Decentralizing Adtech Targeting: Harnessing the Power of Soulbound Token Badges (SBTs)
Abstract
In the Web3 landscape, decentralized systems are transforming data management and utilization. Soulbound Token Badges (SBTs), non-transferable tokens, encapsulate an individual’s identity, achievements, and reputation within this decentralized space. This article introduces an approach using SBTs to innovate user cohorting and ad-targeting, challenging conventional AdTech categorisation norms (like IAB taxonomies). By examining the architectural flows of SBT assignment, ad booking, and user targeting, we highlight the potential of SBTs in contemporary adtech. Readers will grasp the system’s mechanics, positioning them at the cutting edge of digital advertising’s evolution.
Introduction
Web3 stands as the next digital evolution phase in the progression of internet capabilities. Unlike the current status quo, Web2, which centralized control in the hands of a few services providers, Web3 brings forth a decentralized model, ensuring data ownership and control reside with the users. This paradigm shift is poised to redefine many industries, with adtech being no exception.
Here is a comparison table highlighting the main differences between Web2 and Web3 [1, 2]:
[1] https://ethereum.org/en/developers/docs/web2-vs-web3/
[2] https://www.spiceworks.com/tech/tech-general/articles/web-2-vs-web-3/
Emergence of Soulbound Token Badges (SBTs)
We identify that Soulbound Token Badges (SBTs), non-transferable tokens that encapsulate an individual’s digital identity in the decentralized ecosystem, have a key role. Their non-financialized nature distinguishes them from all the other token-based solutions, focusing instead on representing social identity, achievements, and reputation.
Objective and Scope of the Article
In this article, we aim to show a novel use of SBTs in redefining user cohorting and ad-targeting mechanisms, offering a fresh, decentralized alternative to traditional IAB taxonomies. Through an exploration of the system’s architectural flows, we seek to provide a detailed blueprint for future implementations.
Understanding Soulbound Token Badges (SBTs)
While both SBTs and NFTs exist in the realm of Web3, their core functionalities differ significantly. NFTs, primarily designed for trade and ownership, often have a market value. In contrast, SBTs are non-transferable by design, ensuring they remain perpetually tied to the owner, thus preserving the authenticity of the information they represent.
Use Cases of SBTs
As we delve deeper into the applications of SBTs, four primary use cases emerge:
- Non-tradeable Nature: SBTs’ inherent non-transferable nature ensures that they cannot be traded, sold, or acquired by any entity other than the original owner. This guarantees that the token’s attributes remain genuine, fostering trust and credibility in the decentralized ecosystem. [1]
- Establishing Social Identity: In the Web3 landscape, central authorities no longer dictate identity. Instead, SBTs provide individuals with the tools to create and manage their decentralized identities, marking affiliations, memberships, or credentials. [2]
- Attribution for Achievements: From diplomas to certifications, SBTs serve as a testament to an individual’s achievements. Their non-transferable nature ensures these accomplishments can’t be falsely claimed, preserving the integrity of the decentralized system. [3]
- Reputation Building in Web3: SBTs can significantly influence one’s reputation within the Web3 community. By consolidating various aspects of a user’s background, skills, and achievements, they provide a comprehensive view of an individual’s credibility. [1,2]
[1] https://cointelegraph.com/news/what-are-soulbound-tokens-sbts-and-how-do-they-work
[2] https://blog.chain.link/web3-identity-blockchains-credentials-oracles/
[3] https://pixelplex.io/blog/soulbound-tokens-explained/
Architectural Flows of the System
The core of this system revolves around three fundamental flows: Assigning SBTs, Booking Ads, and Targeting Users.
Assigning Soulbound Token Badges
In scenarios where a user seeks content from a publisher guarded by an Ad-wall, the publisher must verify the user’s interests to enable the RTB flow. This verification is achieved through the user’s proof of interest, validated by their topic-specific SBTs.
- Interaction between User and Publisher — To initiate the flow, the user requests specific content from the publisher. This request prompts the publisher to ascertain the user’s interests, ensuring that the subsequent RTB flow aligns with the user’s preferences.
- Algorithmic Topic Recommendations — The exchange plays a pivotal role here, algorithmically recommending topics to the user. These recommendations guide users in determining which topics to enroll in, ensuring that the content they consume is tailored to their interests.
- Proof of Interest: A Verification Mechanism — The onus then shifts to the user to demonstrate their enrollment in these topics. By presenting their SBT as proof of interest, they can authenticate their claims, enabling the publisher to request the ad from the exchange.
A code paradigm for the recommendation algorithm that takes user behavior and preferences to recommend topics, can me something as simple as:
from typing import List, Dict
def recommend_topics(
predefined_topics: List[str],
content_topics: List[str],
user_enrolled_sbt_topics: List[str],
user_demographics: Dict[str, str],
advertiser_topics: List[str]
) -> List[str]:
topic_scores = {}
# Prioritizing content topics and user enrolled SBT topics
for topic in content_topics + user_enrolled_sbt_topics:
if topic in predefined_topics:
topic_scores[topic] = topic_scores.get(topic, 0) + 1
# Giving some weightage to advertiser topics (can be adjusted based on the custom implementation of each ad-echange)
for topic in advertiser_topics:
if topic in predefined_topics:
topic_scores[topic] = topic_scores.get(topic, 0) + 0.5
# Sorting the topics based on scores and returning the top 3
sorted_topics = sorted(topic_scores, key=topic_scores.get, reverse=True)
return sorted_topics[:3]
# Example use
predefined_topics = ["Sports", "Technology", "Fashion", "Music", "Movies", "Health"]
content_topics = ["Music", "Movies", "Fashion"]
user_enrolled_sbt_topics = ["Technology", "Health"]
user_demographics = {"age": "25", "gender": "male", "location": "NY"}
advertiser_topics = ["Sports", "Fashion", "Movies"]
recommended = recommend_topics(predefined_topics, content_topics, user_enrolled_sbt_topics, user_demographics, advertiser_topics)
recommendedBooking Ads
At the heart of this flow lies the Ad-manifest contract, encompassing various components such as the Ad-creative, ad-bid, Ad-Targeting, and Ad-Category.
Crafting the Ad-manifest Contract — The Advertiser initiates the process by formulating the Ad-manifest contract. This contract serves as a comprehensive repository of information related to the ad, ensuring that all parties involved have a clear understanding of the ad’s nuances.
Paradigm of the ad-manifest (not complete):
{
"ad-manifest": {
"ad-creative": {
"device-specific": {
"mobile": "ipfs://QmXYZMobileAdContent",
"desktop": "ipfs://QmXYZDesktopAdContent"
},
"content-source": "ipfs://QmXYZAdContent"
},
"ad-bid": {
"price": 0.05, // This denotes the price in ETH, for example
"currency": "ETH"
},
"ad-targeting": {
"demographics": {
"age": [25, 34],
"gender": "any"
},
"geolocation": {
"country": "UK"
},
"device": ["mobile", "desktop"]
},
"ad-category": {
"IAB-taxonomy": "Tech & Computing"
}
},
"on-chain-data": {
"topics": ["blockchain", "web3", "decentralization"],
"bid-price-investment": 0.05
}
}Each component of the Ad-manifest holds specific significance:
- Ad-creative: Dictates the device-specific content. It is essentially a JSON structure detailing where the content can be sourced.
- Ad-bid & Price: Information utilized by the exchange to prioritize the Ad.
- Ad-Targeting: Demographic and segmentation details essential for ad-targeting.
- Ad-Category: Indicates the IAB taxonomy of the Ad.
Targeting Users
The targeting process begins when a publisher initiates a bid request for a user, specifically one who has pre-enrolled in certain topics of interest. This pre-enrollment is crucial as it informs the exchange about the user’s specific inclinations, ensuring the subsequent ad delivery aligns with these preferences.
- Initiation: Publisher kick-starts the bid request based on user’s pre-enrolled topics.
- Bid-flow Processing: The exchange takes over, processing the incoming bid requests.
- Ad-Bid Prioritization: The exchange then employs a two-fold approach to prioritize ad-bids:
- Segmentation Match: Ensuring the ad-bids match user-specific criteria, such as location and device type.
- Topic Alignment: Cross-referencing the ad-bids with the user’s pre-enrolled topics to guarantee relevance.
The culmination of this process ensures that the user receives ads that are not only contextually relevant but also align with their declared interests, fostering a more engaging and personalized ad experience.
Extending RTB with Web3 Infrastructure
Real-Time Bidding (RTB) in traditional adtech landscapes operates on centralized platforms, where publishers auction off ad impressions in real-time. In our decentralized model, Web3 infrastructure infuses the RTB process with added transparency, security, and user-centricity, making it more efficient and trustable.
- Decentralized Auctions: Unlike centralized servers, bid requests and responses are handled by decentralized nodes, enhancing transparency and reducing single points of failure.
- Smart Contracts: Ad-manifests and bid agreements are codified as smart contracts, ensuring immutable and tamper-proof transactions.
- User Sovereignty: In a Web3 environment, users exercise greater control over their data and preferences, strengthening the relevance of ads delivered through RTB.
By transitioning RTB to a Web3 infrastructure, the adtech ecosystem benefits from the inherent advantages of decentralization. This approach not only modernizes the RTB process but also sets the stage for a more user-friendly and transparent digital advertising future.
The Impact and Potential of Decentralized Adtech
Centralized systems, while efficient, often lack transparency and user control. With decentralized adtech, not only is transparency restored, but users also gain more control over their data and preferences, ensuring a more personalized ad experience [1, 2, 3]. Decentralized adtech offers several benefits to advertisers, including:
- Increased transparency: Decentralized systems can provide advertisers with greater transparency into the ad buying process, allowing them to see where their ads are being placed and how their budget is being spent.
- Lower fees: Decentralized ad exchanges can reduce transaction costs and eliminate the need for intermediaries, resulting in lower fees for advertisers.
- Improved targeting: Decentralized adtech can enable more precise targeting of ads to specific audiences, resulting in higher engagement rates and better ROI,
- Enhanced security: Decentralized systems can provide advertisers with greater security and protection against fraud and other forms of malfeasance.
- Increased control: Decentralized adtech can give advertisers more control over their ad campaigns, allowing them to adjust their targeting and messaging in real-time based on performance data
[1] https://www.nasdaq.com/articles/importance-achieving-decentralization-ad-tech-networks-2017-08-22
[2] https://www.growthchain.io/blog/introduction-to-decentralised-advertising
[3] https://builtin.com/blockchain/blockchain-marketing-advertising-examples
Conclusion: The Road Ahead with SBTs in Adtech
The integration of SBTs into the adtech landscape promises a future where ads are not just viewed as interruptions but as meaningful engagements tailored to individual preferences. By decentralizing the adtech machinery, we’re not just changing the way ads are delivered; we’re redefining the very relationship between consumers, publishers, and advertisers.
