What's the decision path to a world-beating advertising platform?
Are your tools working together, or are they just expensive silos?
The ABCD Overlay
| Layer | Function | Advertising Application |
|---|
| A - AI | Targeting, bidding, creative | Predictive bidding, DCO, audience modeling |
| B - Blockchain | Verification, settlement | On-chain RTB, transparent auctions, instant payout |
| C - Crypto | Payment, incentives | Micropayments for attention, token rewards, EAT protocol |
| D - DePIN | Physical intelligence | 375ai sensors, GEODNET location, verified presence data |
Core Architecture
DATA LAYER → EXECUTION LAYER → INTELLIGENCE LAYER
CDP + DMP + DePIN → DSP + SSP + On-Chain → Attribution + AI + Analytics
Data Layer
| Platform | Data Type | Best For | Status |
|---|
| CDP | First-party, unified | Retention, personalization | Growing — the moat |
| DMP | Third-party, aggregate | Prospecting | Declining — cookies dying |
| DePIN data | Verified, real-world | Ground truth attribution | Emerging — 375ai, GEODNET |
| Leading CDPs | Strength |
|---|
| Segment | Developer-friendly, events |
| mParticle | Mobile-first, real-time |
| Tealium | Enterprise, governance |
| Bloomreach | E-commerce, search |
| ActionIQ | Enterprise, analytics |
Execution Layer
| Platform | Function | Key Players |
|---|
| DSP | Media buying automation | The Trade Desk, Google DV360, Amazon |
| SSP | Inventory management | Google Ad Manager, Magnite |
| Ad Server | Creative delivery | Google CM360, Flashtalking |
| On-Chain Exchange | Transparent RTB + settlement | Alkimi (Sui) |
| Leading DSPs | Strength |
|---|
| The Trade Desk | Enterprise, CTV, identity |
| Google DV360 | Google ecosystem, scale |
| Amazon DSP | Retail media, commerce |
| StackAdapt | Native, programmatic |
| Simpli.fi | Geofencing, local |
Intelligence Layer
| Function | Tools | Purpose |
|---|
| Attribution | Rockerbox, Northbeam | Touchpoint credit |
| MMM | Measured, Recast | Budget allocation |
| Analytics | GA4, Amplitude | Behavior understanding |
| Verification | DoubleVerify, IAS | Fraud and brand safety |
| On-chain audit | Blockchain explorer | Immutable delivery proof |
| Platform | Primary Function | Data Source | Target | Main Goal |
|---|
| DSP | Automates ad buying | Mixed | All audiences | Media buying efficiency |
| DMP | Aggregates third-party data | Third-party | New prospects | Audience prospecting |
| CDP | Unifies first-party data | First-party | Known customers | Retention and LTV |
| SSP | Sells publisher inventory | Publisher | Advertisers | Yield optimization |
| Ad Server | Delivers and tracks creatives | Campaign data | All | Creative management |
AI Capabilities
86% of companies use or plan to implement AI in advertising.
| Function | AI Application | Impact |
|---|
| Bidding | Predictive optimization | 25-30% CPA reduction |
| Targeting | Audience modeling, lookalikes | Reach expansion |
| Creative | Dynamic optimization (DCO) | 10-20% CTR lift |
| Content | Generative ad creation | 60% time savings |
| Attribution | Multi-touch modeling | Better allocation |
| Fraud | Invalid traffic detection | Budget protection |
Identity Infrastructure
Third-party cookies are dying. Identity strategy determines targeting ceiling.
| Solution | Type | Scale | Privacy |
|---|
| First-party cookies | Deterministic | Own traffic | Low risk |
| Hashed emails | Deterministic | Logged-in users | Low risk |
| Unified ID 2.0 | Industry standard | Growing | Medium |
| Privacy Sandbox | Google-controlled | Massive | Medium |
| Contextual targeting | No identity | Unlimited | Zero risk |
| Data clean rooms | Privacy-safe | Partner data | Low risk |
| zkLogin (Sui) | ZK-proof identity | Web2 onboarding | Zero risk |
The Web3 shift: zkLogin allows familiar Web2 logins (Google, Apple) while keeping identity pseudonymous on-chain. ZK proofs verify audience segment membership without exposing personal data.
Channel Tech
Connected TV (CTV)
$34.49B spend projected in 2025 (+23.2% YoY). Transitioning from awareness to performance through shoppable ads.
Digital Out-of-Home (DOOH)
Programmatic DOOH projected to exceed $1B in 2025. DePIN sensors transform measurement.
| Traditional DOOH | DePIN-Enhanced DOOH |
|---|
| Modelled audience estimates | Verified foot traffic (375ai sensors) |
| Coarse geofencing | Centimeter precision (GEODNET RTK) |
| Delayed reporting | Real-time data streams |
| Self-reported metrics | Cryptographic proof of presence |
Social and Commerce
Social commerce projected to reach $8.5T by 2030.
Web3 Disruption Layer
How Sui + DePIN + EAT protocol restructure the advertising stack.
Why Sui for Advertising
Sui enables real-time ad transactions by moving both data and value on-chain with sub-second finality.
| Capability | What It Enables |
|---|
| Parallel execution | 100k+ TPS — handles high-volume ad auctions |
| Object-oriented model | Ad entities (campaigns, creatives, budgets) as native objects |
| Sub-second finality | Real-time settlement replaces 30-90 day payment cycles |
| Programmable Transaction Blocks | Atomic: verify impression + update budget + split payment in one tx |
| zkLogin | Web2 onboarding — Google/Apple login, pseudonymous on-chain |
| ZK Compression | NFT minting costs reduced 5,200x ($0.005/MB vs $1,000/MB) |
On-Chain Ad Objects
| Traditional Entity | Sui Object Model | Why |
|---|
| User Cookie/ID | Sui Address / Kiosk | Persistent, user-controlled asset container |
| Ad Campaign | Shared Object | Multiple publishers interact simultaneously (parallel) |
| Ad Creative | Immutable NFT | Tamper-proof — prevents malvertising |
| Budget | Coin Object (SUI/USDC) | Actual liquidity, not a database number |
| Impression Proof | ImpressionProof Object | Cryptographic delivery receipt |
| DePIN Node | DePINNode Object | Registered capabilities, location, uptime |
Alkimi / EAT Protocol
On-chain Real-Time Bidding on Sui. The Exchange Advertising Terminal eliminates middlemen.
| Traditional RTB | Alkimi on Sui |
|---|
| Hidden auction mechanics | Public, immutable bid record |
| 30-90 day payment cycles | Sub-second settlement |
| 50-60% of spend reaches publisher | 90%+ reaches publisher |
| Self-reported metrics | Cryptographic audit trail |
| Reconciliation required | Payment IS the settlement |
Physical Intelligence Layer
375ai edge sensors + GEODNET precision location = verified physical context.
375ai SENSORS → Foot traffic, dwell time, presence ─┐
├→ ImpressionProof on Sui
GEODNET RTK → Centimeter-level location attestation ─┘
↓
On-chain verification
↓
Atomic payment split (PTB)
| Component | Data Provided | Fraud Eliminated |
|---|
| 375ai | Verified human presence, dwell time, flow patterns | Ghost impressions, bot traffic |
| GEODNET | Centimeter-level position attestation | Location spoofing |
| ZK proofs | Audience segment match without identity exposure | Privacy violations |
| Sui settlement | Instant, atomic, auditable payment | Payment fraud, hidden fees |
Data Velocity Model
Not everything goes on-chain. Separate by speed and trust requirement.
| Data Type | Location | Rationale |
|---|
| Raw RTB bid/response logs | Off-chain (data warehouse) | High volume, low individual value |
| Sensor video frames | On-device (375ai edge processing) | Privacy — never leaves device |
| GEODNET correction streams | Off-chain (real-time service) | High frequency, low value per datum |
| Winning bids + settlement | On-chain (Sui) | Trust point — drives payment |
| Impression proofs | On-chain (Sui) | Trust point — verified delivery |
| Location attestations | On-chain (Sui) | Trust point — anti-spoofing |
| Revenue splits | On-chain (Sui) | Trust point — instant payout |
Privacy-First Targeting
Zero-party data: users own and share voluntarily for compensation.
| Traditional | Web3 (Sui) |
|---|
| Covert cookie tracking | User grants read-only capability to advertiser |
| Data stored on advertiser servers | Data stays in user's wallet (Sui object) |
| All-or-nothing consent | Granular: allowed verticals, formats, frequency caps |
| User gets nothing | User earns tokens for verified attention |
DePIN Integration
How decentralized data infrastructure plugs into the stack:
DePIN Sensors → Verified Data → CDP Integration → Audience Enhancement → DSP Targeting
↓
On-chain attestation
(provenance proof)
| Integration Point | DePIN Data | Value Add |
|---|
| CDP enrichment | Location, weather, environment | Hyperlocal audience segments |
| DSP targeting | Real-time context signals | Moment-based targeting |
| Creative triggers | Weather, foot traffic, events | Dynamic creative optimization |
| Measurement | Physical world verification | Offline attribution |
| Settlement | On-chain delivery proof | Instant, fraud-resistant payment |
Measurement Stack
The Measurement Triad
Best-in-class measurement combines three approaches:
- MMM — Strategic allocation, offline + online, no tracking required
- MTA — Tactical optimization, customer journey mapping
- Incrementality — Causal proof, ground truth calibration
| Function | Tools |
|---|
| Web Analytics | GA4, Adobe Analytics, Amplitude |
| Mobile Attribution | AppsFlyer, Adjust, Branch |
| Multi-touch Attribution | Rockerbox, Northbeam, Triple Whale |
| Marketing Mix Modeling | Measured, Recast, internal builds |
| Incrementality Testing | Geo experiments, holdout tests |
| Ad Verification | DoubleVerify, IAS, MOAT |
| On-chain Verification | Sui block explorer, DePIN attestations |
Build vs Buy
Build proprietary intelligence, buy commodity infrastructure.
| Component | Recommendation | Web3 Option |
|---|
| DSP | Buy | Alkimi (on-chain exchange) |
| CDP | Buy or build | — |
| Attribution | Build + buy | On-chain proofs |
| Creative tools | Buy | NFT-based creative management |
| Optimization AI | Build | — |
| Reporting/BI | Build | On-chain analytics |
| Identity | Buy + partner | zkLogin (Sui) |
| Physical data | DePIN | 375ai, GEODNET |
Stack Evaluation
| Metric | What It Shows |
|---|
| Time to activation | Speed from data to campaign |
| Data freshness | Lag between event and use |
| Match rates | % users identifiable cross-platform |
| Integration reliability | Sync uptime and success |
| Total cost of ownership | Platform + engineering + ops |
| Settlement speed | Time from impression to publisher payment |
| Fraud rate | % of spend on verified vs unverified impressions |
Stack Priorities
- Consolidate — Reduce tool count, increase integration depth
- First-party foundation — CDP and identity infrastructure
- AI-native — Platforms with embedded ML, not bolted-on
- Privacy-ready — zkLogin, consent management, cookieless
- CTV-capable — Streaming inventory access and measurement
- On-chain settlement — Transparent, instant, auditable
- Physical intelligence — DePIN sensors for ground-truth measurement
Context
Links