Advertising Industry
Who and what can you trust?
Advertising is the business of converting attention into action. The industry is being restructured by AI (precision targeting), blockchain (transparent verification on Sui), and DePIN (community-owned data collection).
Playbook
| Prompts | Questions | Reflections |
|---|---|---|
| Principles | What guides us? | Attention economics, Ogilvy-Sutherland truths |
| Performance | Is it working? | KPIs, ROAS, attribution reality |
| Protocols | How do we do it? | Programmatic workflow, data integration |
| Platform | What tools? | Tech stack architecture |
| Players | Who's involved? | Meta, Google, DePIN data providers |
The Thesis
Advertising is transitioning from surveillance extraction to data-informed intelligence:
| From | To | Driver |
|---|---|---|
| Third-party cookies | First-party data | Privacy regulation kills tracking |
| Impression counting | Outcome measurement | AI enables causal attribution |
| Opaque platforms | Transparent reporting | Blockchain verifies ad delivery |
| Centralized data | Community-owned data | DePIN sensors provide ground truth |
| Brand OR performance | Unified measurement | MMM + incrementality + multi-touch |
| Weeks of reconciliation | Real-time settlement | On-chain verifiable truth |
The Trust Problem
Who verifies the verifier?
Advertisers don't trust publishers. Publishers don't trust exchanges. Agencies don't trust measurement vendors. This isn't a payment or compute problem — it's a coordination problem across execution, data, and verification. Reconciliation takes weeks. Disputes over delivery become spreadsheet wars. A hidden fee for "verification" extracts value without transparency.
The meta-problem: the industry charges for trust but cannot prove it earned.
The Sui Stack
What if verification was built into the rails?
Sui's object-centric architecture and extended stack compose into a purpose-built advertising settlement layer:
| Primitive | Solves | How |
|---|---|---|
| Sui Objects | Programmable transactions | Data and value move on the same rails — who, what, where, which impressions |
| Walrus | Cost-effective notarization | Bales of microtransactions stored and notarized on-chain, not per-CPM on L1 |
| Seal | Configurable privacy | PII and GDPR-sensitive data encrypted/decrypted with access policies — never permanently on-chain |
| Nautilus | Trustless validation | Data stored on Walrus verified in TEE — single source of truth eliminates reconciliation |
Verification becomes a feature of the infrastructure, not a hidden fee. Value returns to advertisers and content creators.
AdPool — on-chain verified transactions let publishers access expedited payments (zero-day settlement) in exchange for a fee. DeFi participants generate yield from a market funded by ad spend. The advertising flywheel funds its own infrastructure through the broader Sui ecosystem.
Opportunity Score
Aggregate: 6.5 / 10 | Classification: Monitor Closely
| Dimension | Score | Key Evidence |
|---|---|---|
| Market Attractiveness | 8.0 | $1T global ad spend, digital growing 15%+ YoY |
| Technology Disruption | 7.0 | AI targeting, programmatic CTV, cookie deprecation |
| VVFL Alignment | 6.0 | Data loop works, but incumbents (Meta, Google) dominate |
| Competitive Position | 5.5 | Duopoly entrenched, DePIN advertising nascent |
| Timing Risk | 6.0 | Privacy shift creates window, but execution complex |
Verdict: Massive market with structural disruption in data and measurement. DePIN opportunity is in the data supply chain (feeding better targeting), not replacing the ad platforms themselves.
First Principles
| Principle | Why Immutable | Implication |
|---|---|---|
| Attention is finite | 24 hours per day, fixed | Competition for attention is zero-sum |
| Relevance earns attention | Irrelevant ads get ignored | Better data = better targeting = better results |
| Measurement drives allocation | What gets measured gets funded | Attribution determines ad spend flow |
| Trust decays with opacity | Unverifiable claims lose credibility | Transparent measurement wins budgets |
| Distribution follows audience | Audiences move across platforms | Multi-channel presence is mandatory |
See Principles for the full framework.
The Flywheel
Data Collection → Audience Intelligence → Ad Delivery → Conversion → Revenue → More Data
↑ ↓
└──────────── Revenue funds better data collection and targeting ──────────┘
Better data → Better targeting → Higher conversion → More revenue → Better data
Value Chain
| Stage | Traditional | AI + DePIN Era | Margin Shift |
|---|---|---|---|
| Data collection | Cookies, surveys | DePIN sensors, first-party | → Data providers |
| Audience building | DMP + third-party | CDP + AI modeling | → Intelligence layer |
| Media buying | Manual IO | Programmatic + AI bidding | → Automated |
| Creative | Agency production | AI-generated, DCO | → Platform tools |
| Measurement | Last-click | MMM + incrementality | → Analytics |
The Buyer's Problem
Who is advertising designed for?
Two buyer profiles. Two different failures. One root cause: the ecosystem optimises for intermediaries, not outcomes. Apply the JTBD lens — what progress is each buyer trying to make?
| JTBD | SME | Enterprise |
|---|---|---|
| The job | Get more customers without becoming a marketing expert | Prove marketing spend drives revenue |
| Current solution | Word of mouth, referrals, half-abandoned Google Ads | Stack of agencies, platforms, measurement vendors |
| Trigger | Growth plateaus — network maxed out | CFO asks "what did we get for that $5M?" |
| Hidden objection | "I'll waste money and won't know if it worked" | "If we measure properly, half of it doesn't work" |
| Progress | Predictable pipeline from paid channels | Attribution they can trust |
The SME's job is not "run ads." The enterprise's job is not "buy media." Miss the job, build the wrong solution.
SME Reality
The business owner with no dedicated marketing team. $2K-$20K monthly budget. The largest buyer segment and the most underserved.
| Problem | Why It Hurts | What They Do Instead |
|---|---|---|
| Complexity gap | DSPs, SSPs, CDPs, RTB — built for teams of specialists | Use self-serve platforms they don't understand |
| Agency misalignment | Agencies charge % of spend — incentive is more spend, not better spend | Skip agencies, lose on optimisation |
| Platform black box | Meta and Google grade their own homework | Trust unverifiable metrics |
| Creative at scale | A/B testing needs volume; production costs prohibitive | Run one ad until it stops working |
| Cash flow timing | Pay upfront, revenue comes weeks later | Underspend during growth windows |
| Attribution impossibility | Multi-touch requires infrastructure they don't have | Default to last-click or gut feel |
The root: paying for complexity they can't use, measured by metrics they can't verify.
Enterprise Reality
Dedicated teams, large budgets. They can afford the complexity but can't verify the results.
| Problem | Scale | Cost |
|---|---|---|
| Fee opacity | 40-60% of spend absorbed before reaching publisher | Billions lost to intermediary stack |
| Reconciliation | Weeks of spreadsheet wars between agencies, platforms, vendors | Finance teams can't close books |
| Ad fraud | Sophisticated bots evade detection | Estimated $100B+ annually industry-wide |
| Data silos | Each platform is a walled garden | No unified view of customer journey |
| Agency coordination | Creative, media, data agencies don't share | Duplication, gaps, finger-pointing |
The root: nobody in the value chain has an incentive to tell the truth.
The Connection Gap
Jobs to be done is what glues provider to consumer. When the intermediary solves its own margin problem instead of the buyer's job, the connection breaks.
Advertiser → Agency → DSP → Exchange → SSP → Publisher
$1.00 $0.85 $0.70 $0.55 $0.45 $0.36
Every intermediary optimises for their own margin. None of them are hired to do the buyer's job. The agency is hired to spend budget. The DSP is hired to win auctions. The measurement vendor is hired to report numbers. The buyer's actual job — get more customers or prove spend drives revenue — falls between the cracks.
The agent-native alternative aligns to the job:
Advertiser → Agent → Verified Exchange (Sui) → Publisher
$1.00 $0.95 $0.90 $0.85
The agent is hired to do the buyer's job — targeting, bidding, measurement, optimisation. The Sui stack handles verification and settlement. The human decides strategy and budget. The SME gets enterprise-grade precision at self-serve prices. The enterprise gets transparent attribution they can audit.
Awareness Levels
Where are advertising buyers on the awareness spectrum?
| Level | SME | Enterprise |
|---|---|---|
| Unaware | Don't know growth stalled because of bad targeting | Don't know 60% of spend is absorbed by intermediaries |
| Problem Aware | Know ads aren't working, don't know why | Know attribution is broken, can't fix it |
| Solution Aware | Heard of AI ads tools, haven't tried | Know independent measurement exists, agencies resist |
| Product Aware | Know agent-native options exist, not convinced | Know on-chain verification is possible, unproven at scale |
| Most Aware | Ready to switch, need frictionless onboarding | Ready to pilot, need enterprise-grade compliance |
Most SMEs are Problem Aware — they feel the pain but can't name the cause. Most enterprises are Solution Aware — they know better exists but switching costs are high. The JTBD interview reveals where each buyer actually sits.
This is BOaaS applied to advertising: AI agents on crypto rails providing expertise previously locked behind agency minimums. The AI-native agency playbook — 90% AI / 10% human — software economics applied to service delivery.
The Triangle
Advertising connects to AI Data and Robotics through the data flywheel:
AI DATA
/ \
(feeds) (trains)
/ \
ADVERTISING ——— ROBOTICS
(monetizes attention from robot-generated data)
- AI Data → Advertising: Better data enables precision targeting
- Advertising → AI Data: Ad revenue funds data collection infrastructure
- Robotics → Advertising: Robot-collected data creates new audience signals
Deep Dives
| Section | Deep Dive | What's There |
|---|---|---|
| Principles | Attention Economics | Immutable truths of advertising |
| Performance | KPIs | Metrics and measurement |
| Protocols | Workflows | Programmatic buying, DePIN integration |
| Platform | Tech Stack | Architecture and tools, Alkimi/EAT on Sui |
| Players | Ecosystem | Incumbents and disruptors |
| Star | KPI Deep Dive | 364 lines of benchmarks and metrics |
| Star | 375ai | Verified physical presence for advertising |
| Star | Sui | Object-centric settlement and verification |
| Star | Sui Ecosystem | Walrus, Seal, Nautilus — the extended stack |
Context
- Jobs To Be Done — The framework that glues provider to consumer
- Truth, Trust, Identity — The meta-problem advertising exposes
- Agent Commerce — Agents aligned to the buyer's job, not intermediary margin
- Sui — Settlement layer for data and value
- 375ai — Verified physical presence replaces modelled estimates
- Advertising Sales Protocol — How a business runs ads