User‑Paid IDs in Programmatic: A Sell‑Side Blueprint for Pricing and Fair Value Transfer

Introduction

Identity is being rewired across the open internet. Third‑party cookies are receding, mobile identifiers face stricter controls, and platform policies continue to prioritize user privacy. In this environment, user‑paid identifiers are gaining traction because they are rooted in durable relationships that users choose and pay for. That combination of consent, persistence, and context makes them uniquely valuable. For the sell side, this is a strategic moment. Publishers and SSPs can turn user‑paid IDs into differentiated inventory, measurable performance, and fair value transfer back to users who make that value possible. The opportunity is real, but so are the execution details: pricing mechanics, packaging, auction signaling, identity quality scoring, measurement, and compliance. This thought piece sets out a practical, supply‑side blueprint. We will define what user‑paid IDs are, how to price them, how to ensure fair value flows to both sellers and users, and how to integrate them into auctions across web, app, and CTV with privacy‑by‑design. We will also share code snippets and schemas you can adapt with your teams, and we will ground recommendations in current standards such as OpenRTB 2.6, IAB Tech Lab’s Global Privacy Platform, and Seller Defined Audiences.

What Are User‑Paid IDs?

User‑paid IDs are identifiers anchored in a value exchange where the user has a direct paid relationship that can be verified by the publisher or app. They are typically consented, persistent across devices or sessions, and governed by strong privacy terms. Common forms include:

Subscriber IDs: Derived from paid subscriptions or memberships, often linked to email or account IDs in hashed or tokenized form.
Passkey or federated login tokens: Credentials originating from secure authentication (for example FIDO passkeys) that can bind sessions without exposing raw PII.
Wallet‑based tokens: Pseudonymous proofs from consumer wallets where the wallet controls attestations about the user’s consent or tier.
Customer data platform tokens: Publisher‑issued tokens mapped to first‑party profiles, sometimes extended into clean rooms for measurement.
CTV account identifiers: Subscriber or household tokens within streaming apps, typically scoped to the app and governed by platform policies.

These IDs differ from legacy device identifiers or third‑party cookies. The persistence stems from the user’s ongoing paid relationship; consent can be explicit and renewable; and the value exchange is transparent. For advertisers, that means better addressability and measurement. For publishers and SSPs, that means structurally higher yield potential that should be priced and proven.

Why the Sell Side Should Lead

When identity value is proven at the supply source, the sell side captures more of the economics. That requires a pricing system tied to identity quality, a measurement plan that proves incremental performance, and packaging that helps buyers commit budget at scale.

Control and transparency: Publishers can verify consent and set clear identity service levels, reducing buyer uncertainty and performance risk.
Yield and stability: Durable IDs enable frequency management, multi‑touch measurement, and optimization that drive predictable CPM lift.
Privacy‑by‑design: Supply‑side governance can enforce tokenization, purpose limitation, and expiration, keeping compliance tight while sustaining value.
Cross‑channel leverage: Web, app, and CTV can share a common blueprint for identity packaging and auction signaling, even when the underlying IDs differ.

A Blueprint For Pricing User‑Paid IDs

Pricing identity should be systematic, evidence‑based, and aligned to privacy. The following blueprint contains four pillars: Identity Quality Scoring, Uplift Measurement, Auction Mechanics, and Packaging.

1) Identity Quality Scoring

A standardized score helps translate heterogeneous IDs into a pricing signal. We recommend an Identity Quality Score (IQS) between 0 and 1 that incorporates five weighted factors:

Verification strength: Degree of authentication (for example email verification, passkey, two‑factor authentication).
Persistence horizon: Expected lifetime and cross‑device scope subject to purpose and consent.
Recency and activity: Last login or paid event, plus on‑site engagement recency.
Consent and scope: Evidence of consent (under GPP or equivalent), permitted purposes, regional flags, and expiration rules.
Collision and portability: Risk of duplicate identities in session, and whether the ID can be mapped in clean rooms for measurement.

An example formula:

IQS = 0.30*Verification + 0.20*Persistence + 0.20*Recency + 0.20*Consent + 0.10*CollisionInverse

Scores should be recomputed at impression time or session start, cached for latency control, and exposed to the auction as a supply signal without revealing PII.

2) Uplift Measurement

Identity should be priced on proven incremental performance, not theory. That means controlled experiments.

Identity on/off A/B testing: Randomized assignments at user or session level with otherwise identical targeting, to isolate identity’s contribution to CPM, win rate, CTR, CPA, or ROAS.
Holdout cohorts: Consistent 5 to 10 percent holdouts to track long‑term deltas without cross‑contamination.
Clean room attribution: Privacy‑preserving match in a neutral environment to measure post‑exposure outcomes without leaking raw user data.
Media mix calibration: Match identity lift against cohort or contextual baselines to understand substitution effects.

We will provide simple SQL‑style pseudocode later to compute lift and confidence intervals.

3) Auction Mechanics

You will need a consistent way to turn IQS and measured uplift into money in a first‑price world.

Identity‑adjusted floors: Dynamic floors that reflect expected CPM based on IQS and observed lift, with bounds to prevent extreme jumps.
Priority lanes: Private marketplace or programmatic guaranteed deals with identity SLAs get higher priority and lower uncertainty for buyers.
Supply signals: Identity metadata travels via OpenRTB user.ext and eids, along with consent signals in regs.gpp and user.ext.consent.
Transparency in logs: Bid request and auction logs should carry non‑PII identity flags so buyers can audit performance and fees.

4) Packaging For Buyers

Buyers want reliability and scale. Package identity as an SKU with SLAs.

Identity tiers: Bronze (IQS 0.3 to 0.5), Silver (0.5 to 0.7), Gold (0.7 to 0.9), Platinum (0.9+). Each tier comes with expected match rate and measurement support.
Deal ID catalog: Curate PMPs with identity tiers, contextual signals, and vertical metadata to map budget lines easily.
Measurement add‑ons: Optional clean room or conversion API support for high‑intent buyers that need outcome proof.
CTV and app variants: Offer channel‑specific packages that align with device policies and measurement realities.

Fair Value Transfer: Paying It Forward To Users

User‑paid IDs exist because users fund content and utility. Fair value transfer means users see meaningful benefits when their consented identity improves advertising yield. Models to consider:

Subscription credits: A small monthly credit or discount funded from identity uplift margin when ads are personalized under consent.
Loyalty points: Points redeemable for content unlocks or partner perks awarded for sustained identity participation.
Ad experience upgrades: Fewer interruptions, higher quality video, or reduced ad load when identity is active and measurable.
Transparent dashboards: Users can see and control their participation, revoke consent easily, and review the benefits they received.

Governance matters. Maintain purpose limitation, provide granular controls, document DPIAs, and normalize consent signaling via the Global Privacy Platform so downstream partners respect user choices.

Standards And Interop You Should Leverage

Identity in programmatic is only as strong as its interoperability and compliance. The following standards are relevant:

OpenRTB 2.6: Supports richer supply signals, inventory types, and user.ext structures for identity metadata.
IAB Tech Lab Global Privacy Platform: A unified payload for multiple privacy regimes, including TCF and US state signals.
Seller Defined Audiences: A taxonomy and signaling framework for publisher‑defined cohorts that can complement identity.
Prebid: Client and server frameworks with user ID modules and consent integration across web and app.
ads.txt and sellers.json: Foundation for supply transparency and authorized selling paths that should be consistent with identity packaging.

References for deeper reading:

IAB Tech Lab: OpenRTB 2.6 Specification
IAB Tech Lab: Global Privacy Platform
IAB Tech Lab: Seller Defined Audiences (SDA)
Prebid.org: User ID Modules and Consent Management
Implementation Blueprint: Web

Prebid.js Configuration Example

Below is an example configuration that enables a mix of user ID modules, ties into consent, and sets storage rules. Treat the actual modules as placeholders for your stack and privacy posture.
```
pbjs.setConfig({
consentManagement: {
cmpApi: 'iab',
timeout: 8000,
allowAuctionWithoutConsent: false,
defaultGdprScope: true
},
userSync: {
userIds: [
{
name: 'uid2',
storage: { type: 'html5', name: 'uid2_token', expires: 30 },
params: { uid2Token: window.__UID2_TOKEN__ } // token sourced from secure first-party endpoint
},
{
name: 'unifiedId',
storage: { type: 'html5', name: 'tdid', expires: 30 },
params: { partner: 'publisher', url: '/id/tdid' }
},
{
name: 'pubProvidedId',
storage: { type: 'html5', name: 'ppid', expires: 30 },
params: { eids: window.__PPID_EIDS__ } // publisher-provided hashed identifiers
}
],
syncDelay: 2000,
filterSettings: { iframe: { bidders: '*', filter: 'include' } }
},
priceFloors: {
floorMin: 0.30,
floorProvider: 'identityAdaptive',
enforceFloors: true
},
identity: {
iqsProvider: '/api/identity/iqs', // returns IQS per session
upliftBounds: { min: 1.05, max: 1.45 }
}
});
```
Key points:
- Consent gating: Never load or pass IDs without valid consent for the region and purpose.
- Publisher provided IDs: Keep them tokenized and renew on login events.
- Floors tied to identity: Use a service that returns identity‑adjusted floors based on IQS and measured lift.
OpenRTB 2.6 Bid Request Example

This is a simplified example of how to convey identity and privacy signals.
```
{
"id": "req-123",
"imp": [{
"id": "1",
"banner": { "w": 300, "h": 250 }
}],
"site": { "domain": "example.com", "page": "https://example.com/article" },
"user": {
"id": "pub-session-abc",
"ext": {
"eids": [
{
"source": "uidapi.com",
"uids": [{ "id": "AAABBBCCC", "atype": 1 }]
},
{
"source": "publisher-provided-id",
"uids": [{ "id": "PPID_HASH_XYZ", "atype": 3 }]
}
],
"iqs": 0.78
}
},
"regs": {
"gpp": "DBABBg~CPXxRfAPXxRfAAfYB...",
"gpp_sid": [2, 7]
},
"source": {
"ext": {
"schain": { "ver": "1.0", "complete": 1, "nodes": [{ "asi": "ssp.example", "sid": "1234", "hp": 1 }] }
}
},
"ext": {
"identity": {
"tier": "Gold",
"sla": { "min_match_rate": 0.55, "max_advertiser_lookback_days": 30 }
}
}
}
```
Practices to follow:
- Tokenization: Never send raw emails or PII. Rely on standardized eids and publisher‑provided tokens.
- Consent: Include GPP or regional signals consistently, and drop identity signals when consent is absent.
- Identity SLA markers: Non‑binding fields that inform buyers of expected match quality without leaking secrets.
Implementation Blueprint: Mobile App

Mobile presents added constraints and opportunities.
- iOS: IDFA is permissioned via ATT, IDFV remains app‑scoped. Lean into login‑based IDs and SKAdNetwork measurement for outcomes.
- Android: Privacy Sandbox on Android shifts to SDK‑Runtime and Topics APIs. First‑party login remains a durable anchor.
- In‑app Prebid: Prebid Mobile supports user ID modules subject to consent. Use server‑side adapters to manage complexity and latency.
Example Prebid Mobile user ID configuration (Kotlin pseudo):
```
val userIds = listOf(
UserIdModule(
name = "pubProvidedId",
params = mapOf("eids" to getPPIDEids()),
storageDays = 30
),
UserIdModule(
name = "uid2",
params = mapOf("uid2Token" to secureTokenProvider()),
storageDays = 14
)
)
PrebidMobile.setUserIds(userIds)
PrebidMobile.setGPPString(currentGPP())
PrebidMobile.setEnforceConsent(true)
```
Implementation Blueprint: CTV

CTV runs inside app environments with their own identity and privacy rules.
- Household scope: IDs often map to a household account rather than a single person; frequency and measurement should reflect that.
- Subscription tokens: Treat account sign‑in as your root of trust; rotate tokens and honor device policies.
- Deal‑first packaging: Many CTV buyers prefer PMPs with identity guarantees and fixed ad pod governance.
- ACR and contextual signals: Complement identity with high‑quality signals that are compliant and do not overexpose device attributes.
OpenRTB request fields remain similar, but many integrations will be private marketplace or programmatic guaranteed with custom deal metadata for identity SLAs and pod rules.

Measurement: Proving Incremental Value

A rigorous plan prevents identity pricing from becoming a faith exercise.

Experiment Design
- Randomization unit: Use user or household where possible. If not available, randomize sessions with sticky assignment.
- Consistent holdout: Keep a stable 5 to 10 percent holdout at all times for rolling benchmarks.
- Outcome metrics: Beyond CPM lift, track win rate, CTR, conversion rate, CPA, and downstream ROAS where buyers support it.
- Time windows: Identity benefits compound over time. Use 7‑day and 28‑day readouts.
Simple SQL‑style Lift Calculation
```
WITH base AS (
SELECT
test_group,            -- 'ID_ON' or 'HOLDOUT'
AVG(cpm) AS avg_cpm,
AVG(win) AS win_rate,  -- 0/1 per auction
AVG(click) AS ctr,     -- 0/1 per impression
COUNT(*) AS imps
FROM auction_outcomes
WHERE date BETWEEN CURRENT_DATE - INTERVAL '28 day' AND CURRENT_DATE
GROUP BY test_group
),
calc AS (
SELECT
(SELECT avg_cpm FROM base WHERE test_group='ID_ON') /
NULLIF((SELECT avg_cpm FROM base WHERE test_group='HOLDOUT'), 0) AS cpm_uplift,
(SELECT win_rate FROM base WHERE test_group='ID_ON') -
(SELECT win_rate FROM base WHERE test_group='HOLDOUT') AS win_rate_delta
)
SELECT * FROM calc;
```
Tie pricing to statistically significant uplift, not small fluctuations. Use bootstrapping or t‑tests to validate significance where your data science team is comfortable.

Turning IQS Into Floors

Identity‑adjusted floors are effective when bounded and empirically calibrated.
```
def identity_adjusted_floor(base_floor, iqs, uplift_curve):
# uplift_curve maps IQS to expected CPM multiplier, trained on past experiments
multiplier = uplift_curve.predict(iqs)
multiplier = max(1.05, min(multiplier, 1.45))  # guardrails
return round(base_floor * multiplier, 2)
```
Operational guidelines:
- Guardrails: Avoid volatile floors that whipsaw demand. Start conservative and tune quarterly.
- Feedback loop: Refresh uplift curves monthly using new experiments and buyer feedback.
- Transparency: Document identity floor logic to internal teams and major buyers under NDA.
Packaging: From Identity To Product

Identity should be sold like a product, not sprinkled like magic.
- Tiered PMPs: Each tier declares expected match rate, frequency control confidence, and measurement options.
- Programmatic guaranteed: Lock in budgets for premium identity supply with clear delivery and measurement SLAs.
- Vertical alignment: Finance, retail, and autos value durable IDs. Create vertical collections with relevant contextual signals.
- Seasonal packs: Align to retail calendars where buyers have higher tolerance for PMPs with strong identity.
Documentation should include:
- Identity SLA: Minimum IQS, expected match rate, and consent coverage by region.
- Measurement support: Clean room partners, conversion APIs, and lookback windows.
- Privacy posture: Tokenization, retention policies, and incident response.
Fair Value Transfer Mechanics

How does uplift reach users in practice?
- Revenue allocation: Dedicate a fixed percentage of identity‑attributed uplift margin to credit pools or loyalty programs.
- Eligibility: Participation requires active consent and verified subscription or login. Users can opt out at any time.
- Accounting: Calculate identity uplift monthly against a rolling holdout and distribute benefits transparently.
- Messaging: Keep the message clear: your login gives us permission to improve your ad experience; in return you get credits or fewer ads.
Data Architecture: Privacy‑By‑Design

Identity value is fragile if privacy is weak. Build for compliance from the start.
- Tokenization and rotation: Never store or transmit raw PII. Rotate tokens on a defined cadence and upon risk events.
- Scoped keys: Key management scoped by partner and purpose to prevent cross‑partner correlation.
- Purpose enforcement: At request time, verify that the downstream bidstream purpose matches user consent.
- Audit trails: Immutable logs that prove consent state, identity presence, and purpose checks without exposing PII.
Minimal Identity Schema (Pseudocode)
```
IdentityEvent:
event_id: uuid
ts: timestamp
user_scope_id: string        # pub-scoped, rotated
iqs: float                   # 0..1
consent:
gpp: string
jurisdiction: string
purposes: [string]
expires_at: timestamp
eids:
```

source: string atype: int token_hash: string # never raw session: device_type: string channel: enum(web, app, ctv) region: string


## SSP Considerations
SSPs are the connective tissue that can normalize, signal, and price identity consistently across publishers.
<ul>
<li><strong>Normalization</strong>: Convert diverse publisher signals into a consistent eids structure with attached IQS and consent validity.</li>
<li><strong>Supply segmentation</strong>: Create inventory buckets by identity tier for routing and logging consistency.</li>
<li><strong>Buyer education</strong>: Publish a transparent methodology guide on how identity floors are computed and verified.</li>
<li><strong>Fee transparency</strong>: Separate identity enablement fees from standard take rates in reporting to avoid confusion.</li>
</ul>
## Governance, Legal, And Risk
Identity pricing cannot ignore policy. Avoid these pitfalls.
<ul>
<li><strong>Consent drift</strong>: Users change preferences. Enforce real‑time checks and stop identity signaling instantly upon revocation.</li>
<li><strong>Regulatory change</strong>: Build policy abstraction layers so new rules map to consent purposes without refactoring pipelines.</li>
<li><strong>Partner lock‑in</strong>: Use standards‑based IDs where possible and maintain abstraction so you can swap vendors with limited friction.</li>
<li><strong>Data quality</strong>: Garbage in means garbage out. Monitor match rates, error budgets, and freshness SLAs.</li>
</ul>
## Economics: A Simple ROI Model
Identity pricing must net out after costs.
Let:

Base CPM = B
Identity CPM with uplift = U
Incremental CPM lift = L = U − B
Identity costs per impression = C (licensing, compute, clean room fees)
Distribution to users = D (credits, discounts)
Net identity margin per impression = M = L − C − D You should allocate floors and packaging such that M stays positive and grows with scale. Publish net identity margin targets internally and adjust tiers when the realized M underperforms for two consecutive months.
Example: From Raw Signals To Productized Identity
1. Day 0 to 30: Implement login flows with clear consent notices, tokenization, and a minimal IQS calculator. Start a 10 percent holdout.
2. Day 30 to 60: Launch Bronze and Silver PMPs, each with target match rates and measurement support. Begin clean room trials with 2 to 3 anchor buyers.
3. Day 60 to 90: Publish uplift readouts. Add identity‑adjusted floors on open auction where demand supports it. Introduce user credits for consenting subscribers funded by realized uplift.
  CTV Specific Guidance
  
  CTV identity is often higher value due to screen context and co‑viewing. Price carefully.
  - Household frequency: Identity enables cross‑day household frequency caps that buyers value. Monetize via guaranteed deals.
  - Pod governance: Integrate identity tiers into pod rules so buyer brands avoid adjacency conflicts while preserving yield.
  - Privacy posture: Do not pass device serials or sensitive signals. Stick to account tokens, eids, and consent flags.
  - Measurement partnerships: Enable clean room outcomes or panel calibration for household ROAS where possible.
  Mobile App Specific Guidance
  - Lean on login: ATT limits IDFA availability. Login‑based tokens with clear consent provide durable alternatives.
  - On‑device computation: Consider computing IQS and consent enforcement on device to minimize server round trips.
  - SKAdNetwork alignment: For performance buyers, align identity pricing with SKAN postbacks that show improved conversion value distribution.
  Demand Alignment: Helping Buyers Buy
  
  Make it easy for buyers to switch budget into identity‑rich supply.
  - Deal taxonomies: Use consistent naming: RV‑Gold‑News‑US‑Viewable90 to encode tier, category, region, and viewability.
  - Fee clarity: Provide line‑item breakdowns for identity enablement in reporting and buyer‑visible logs.
  - Case studies: Publish anonymized uplifts and measurement stories with confidence intervals, not just point estimates.
  Reporting And Auditing
  
  Buyers should be able to verify what they paid for.
  - Log fields: Identity tier, IQS bucket, consent valid flag, and floor applied. Avoid PII in any logs.
  - Reconciliation: Monthly reconciliation of promised vs delivered identity mix by deal.
  - Independent audit: Invite periodic audits of identity SLAs and measurement methodology from trusted partners.
  Example Log Extract (CSV)
```
ts,imp_id,deal_id,identity_tier,iqs_bucket,consent_valid,floor_applied_cpm,clearing_price_cpm,win
2025-09-14T10:12:00Z,imp-001,RV-Gold-News-US-001,Gold,0.7-0.8,true,1.20,3.45,1
2025-09-14T10:12:01Z,imp-002,RV-Silver-Lifestyle-UK-003,Silver,0.5-0.6,true,0.80,1.95,1
2025-09-14T10:12:02Z,imp-003,,Bronze,0.3-0.4,false,0.30,0.55,0
```
  Common Anti‑Patterns To Avoid
  - Identity floor whiplash: Over‑reacting to weekly noise creates instability. Use multi‑week windows and guardrails.
  - PII leakage: Hashing alone is not a privacy panacea. Combine tokenization, salting, and strict purpose limitation.
  - Opaque packaging: Buyers will not pay premiums for mystery boxes. Document identity tiers and SLAs plainly.
  - One‑size pricing: Web, app, and CTV differ. Calibrate floors and deals to channel realities.
  How Red Volcano Can Help
  
  As a supply intelligence platform, Red Volcano can serve as the discovery and monitoring layer for identity‑priced supply.
  - Discovery: Identify publishers and apps with user‑paid identity capabilities, subscription footprints, and clean room integrations.
  - Tech stack tracking: Monitor adoption of user ID modules, consent frameworks, and clean room SDKs across properties.
  - Ads.txt and sellers.json correlation: Validate authorized sellers and resellers for identity‑priced PMPs.
  - CTV intelligence: Map streaming apps with account‑based identity and help SSPs assemble high‑confidence CTV supply packages.
  - Sales enablement: Equip SSP BD teams with identity tier insights and packaging guides for outreach.
  A Phased Roadmap For Publishers And SSPs
  
  Phase 1: Foundations (0 to 30 days)
  - Consent and login: Ensure clear notices, GPP wiring, and tokenized login flows.
  - IQS v1: Implement the first scoring model and add identity flags to your bidstream.
  - Holdout cohort: Start a persistent 10 percent holdout to build measurement history.
  Phase 2: Monetization (30 to 90 days)
  - Tiered PMPs: Launch Bronze and Silver. Add Gold once match rates stabilize.
  - Identity floors: Introduce modest identity‑adjusted floors in open auction with guardrails.
  - Buyer pilots: Run 3 to 5 paid pilots with clean room measurement and publish results internally.
  Phase 3: Scale and Value Transfer (90 to 180 days)
  - Programmatic guaranteed: Lock in multi‑quarter budgets for top identity supply.
  - User credits: Launch credits or discounts funded from proven uplift margin.
  - Audit and certification: Invite a neutral audit of your identity SLAs and publish a summary for buyers.
  Frequently Asked Questions
  - Will buyers pay more for identity now? Yes when you prove incremental performance and reduce risk with SLAs. Anchor pricing in measured lift.
  - Is this only for logged‑in users? Mostly yes, although you can combine with contextual and SDA for broader reach without personal data.
  - What about browser changes? A login‑anchored token strategy is resilient to cookie restrictions because it does not rely on third‑party storage.
  - How does this work in CTV? Use account‑based tokens, deal packaging, and household‑level frequency and measurement.
  Conclusion
  
  User‑paid IDs are not a silver bullet, but they are a durable, privacy‑aware foundation for addressability across web, app, and CTV. The sell side can and should lead by converting identity into a clear product: a scored signal tied to consent, a pricing system tied to measured uplift, and packaging that buyers understand and can commit to at scale. Do this with privacy‑by‑design, transparent logs, and fair value transfer back to users. Make identity an incentive alignment mechanism: users get better experiences and tangible benefits, publishers earn sustainable yield, and advertisers get performance they can measure. The sooner you standardize your blueprint, the faster you capture the structural advantage identity can deliver.
  
  References and Further Reading
IAB Tech Lab. OpenRTB 2.6 Specification. https://iabtechlab.com
IAB Tech Lab. Global Privacy Platform. https://iabtechlab.com
IAB Tech Lab. Seller Defined Audiences. https://iabtechlab.com
Prebid.org. User ID Modules and Consent Management. https://prebid.org
IAB. Transparency and Consent Framework. https://iabeurope.eu These resources provide the technical grounding for the signaling, consent, and measurement approaches outlined in this article.

Introduction

What Are User‑Paid IDs?

Why the Sell Side Should Lead

A Blueprint For Pricing User‑Paid IDs

1) Identity Quality Scoring

2) Uplift Measurement

3) Auction Mechanics

4) Packaging For Buyers

Fair Value Transfer: Paying It Forward To Users

Standards And Interop You Should Leverage

Implementation Blueprint: Web

Prebid.js Configuration Example

OpenRTB 2.6 Bid Request Example

Implementation Blueprint: Mobile App

Implementation Blueprint: CTV

Measurement: Proving Incremental Value

Experiment Design

Simple SQL‑style Lift Calculation

Turning IQS Into Floors

Packaging: From Identity To Product

Fair Value Transfer Mechanics

Data Architecture: Privacy‑By‑Design

Minimal Identity Schema (Pseudocode)

Example: From Raw Signals To Productized Identity

CTV Specific Guidance

Mobile App Specific Guidance

Demand Alignment: Helping Buyers Buy

Reporting And Auditing

Example Log Extract (CSV)

Common Anti‑Patterns To Avoid

How Red Volcano Can Help

A Phased Roadmap For Publishers And SSPs

Phase 1: Foundations (0 to 30 days)

Phase 2: Monetization (30 to 90 days)

Phase 3: Scale and Value Transfer (90 to 180 days)

Frequently Asked Questions

Conclusion

References and Further Reading