AdTech and Growth: A Web3 Perspective
Special thanks to Justin (Safary), Joe (HypeLab), Anton (Helika), Filip (Cookie3), Oleksii (Slise) for their insightful comments that helped shape this article.
What is AdTech and how does it work in Web2?
That’s the revenue that Google, Facebook, and Amazon earned from their advertising segments in 2022. 97.5% of Facebook’s revenue share and 80.2% of Google’s revenue comes from their advertising services. If the sheer magnitude of these numbers made you wonder why there was no chatter about advertising tech at any of the recent Web3 conferences, you are not alone.
Often abbreviated as AdTech, advertising technology is perhaps the most important factor of your internet browsing and social media experience. In the conventional sense, AdTech refers to all technological services and infrastructure involved in buying, selling, serving, tracking and analyzing digital ads and campaigns. On a very high level, AdTech has three main players:
- Publishers: They are the owners or suppliers of digital advertising space. For instance, news and media content distribution channels (eg. The New York Times, Warner Bros.), podcasts, video content creators (eg. YouTube channels, TikTok creators), games, and software platforms
- Advertisers: They are the buyers of the ad space that publishers supply. For example, if Samsung just launched a new phone, they might want to buy ad space on The Verge
- Ad Networks and Exchanges: In essence, they bundle up ad space from the publishers and sell it to advertisers. In doing so, they group the inventory into various groups segmented by vertical, ad format, and demographics. Thus, advertisers can now buy ads that would better target their potential customer base. Some popular ad networks include Google AdSense and Facebook Ads. Ad exchanges are a slightly more sophisticated version of ad networks where advertisers pay per impression levels. Popular ad exchanges include Google AdX and OpenX.
Currently, over half the Web2 ad market is controlled by five tech giants (Google, Facebook, Amazon, Alibaba, and ByteDance). We also all now know that the product is not the app or service itself, but you, the user. Using you as a data collection point, big tech firms sell the data they obtain from you (after running their rather clever and sophisticated models) to advertisers. You are their main source of revenue.
Note: The AdTech umbrella also covers several niches such as Attribution, CRMs, Growth Analytics, Community Automation, and other similar platforms. However, there is little consensus on what “AdTech” comprises and thus some people may argue these sub-niches fall under Growth. While this is not incorrect, for the sake of brevity we will be referring to both AdTech and Growth services collectively as AdTech. We will be exploring these sub-niches more in-depth during our discussion about Web3 AdTech.
What’s changing in Web2 AdTech?
Given that over 80% of Big Tech’s revenue comes from AdTech, it is no surprise that predictive models for customer targeting are very, very good. However, Web2 models are limited by a few factors. Firstly, by the vastness and quality of data available. Secondly, by the law of statistics. Essentially, Web2 data models use demographic, psychographic, and behavioral data as proxies to predict future buying behavior for potential customers. Thus, even with vast data available Web2 models make predictions, not claims (albeit, very good predictions).
However, with increasing user demand for greater privacy through transparency and some degree of control of how their data is used, there has been an inexorable push to tighten privacy regulations to curtail the rampant advent of data harvesting. To tackle this, several laws have come into effect, the most prominent being the General Data Protection Regulation, popularly known as GDPR. Among a battery of provisions to safeguard personal data, the most important element of GDPR is the concept of “opt-in.” This is the main reason you see an option to accept or deny cookies when visiting a website. Speaking about cookies, there is a within-industry effort to phase out third-party cookies. In 2020, Google revealed its plans to phase out third-party cookies from Chrome by 2023 and promised not to replace them with “alternate identifiers to track individuals.”
While these regulations do a wonderful job of protecting privacy interests, they do happen to have a few crucial faults. Since consumers now consent to tracking cookies by opting in, trackability for those customers goes up substantially. This better quality of data collected raises advertising prices. Furthermore, due to GDPR, smaller advertisers and businesses who were reliant on third-party cookies now collect less data and “conduct less business due to consumer opt-out.” This puts them at a significant disadvantage to internet giants who leverage their first party ecosystem to collect data. Thus, instead of diluting Big Tech’s power over the data economy, GDPR regulations consolidate them further (if you’re interested in exploring this further, I would recommend you to explore this 76-page research paper written in collaboration between MIT, Columbia, Northwestern, National Bureau of Economic Research, and the Federal Trade Commission that investigates the effects of GDPR on Web2 AdTech).
What’s different about Web3 AdTech?
Web3 brings a paradigm shift to traditional Web2 AdTech. Web3 proposes a very interesting dynamic with respect to your on-chain data – it is no one’s and everyone’s at the same time. It’s no one’s in the sense that on Web3 you are no longer Alice or Bob, you are just an alpha-numeric string (0x…), your wallet address. No one knows the color of your skin, your age or where you live. What this means is that you, the user, are no longer the product. You are back to being what you were always intended to be – a consumer, not a data point. Essentially, your entire transaction history is on-chain. What you (or rather your wallet address) buys, sells, which NFTs you possess, which DeFi services you interact with, everything is transparent and accessible to anyone. This is particularly interesting when we think about how Web2 advertising algorithms work and how they might work in Web3. As discussed above, Web2 models make great predictions but not firm claims. That dynamic changes with the nature of data available in Web3. Web2 models can predict that you might have bought that pair of Air Force Ones you were eyeing last week on a sale on Nike so it won’t show you an ad for sneakers anymore. However, Web3 models know that you bought that Milady NFT you’ve been wanting for a month so maybe it won’t show you any more Milady ads. Time for some Bored Apes perhaps? Through this we see there is a fine line between Web2 predictions and Web3 claims. However, this makes all the difference for upcoming Web3 projects who are aiming to target and onboard potential users.
Moreover, the lack of demographic and personal data has two camps of thought. One camp questions the strength of Web3 models, given they will not be able to factor in conventional psychographic and behavioral data that allows current Web2 models to predict customer tendencies. Another camp questions whether we even need such sensitive data for Web3 models. Do you really need to know someone’s age, gender, race, and other sensitive information to make predictions? This camp argues the abstraction of the human element behind the bits of a wallet address is perhaps not all that bad. Maybe it no longer matters who you are. This camp also sees this as a counter-act to prevent the effect of human biases in AI/ML algorithms.
So essentially, we can see AdTech as a line where one extreme represents borderline data mining and oppressive privacy practices (Web2) while the other extreme (current Web3) represents privacy maximization but underdeveloped/ limited advertising algorithms. Clearly, the optimal solution lies somewhere near the middle of these two extremes. This is where the true power of Web3’s potential lies. We realize wallet info is limited and wallet data alone cannot drive Web3 AdTech alone. How can we potentially change this while ensuring the consumer’s privacy is not compromised unfairly? Simply put, allow users to earn from the data they choose to give away. Currently, Web2, rather cunningly, makes users “choose” to give away data through opt-in but users don’t really get anything in return except more targeted ads. With Web3, there can be data exchange platforms or integrated solutions that allow users to choose and willingly give personal data in exchange for monetary returns. Moreover, there are proponents calling for user compensation across multi-touch attribution touch points when a successful conversion is made through micropayments. Essentially, your data is yours and you deserve to be rewarded for it when you voluntarily give it up.
Still with us? Let’s quickly recap why Web3 AdTech is cool:
- You, the user, are no longer the product that Big Tech currently treats you as
- Removes human biases from current advertising and tracking AI/ML models
- Web3 brings transparency and vast on-chain data
- Web3 AdTech models can make firm claims, not just predictions
Alright, before we get all too excited and start calling for an upheaval of Web2 AdTech and welcome the savior that Web3 AdTech seems to be, let’s hold our horses and have a look at its few caveats. It’s important to understand that Web3 AdTech is in no way perfect or close to being perfect for a short while and it is imperative to be cognizant of these shortcomings.
Why is Web3 AdTech not cool?
- Decentralization fragments customer identities across multiple wallets and chains, making it challenging to collect accurate data and understand customer behavior. Also, Web3 applications (still) run on Web2 interfaces, which adds to the fragmentation and hinders accuracy. How can we unify this data to enable accurate attribution and personalization?
- Currently, on-chain data is limited and so is our understanding of it. Web3 brings with it new quantitative metrics such as TVL for DeFi projects, floor price for NFTs, and community engagement ratios for DAOs. What do these metrics mean? Which ones are important to track, which ones can be safely ignored?
- New, hybrid data stacks will be required to unify data fragmented across Web3, trace it back to Web2, and have an accurate picture of customer profiles – all while preserving their privacy.
- Currently, most Web3 dApps still run on Web2 websites and interfaces. This means that whether the back-end runs on decentralized blockchains, the front-end of the application still runs on traditional Web2 sites. This disconnect makes it even harder to reconcile actions done on Web2 UIs (eg. clicks, page visits, etc.) with on-chain ones (eg. transactions, swaps, transfers, etc.), and trace them both back to one single identity (eg. wallet address).
Web3 AdTech ecosystem
Now that we understand how Web3 AdTech works, let’s explore its sub-niches and some interesting projects.
Note: A number of these projects may appear to be doing the same thing but it’s important to understand how such projects can coexist and complement each other from the user’s perspective.
In its general Web2 sense, attribution essentially pertains to understanding where your users come from and where you should invest to get more users. This involves identifying users across online channels, offline channels, and across numerous devices. In Web3, attribution presents a new challenge. As we alluded to above, the typical definition of a consumer is drastically different along the standard user journey. With touch points spread across Web2 and Web3, a lack of a popular Web3 native social media network, the role of Discord and other DAO communities in influencing customer journeys, and with users having multiple wallets. Web3 attribution does not have an easy road ahead of itself. However, a foundational solution that is willing to tread this tough path is bound to emerge as an extremely strong force for years to come. Up until the bear market of 2023, startups and projects were enjoying the honeymoon phase of getting funding with minimal understanding of their potential customer base. Ignorant of data, these projects were built on principles that are fundamentally opposed to basic entrepreneurial beliefs. However, with funding drying up in the bear market, fundamentals such as customer base identification are back in the limelight, making Web3 attribution absolutely imperative.
Safary aims to build marketing attribution for Web3 while also empowering a Web3 growth ecosystem through their SaaS interface/API. With setup requiring only a single line of code, Safary provides detailed attribution analytics through its no-code dashboard. Currently, Web3 projects are only able to track top-of-the-funnel metrics and Web2 social and bottom-funnel metrics such as wallet purchases on chain. Safary provides analytics throughout the continuous journey from Web2 channels to Web3 outcomes.
Currently, crypto companies face two significant challenges in reaching out to their desired target customer base. Firstly, crypto ads simply do not work through traditional Web2 channels such as Google and Facebook services. You may have seen a few L1s advertising on Google and Facebook, but this involves a lot of wrangling with regulation and convincing the right person that the L1 is essentially a tech infra company.
Secondly, Web3 advertising and user acquisition have primarily been through one-time token airdrops, the act of incentivizing user activity through the promise or presumption of giving away protocol tokens. However, airdrops are a fundamentally broken form of user acquisition in which the cost far outweighs the LTV (Customer Lifetime Value) and has not proven to be sustainable. Dune Analytics conducted a deep dive into the Uniswap airdrop that occurred in late 2020 and found some discouraging statistics:
- Only 7% of the claimed wallets are still holding the UNI token
- Over 75% of the wallets dumped the token in the first 7 days
- Only 5% of the claimed wallets remain Uniswap users today
- 50% of the claimed wallets have not been active on Ethereum in the last 610 days
Thus, clearly, Web3 advertising needs to be optimized to ensure marketing strategies reach their end goal of adding valuable long-term customers to new crypto projects. Projects need to optimize their customer targeting, which is why marketing strategies such as airdrops and giveaways barely ever work for new projects.
HypeLab and Slise are two startups working to solve the user acquisition problem in Web3. HypeLab offers personalized services to advertisers who want to find new customers and publishers who want to monetize their user base. Along with their main analytics offering, HypeLab offers advertisers design services to create image and video marketing assets as well as UI to upload these creatives onto the platform. For publishers, HypeLab offers a publisher SDK which can be used to seamlessly integrate ads into their front-ends and provide real-time tracking of revenue and other metrics. Slise offers a similar service which uses blockchain indexing, user profiling, segmentation, and real-time bidding to bridge the gap between publishers and advertisers in Web3. Furthermore, both companies also work across the Web2/Web3 fabric by providing publishing capabilities across Web3 dApps, Web2.5 platforms such as crypto-media and coin-trackers, and general Web2 publishers.
With the emergence of projects like HypeLab and Slise, we can envision a future of Web3 advertising, which will enable early-stage projects to reach potential customers effectively rather than just hoping the follower base of Twitter influencers they’re paying matches their ideal customer base.
While growth analytics may seem to have significant overlaps with attribution, growth analytics focuses more on collecting, analyzing, and interpreting data to understand how users interact with advertising campaigns. This data can be used to optimize campaigns for better results, such as increased click-through rates (CTRs), conversions, and revenue.
Perhaps the best way to understand Web3 AdTech is to look at one of the player’s out there – Cookie3. While offering basic attribution services, Cookie3 also offers off-chain to on-chain conversion tracking, Discord server insights, wallets CRM, user segmentation analysis, and Twitter advertising strategy suggestions based on on-chain transactions. Cookie3’s algorithms are one of the strongest in the Web3 growth analytics landscape through their massive datasets, of which they have processed data from 200 million wallets, 500k Twitter accounts, 8 billion transactions, and 4.5 million tokens.
Another interesting booming sector within growth analytics is gaming analytics. Helika is one such startup that offers holistic end-to-end solutions to optimize spend on user acquisition and to drive player engagement for Web3 games through live ops and a/b testing for game studios. Through onboard game analytics and stratification of users into different gamer archetypes, Helika aims to enable gaming studios to understand the community engaging with their product, ultimately driving higher revenues. They also offer competitive analytics to help projects understand what other games their users or potential users are engaging with by tracking their NFT and ERC20 portfolios to drive targeted user acquisition from competitive projects. With Web2 social media (Twitter and Discord) insights integrated into their core product, Helika offers gaming studios a great blueprint to acquire and engage users.
Wallet Relationship Managers (WRMs)
WRMs are essentially CRM but where your customers are now replaced with wallet profiles. Projects such as Absolute Labs offer end-to-end “wallet” management solutions that enable you to create Web3 profiles by understanding waller clusters, design wallet segmentations, and push Web2/Web3 marketing campaigns such as airdrops, wallet messaging, emails, and SMS. A challenge Web3 startups are encountering today pertains to them not having an experienced marketing team comfortable with niche Web3 marketing stacks. By offering them a turn-key solution that extends from analytics to segmentation to designing flows to execution, WRMs offer a seamless solution to interact better with your clients.
Future for Web3 AdTech
From our above discussion, one thing becomes clear – there is an explicit need for Web3 to have its native social analytics sphere. Web2 services such as Twitter can only go as far as being a glorified town hall for crypto discussions. Web3 AdTech promises a future where the customer gets to actively participate in the currently restrictive advertising processes, a promise which cannot be fulfilled within the restrictions and ideologies of Web2 constructs.
Web3 ad networks will also enable the creation of new “ad formats” that hadn’t existed before. Every new generation of social networks and media platforms has brought about original forms of content distribution (think Tiktok, instagram reels etc.). New forms of content and culture act as a medium for new ad formats and tools of engagement. Web3 opens up a new playground of tools for marketers and growth hackers to experiment and engage with their customer base.
However, we have to realize we are in the very infancy of Web3 AdTech. Yes, currently, Web3’s promise of advertising algorithms not using personal data seems too utopian to be true. Despite everything being funneled on-chain, on-chain data is inherently limited and does not allow for good predictive models. To solve this, AdTech projects currently rely on connecting a wallet with its Web2 identity to make sense of their models. While this is the best they can do right now, it is scrappy and backtracks on the privacy-preserving thesis. However, by leveraging zk-proofs, on-device data storage integrations, and the rise of Self-Sovereign DIDs (essentially Web3 passports), frameworks can be designed where users can give up their data in a privacy-preserving manner for financial returns.
Projects such as Safary, HypeLab, Cookie3, and Helika provide a wonderful landing pad for the imminent launch of mainstream Web3 social. Along with these we hope to see further major web3-focused advancements in the space. These might come through DIDs, expanding data types, growing wallet functionalities, the merging of the real and digital realms through the metaverse, a native Web3 social media app, Web3 hiring platforms, or blockchains that offer built-in identities.
Most importantly, Web3 AdTech’s potential to enable you to control and earn from your data is what truly separates it from Web2 and is crucial for inducing a mass transformation from oppressive Web2 to equitable Web3 social.
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