Cross-platform measurement platform

Stop Double-Counting Customers Across Platforms

DriveMetaData reconciles web, app, CTV, paid media, CRM, commerce, and offline events into one trusted measurement view, so growth, finance, and data teams can see which journeys actually create revenue.

Stitch identities across CTV, web, app, CRM, and offline
Dedupe platform claims before finance sees revenue
Measure journey-level LTV, payback, and Verified ROAS
Export verified attribution decisions to BI and warehouse
app.drivemetadata.com / measurement/reconciliation-command
Double-counting control room
One customer, one journey-level revenue truth
3.8x
raw claims
-32%
duplicate credit
94%
confidence
CTV exposure
App install
Web purchase
CRM renewal
Duplicated platform claims
Metaclaims purchase$18.4k
Googleclaims same user$18.4k
CTVassisted exposure$3.3k
Journey confidence
Raw export status
journey_id ready
revenue verified
BI sync fresh
Device and identity graph
CUID
Device
Household
CRM
Claim reconciliation
Meta + Google duplicate: 21%
Verified winner: paid search · CTV assisted
Fraud-adjusted ROAS
Clean ROAS4.9x
Invalid traffic17%
AI optimization
Shift 16%
from overlapping retargeting to verified acquisition journeys
What you can see

The Journey, the Reconciliation, and the Proof

Three operating views show the path, the decision, and the evidence behind every exported attribution answer.

DriveMetaData product visualization showing CTV, mobile, web, CRM, and offline touchpoints connected to verified revenue.
Journey timeline
See one customer move from CTV exposure to app install, web purchase, CRM renewal, and offline sale without losing assist or revenue context.
DriveMetaData product visualization showing devices, sessions, CRM records, and revenue joined into one identity graph.
Reconciliation ledger
Compare platform claims against first-party identity and finance-approved revenue before reporting ROAS.
DriveMetaData product visualization showing consent, SKAN, server-side events, fraud scoring, and trusted ROAS.
Confidence layer
Expose privacy mode, fraud adjustment, identity confidence, and raw export lineage in the same operating view.
The cross-platform problem

Customers Move Across Screens. Platforms Double-Count Them.

A single buyer can look like many users. DriveMetaData groups the signals, dedupes credit, and shows which claims are trusted.

app.drivemetadata.com / measurement/cross-platform-reconciliation
Media
CTV exposed householdMeta claimed installGoogle claimed purchase
Owned
App saw device userCRM tied renewalCommerce booked order
Late signals
Offline import landedSKAN arrived aggregatedFraud spike flagged
Verified journey-level truth
One winner, retained assists, rejected duplicates, and late corrections in one decision ledger.
1
winner
2
assists
3
rejects
What breaks before reconciliation
One customer becomes five reported users
Every platform over-claims the same revenue
CTV and mobile assists disappear from LTV
Finance cannot tie ROAS to booked revenue
Late SKAN and offline signals change the answer
Fraud makes bad spend look scalable
Result: one customer, one revenue truth
Winners, assists, rejected claims, and late corrections are visible before budget decisions move.
Journey-level measurement

Measure the Customer Journey, Not the Device

A mobile-first rail keeps the journey readable: signal, decision state, value, and why it matters.

CTV exposure -> mobile installMobile app -> web checkoutPaid click -> owned CRM nurtureAnonymous session -> known customerSubscription -> offline renewalFraud-adjusted ROAS -> clean budget move
app.drivemetadata.com / journeys/cross-platform-path
1
CTV
Household exposure
assist kept76%

Household signal stays visible after final credit is deduped.

2
Mobile
App install
identity linked91%

Device and customer IDs are joined with consent state attached.

3
Web
Checkout
winner scored$18.4k

Revenue is matched before the platform claim is published.

4
CRM
Renewal
LTV joined$42.7k

Lifecycle value flows back to acquisition and assist reporting.

5
Offline
Store sale
versionedlate

Delayed imports update the answer without losing lineage.

Reconciled journey output
Identity confidence, assists, winner credit, LTV, fraud adjustment, and raw export lineage are calculated before reporting.
94%
identity
4.9x
clean ROAS
1
export
Measurement architecture

Collect, Stitch, Reconcile, Score, and Export

The architecture is simple enough to scan on mobile and specific enough for data teams to inspect on desktop.

Identifier setup

Recommended inputs include customer_id, hashed email or phone, device ID, household ID, order ID, CRM account ID, consent state, and event timestamp. Missing identifiers are modeled and labeled instead of silently trusted.

app.drivemetadata.com / identity/cross-device-graph
1
SDK + S2S
Collect

Capture web, app, CTV, partner, CRM, commerce, and offline events.

ConsentTimestampSource
2
customer_id/CUID
Stitch

Resolve first-party IDs, hashed identifiers, devices, households, and sessions.

ID graphMatch scorePrivacy mode
3
claim ledger
Reconcile

Compare platform claims against one journey graph before credit is assigned.

WinnerAssistsRejects
4
Verified ROAS
Score

Adjust decisions for identity quality, modeled signals, revenue truth, and fraud.

ConfidenceClean ROASRisk
5
raw + BI
Export

Send raw events, identity links, decisions, LTV cohorts, and revenue fields.

WarehouseAPIAudit
Input
events + identifiers + consent
Decision
winner, assists, rejects, confidence
Output
raw export + BI rollup + API
Measurement methodology

A Decision Map for Identity, Consent, Fraud, and Revenue

Every claim passes through the same visible gates before it becomes a winner, assist, reject, or finance-ready export.

app.drivemetadata.com / measurement/decision-map
01
Identity
Link known and anonymous touches into one journey
Input
customer_id, hashed email, household, device
Proof
94% match confidence
02
Consent
Label observed, modeled, delayed, or restricted data
Input
consent state, SKAN, regional policy, retention
Proof
Privacy mode travels with every event
03
Fraud
Filter bad sources before ROAS and payback update
Input
click spikes, device farms, invalid traffic risk
Proof
Clean and polluted ROAS separated
04
Revenue
Publish winner, assists, rejects, and finance truth
Input
commerce, refunds, CRM deals, offline imports
Proof
Raw decision exported to BI
-37%
duplicate credit

same conversion no longer claimed by every platform

94%
identity confidence

first-party and modeled links stay labeled

4.9x
clean ROAS

invalid traffic removed before budget moves

1 feed
warehouse proof

raw events, decisions, revenue, and audit lineage

Raw data and warehouse outputs

Export the Proof Behind Every Attribution Decision

Raw rows stay readable: what happened, what won credit, why it won, and how fresh the proof is.

Raw event and decision feeds for BI and data science
Journey-level LTV, payback, assist, and winner fields
Export status, freshness, and audit lineage for every sync
Warehouse-ready freshness

Streaming exports keep operational dashboards current, while batch backfills preserve late SKAN, CRM, refund, and offline sales corrections without overwriting prior audit history.

app.drivemetadata.com / exports/raw-attribution-decisions
journey_idjrn_8f21Stable customer journey key
identity_confidence94%Deterministic plus modeled match score
winning_creditGoogle Search 42%Deduped attribution decision
assisted_creditCTV 18%Journey assist retained for LTV
revenue_statusfinance_verifiedBooked revenue joined
fraud_adjusted_roas4.9xInvalid traffic removed
Enterprise trust

Privacy, Governance, and Auditability Built Into the Measurement Layer

Consent state, export history, retention, and security controls stay attached to each decision.

RBAC, SSO, SCIM, and workspace permissions
Audit logs for identity merges, rule changes, and exports
Data retention, residency, data processing terms, and consent controls
SOC 2 and ISO-aligned control mapping for security review
app.drivemetadata.com / trust/governance-review
Consent-aware measurement status
SKAN
aggregated · modeled
Web
consented · observed
CTV
household · assisted
Identity rule changedadminaudited
Warehouse export syncedBIfresh
Revenue correction appliedfinanceversioned
Data retention policyregionenforced
Confidence layer

Turn Reconciled Signals Into Actionable Verified ROAS

Rank duplicate claims, weak identity, delayed revenue, suspicious sources, and safer budget moves.

Recommendation example

Meta, Google, and CTV overlap is reducing retargeting confidence. Shift budget toward verified acquisition cohorts with higher first-party revenue match quality.

app.drivemetadata.com / ai-measurement/cross-platform-cockpit
Duplicate claim detection
Ranked by confidence, revenue impact, and optimization urgency.
Journey gap alerting
Ranked by confidence, revenue impact, and optimization urgency.
Revenue mismatch detection
Ranked by confidence, revenue impact, and optimization urgency.
Verified ROAS scoring
Ranked by confidence, revenue impact, and optimization urgency.
Fraud-adjusted performance

Protect LTV and Payback From Polluted Platform Signals

Separate clean ROAS from polluted ROAS before LTV, payback, and budget optimization update.

app.drivemetadata.com / performance/fraud-adjusted-roas
Invalid traffic and click spam filtering
Bot, device farm, and suspicious conversion scoring
Partner and source quality adjustment
Clean vs polluted ROAS and payback views
Journey examples

Real Cross-Platform Paths, Not Channel Checklists

Each path shows the source, the conversion handoff, and the decision that keeps credit clean.

Filter by source, identity, revenue, export status, or fraud quality
CTV to mobile
CTV exposure
Mobile install
In-app trial
Web purchase

Keep the assisted CTV contribution without letting it double-claim final revenue.

Web to app
Paid search
Web product view
App install
Subscription

Connect anonymous web intent to the known app customer and cohort LTV.

App to web
Push
App session
Desktop checkout
Refund adjusted

Join purchase and refund truth before ROAS is sent to finance or BI.

CRM to offline
Email nurture
CRM opportunity
Store sale
Renewal

Attribute offline and renewal revenue back to the full digital journey.

Paid to owned
Meta click
Email signup
SMS offer
Commerce order

Separate paid acquisition credit from owned-channel conversion lift.

Enterprise architecture

A Launch Path Teams Can Actually Follow

Implementation moves from capture to governance without hiding the decision layer inside another dashboard.

Architecture layers
SDK and server-side collectionIdentity and consent graphClaim reconciliation engineFraud and confidence scoringRaw export and warehouse syncGovernance, audit, and SLA controls
Week 1
Event plan and identifiers
Week 2
SDK, S2S, and partner capture
Week 3
Reconciliation and export QA
Week 4
BI, governance, and launch review
Growth decisions

Turn Journey-Level Measurement Into Finance-Ready Decisions

The page ends with proof points buyers can scan quickly and hand to growth, finance, and data teams.

-37%
Duplicate conversion credit
94%
Journey confidence score
4.9x
Fraud-adjusted clean ROAS
1 feed
Raw export for BI and warehouse
+31%
First-party revenue match rate
2.6x
Faster budget optimization
5 steps
Collect, stitch, reconcile, score, export
1 view
Growth, finance, and data alignment

Build Journey-Level Measurement Truth.

See how DriveMetaData stitches identities, dedupes platform claims, verifies revenue, exports raw decisions, and protects cross-platform ROAS from fraud.