Advertising Protocols
How advertising flows from intent to action. The programmatic workflow and how DePIN data integration changes it.
The Advertising Flow
INTENT → TARGET → BID → DELIVER → MEASURE → OPTIMIZE
↓ ↓ ↓ ↓ ↓ ↓
Campaign Audience RTB Creative Attribution Feedback
brief build DSP serving analysis loop
Each step has protocols — automated rules that govern how decisions are made at millisecond speed.
Programmatic Workflow
How $168B in US digital ad spend flows through automated systems.
The Real-Time Bidding Cycle
| Step | Time | Action | Technology |
|---|---|---|---|
| 1 | 0ms | User loads page | Browser/app |
| 2 | 10ms | Ad request sent | SSP |
| 3 | 50ms | Audience matched | DMP/CDP |
| 4 | 80ms | Bid calculated | DSP + AI |
| 5 | 100ms | Auction resolved | Exchange |
| 6 | 120ms | Creative served | Ad server |
| 7 | ~seconds | User sees ad | Browser |
| 8 | ~variable | User acts (or not) | Conversion tracking |
100 milliseconds. That's the time from ad request to bid decision. Every step is automated. AI optimization at each stage compounds into massive efficiency gains.
Data Integration Protocols
First-Party Data Flow
User Action → Collect → CDP → Segment → Activate → DSP → Serve
↓ ↓
Privacy consent Attribution
The shift: Third-party cookies → first-party data + AI modeling. Companies that build first-party data pipelines gain structural advantage.
DePIN Data Integration
How decentralized data sources feed the advertising pipeline:
| DePIN Source | Data Type | Advertising Use | Integration Point |
|---|---|---|---|
| GEODNET | Precision location | Centimeter-accurate geotargeting | CDP/DSP audience layer |
| WeatherXM | Hyperlocal weather | Context-based creative triggers | DCO creative engine |
| Hivemapper | Fresh map imagery | Location intelligence, footfall | Analytics and planning |
| Helium | Connectivity data | Device/location intelligence | Audience enrichment |
The Data Quality Protocol
DePIN Device → On-chain attestation → Verified data → AI processing → Audience signal
↓
Cryptographic proof of:
- When collected
- Where collected
- How collected
- Device identity
Why this matters: Advertising built on unverified data produces unverified results. DePIN attestations create a provenance chain from physical sensor to targeting decision.
Channel Protocols
Search (SEM)
| Component | Protocol | Optimization |
|---|---|---|
| Keywords | Auction-based bidding | Quality score maximization |
| Creative | Text + extensions | CTR optimization |
| Landing | Conversion-optimized | CVR improvement |
| Bidding | AI-automated | Target CPA/ROAS |
Social (Meta, TikTok, LinkedIn)
| Component | Protocol | Optimization |
|---|---|---|
| Audience | Interest + behavioral | Lookalike expansion |
| Creative | Video + carousel | Engagement rate |
| Placement | Automated across surfaces | CPM efficiency |
| Attribution | Platform-reported | Independent verification needed |
CTV (Connected TV)
Fastest-growing channel. $34.49B spend projected in 2025.
| Component | Protocol | Optimization |
|---|---|---|
| Audience | ACR + identity graph | Household targeting |
| Buying | Programmatic guaranteed + RTB | CPM efficiency |
| Measurement | Incrementality + brand lift | Cross-device attribution |
| Format | 15s/30s + shoppable | Direct response + brand |
Programmatic DOOH
| Component | Protocol | Optimization |
|---|---|---|
| Targeting | Geofenced audiences | Location + time triggers |
| Buying | Programmatic SSP | Daypart optimization |
| Creative | Dynamic, weather/event triggered | Context relevance |
| Measurement | Foot traffic lift | Attribution via mobile IDs |
Measurement Protocols
The Three-Model Approach
| Model | Frequency | Purpose | Output |
|---|---|---|---|
| MMM | Quarterly | Budget allocation | Channel-level ROI |
| MTA | Daily | Campaign optimization | Touchpoint-level credit |
| Incrementality | Monthly | Causal validation | True lift measurement |
Verification Protocol
Ad Served → Viewability check → Brand safety check → Fraud filter → Valid impression
↓
Attribution credit
The Evidence Loop
CAMPAIGN → MEASURE → COMPARE (vs expectation) → DIAGNOSE → OPTIMIZE → NEXT CAMPAIGN
This is the VVFL applied to advertising. Every campaign generates data that improves the next.
| Stage | Metric | Diagnosis If Below Target |
|---|---|---|
| Headline | CTR | Headline didn't select or intrigue |
| Landing | Bounce rate | Page didn't deliver on promise |
| Conversion | CVR | Friction, trust, or relevance issue |
| Revenue | ROAS | Wrong audience or wrong offer |
Context
- Advertising Overview — The transformation thesis
- Platform — Tech stack architecture
- Performance — What to measure
- AI Data Protocols — Data pipeline architecture