuable, capable users.

The bitter truth is that quality acquisition is expensive and complex. There is no magic bullet. The winning strategy involves:

1. Audit Your Funnel: Know your true Cost to Acquire a Customer (CAC) and Lifetime Value (LTV). Without this, you're marketing in the dark.

2. Embrace Web3-Native Precision: Allocate a significant portion of your budget to networks like Blockchain-Ads that can target based on on-chain behavior. This is your highest-probability channel for real users.

3. Use Twitter for Community, Not Just Conversion: Leverage its reach for storytelling and brand building, but track how effectively it drives on-chain actions.

4. Avoid the Vanity Trap: Radically deprioritize quest platforms and unstrategic airdrops. Focus on retention, not just sign-ups.

5. Test and Iterate: The landscape changes monthly. Continuously A/B test your messaging, creatives, and channel mix.

In 2025, the crypto market is more competitive than ever. Survival doesn't go to the projects with the biggest marketing burn; it goes to those who are the most strategic, data-driven, and authentic in how they find and keep their users. Choose your channels wisely.

FAQ

What is the main difference between Web2 and Web3 ad networks?

Web2 ad networks (like Coinzilla, Bitmedia) place ads on informational websites (news, blogs). The audience is broad but unqualified, as most users do not have a connected wallet. Web3 ad networks (like Blockchain-Ads, Slise) place ads within functional dApps (DeFi protocols, NFT marketplaces). The audience is smaller but consists entirely of active, wallet-connected crypto users with a much higher intent to interact.

Why is Twitter not considered a Web3 platform for ads?

While Twitter is the social hub for crypto, its advertising platform is still built on Web2 infrastructure. It can target users based on interests and social graphs but lacks access to on-chain data. This means you cannot target users based on their wallet balance, NFT holdings, or transaction history, which is the most reliable indicator of a valuable user.

Are there any crypto ad networks with no minimum spend?

Yes, some networks are more accessible. Bitmedia and A-Ads are known for having no minimum deposit requirement, making them easier for smaller projects to test. However, remember that low cost often correlates with lower-quality traffic.

What is the most important metric for evaluating a crypto ad campaign?

While click-through rate (CTR) and cost-per-click (CPC) are useful, the only metrics that truly matter are on-chain conversions. This could be the cost to acquire a user who makes a deposit (CPA), completes a trade, or interacts with your smart contract. Tracking these requires on-chain analytics tools.

Can I use a combination of these channels?

Absolutely. A sophisticated strategy often involves a mix:

• Web2 Networks: For broad, top-of-funnel awareness.

• Web3 Networks: For high-intent, performance-driven acquisition.

• Twitter: For community engagement and announcement amplification.
  The key is to track each channel's contribution to your final on-chain goal, not just intermediate metrics like website clicks.

In our previous analysis, we argued that this era of centralized dominance is fundamentally incompatible with the core tenets of Web3. The primary reason is the wide accessibility of rich on-chain data and the deliberate lack of control granted to any single entity. Blockchain's inherent transparency means that the most valuable behavioral and financial data—what a wallet owns, where it transacts, what protocols it uses—is a public good, not a proprietary asset.

This dismantles the very foundation of Web2 ad monopolies. But it raises a critical question: if not a monopoly, then what? What does a healthy, dynamic, and fair advertising market look like when data is free-flowing and no single player can hoard it?

This article argues that the Web3 advertising market of 2025 will not be a winner-take-all arena but a highly competitive ecosystem of specialized networks. Success will be determined not by data ownership, but by superior technology, strategic partnerships, and the ability to create and capture value in novel ways. We will explore the two core pillars of competition in this new landscape—network effects and algorithmic intelligence—and analyze the emerging framework for value distribution.

The Publisher's Dilemma: Price is King, But What Drives Price?

The desire of a publisher to work with an ad provider is ultimately defined by one simple metric: the price the provider can pay for their inventory. In Web2, this price was largely a function of data. A platform with richer, more exclusive data could command higher CPMs from advertisers and, in turn, share more revenue with publishers.

In Web3, with data democratized, this traditional lever is neutralized. If every network has access to the same on-chain data, what becomes the new basis for competition? The answer lies in two interconnected areas: the efficiency of the network and the intelligence of the algorithms that power it.

The New Pillars of Competitive Advantage in Web3 Advertising

1. The Network Effect: Scale, Liquidity, and Multi-Homing

A fundamental truth of ad tech remains: a wider network of users and advertisers leads to more efficient matching. A larger network can find more tailored offers for each individual user, maximizing the value of every impression. A large network will inherently be more effective and able to pay more than a small one or a simple 1:1 partnership.

However, the nature of "winning" the network is different in Web3. The traditional ad tech landscape is not a series of isolated silos; publishers almost always integrate multiple ad networks and even expose their inventory to larger cross-network auctions through Supply-Side Platforms (SSPs). This practice, known as multi-homing, is rational and beneficial for publishers.

Why Multi-Homing is Rational for Publishers:

• Price Competition: Multiple bidders create a competitive auction, driving up the price for premium inventory.

• Demand Redundancy: It provides a backup source of demand, ensuring fill rates remain high even if one network's demand dips.

• User Yield Optimization: As a user is exposed to more ads, they exhaust the immediate demand within a single network, causing effective CPMs to drop. It becomes a sound financial decision for a publisher to effectively "refresh" that user by exposing them to a different network's demand pool, even if the ads are similar.

It is therefore naive to think publishers will become monogamous in Web3. They will route traffic to the providers that pay the most. This creates a fascinating challenge: in a world where data is equalized, how can any one provider consistently pay more? The answer pushes competition to the next level.

2. The Algorithmic Edge: Intelligence as the New Moat

When everyone has access to the same raw data and a similarly sized network, the winner is the one who can process that data more efficiently and interpret user intent more accurately. Competitive advantage shifts from data hoarding to data intelligence.

This algorithmic superiority operates on multiple layers:

• Predictive Wallet Profiling: Moving beyond past transactions to predict future behavior and purchase intent.

• Campaign Optimization: Using AI to dynamically adjust bids, creatives, and targeting parameters in real-time to maximize advertiser ROI.

• User Ranking & Audience Optimization: Intelligently segmenting audiences not just by what they hold, but by their potential value to specific advertiser verticals.

• Fraud Prevention: Deploying advanced machine learning models to identify and eliminate sophisticated bot traffic and sybil attacks, ensuring advertisers pay for real human attention.

The ultimate output of superior algorithms is a consistently higher Click-Through Rate (CTR). A higher CTR creates more value from the same raw traffic, allowing the network to command higher prices from advertisers and share more revenue with publishers. This creates a virtuous cycle: more revenue attracts more publishers, which increases inventory supply and data signals, which further improves the algorithms.

The 2025 Perspective: The original article noted a scarcity of AI/ML talent in Web3 marketing. This has changed dramatically. The acquisition of Slise by W3M Ventures in 2024 was a testament to the value of this expertise, bringing sophisticated AI capabilities from the traditional tech world into the Web3 ad stack. Today, algorithmic intelligence is the primary battleground.

Analyzing the Web3 Advertising Landscape Through Porter's Five Forces

The intensity of competition in Web3 advertising can be powerfully analyzed using Michael Porter's Five Forces framework, which reveals a market that is inherently more competitive and less monopolizable than its Web2 predecessor.

Porter's Five Forces Analysis of Web3 Advertising:

As the table illustrates, competition is intensified across all five forces in Web3. The open nature of the technology lowers barriers to entry, empowers publishers and advertisers, and makes it easy for substitutes to emerge. This makes the formation of a stable mono- or duopoly nearly impossible.

The Path to Value Capture: Embeddedness and Community Cohesion

In this hyper-competitive environment, how can a Web3 ad network build a defensible advantage? The a16z analysis points to two key concepts:

1. Embeddedness: A protocol can become a standard "Lego block" embedded in many other systems. The more a network's infrastructure is composable and integrated into the core workflows of dApps, wallets, and analytics platforms, the higher the switching cost and the more defensible its position becomes.

2. Community Cohesion: Networks that foster a strong sense of community among publishers and advertisers—potentially through token-based incentives, governance participation, or shared growth—can create loyalty that transcends pure price competition. When users are emotionally and financially invested in a platform's success, they are less likely to churn.

"Splitting the Pie" – A Fair Framework for Value Distribution

The term "splitting the pie" is a powerful metaphor for value distribution, famously applied to negotiation and startup equity. In Web3 advertising, the "pie" is the total value created by a successful ad transaction: the advertiser's gain from a conversion minus their costs, which includes the revenue paid to the publisher and the ad network's margin.

The Web2 model often saw the platform take a disproportionately large slice of this pie, justified by its ownership of the data and the audience.

The Web3 model, by contrast, necessitates a fairer split. The publisher's traffic and the advertiser's budget are the essential ingredients. The ad network's role is that of a chef who efficiently combines them. Its fair value is not based on owning the kitchen (the platform) but on the skill and efficiency (the algorithm) with which it prepares the meal.

A fair and sustainable model, therefore, aligns incentives:

• Publishers are compensated transparently for their valuable user attention.

• Advertisers pay only for performance and high-intent users, maximizing their ROI.

• Ad Networks earn their margin based on their ability to optimize the value creation process for both sides, not through rent-seeking on data.

This fair distribution is not just ethical; it's a competitive necessity. In an environment where publishers and advertisers have high bargaining power, networks that attempt to capture an unfair share of the pie will simply be bypassed.

Conclusion: A Collaborative, Positive-Sum Future

The Web3 advertising market of 2025 is not a zero-sum game where one platform's gain is another's loss. The ethos of Web3, even amidst robust competition, is a common effort to grow the size of the pie for all.

The path to value creation is collaborative. It's about building superior algorithms that make the entire ecosystem more efficient. It's about creating standards and infrastructure that become embedded in the fabric of Web3. It's about fostering communities that are invested in mutual success.

We will not see a new Google or Meta in Web3. Instead, we will see a fair distribution of traffic and revenue between multiple strong players, with their market shares weighted not by data monopolies, but by their algorithmic advancement, strategic embeddedness, and ability to foster trust and collaboration.

The future of advertising is not a walled garden presided over by a single giant. It is a thriving, open, and competitive marketplace where value is earned through innovation and fairness, not controlled through ownership. The pie will be bigger, and the slices, while more numerous, will be more justly distributed.

FAQ

Won't the biggest Web3 ad network just become the new Google?

No. The fundamental economics prevent it. In Web2, Google's moat was its exclusive ownership of user data and search intent. In Web3, on-chain data is public and accessible to all. A network might achieve temporary leadership through better technology, but the low barriers to entry and the ease with which publishers multi-home mean that any attempt to abuse dominance by raising fees or lowering publisher payouts will be quickly punished by the market as traffic moves to more efficient competitors.

How can a small ad network compete without exclusive data?

Its competitive advantage must be built on specialization and algorithmic excellence. A small network could focus on a specific vertical (e.g., DeFi power users, NFT collectors, gamers), developing deeper expertise and better targeting algorithms for that niche than a general-purpose network. It can also compete on service, fee structure, and integration ease, leveraging the composability of Web3 to embed itself in specific ecosystems.

What role do tokens play in this competitive landscape?

Tokens can be a powerful tool for creating community cohesion and embeddedness. A network could use a token to:

• Reward publishers and advertisers for participation.

• Offer discounts on fees for token holders.

• Govern key protocol parameters.
  This creates a loyal ecosystem where participants are financially and governance-wise invested in the network's success, adding a layer of defensibility beyond pure technology.

How does this fairer model benefit advertisers?

Advertisers win through transparency and performance. They can clearly see what they are paying for and can track on-chain conversions directly to specific campaigns and networks. The intense competition between networks forces continuous innovation in targeting and optimization, driving down customer acquisition costs and improving ROI. They are no longer locked into a single platform's black-box algorithm.

Is this model sustainable for ad networks themselves?

Yes, but it requires a shift in mindset. The profit model moves from rent-seeking to value-creation. Networks will earn sustainable margins by taking a fair cut for the tangible value they provide: connecting advertisers to the right audiences with unparalleled efficiency. Their profit is a function of their ability to grow the overall pie for their clients, ensuring long-term alignment and sustainability.