Property Intelligence Workspace

One place to understand what a property did—and what to do next.

Start from the show, album, podcast, YouTube channel, franchise, product line, or brand. Marble organizes every unit, audience signal, creator contribution, impact model, value range, and source around that durable object.

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Public-data read with zero setup
Measured, estimated, and derived evidence kept distinct
Coverage and next-best data connection shown for every decision

Illustrative example

Example documentary series · Property overview

Demo data

Example property

Series · 3 episodes live

Public data active

Owned

Official channels and full episodes

Partner

Creator clips and network amplification

Earned

Press, podcasts, reviews, and conversation

Discovered

Unbriefed public activity auto-linked to the property

Observed

measured

Audience movement

Direct platform signals · high confidence

Incremental

estimated

Above baseline

Likelihood stated · directional

Coverage

Question by question

Gaps named openly

Marble AI reads the whole property. Every conclusion links back to the signals, assumptions, and missing sources behind it.

Portfolio workspace

See every property at its current level of confidence.

Move from a portfolio scan into a property, unit, creator, source, or decision without losing context. Early properties can begin with public signals; mature properties can add partner and first-party evidence.

Illustrative example

Property portfolio workspace

Demo data

Your portfolio

One workspace across properties and units

Add property

Example sports series

Mature · public + partner data

Strong read

Example podcast pilot

Pilot · public-data read

Directional

Example product launch

Early · public signals

Emerging

Overview

The whole property, compressed into one decision surface.

Performance, audience creation, footprint layers, inferred impact, commercial value, next actions, and evidence coverage sit together—not in separate reporting tabs.

Illustrative example

Example documentary series · Property overview

Demo data

Example property

Series · 3 episodes live

Public data active

Owned

Official channels and full episodes

Partner

Creator clips and network amplification

Earned

Press, podcasts, reviews, and conversation

Discovered

Unbriefed public activity auto-linked to the property

Observed

measured

Audience movement

Direct platform signals · high confidence

Incremental

estimated

Above baseline

Likelihood stated · directional

Coverage

Question by question

Gaps named openly

Marble AI reads the whole property. Every conclusion links back to the signals, assumptions, and missing sources behind it.

Executive Summary

A verdict with its confidence attached.

The executive read explains what appears to have happened, what the evidence supports, where uncertainty remains, and which decision the current signal can responsibly inform.

Illustrative example

Executive summary

Demo data

AI-generated draftSignals reviewed · 24 demo signals

Property read

The release coincided with durable audience movement beyond the expected baseline.

The modeled contribution is directional; distribution and first-party conversion data would tighten the estimate.

Open evidence links

Next decision

Connect the missing signal before increasing spend.

Confidence-aware recommendationEvidence attached to claim

Audience

Who the property reaches—and how much of it is new.

Separate observed movement from estimated incrementality, map overlap across property, creator, and partner audiences, and keep the modeled contribution visible.

Illustrative example

Audience creation and overlap

Demo data

Reached

Engaged

Followed

Deeper engagement

Overlap

Why new viewers entered

estimated

Talent affinityRelative weight

Topic relevanceRelative weight

Partner reachRelative weight

Episodes and units

Understand which release moments changed the trajectory.

Episodes, tracks, fixtures, launches, or campaign moments become comparable units inside the property. Response curves and release context show where attention moved and where it held.

Illustrative example

Units and release moments

Demo data

Release 01

Measured

Release 02

Measured

Release 03

Inferred impact

Release 04

Unreleased

Creator Content

Connect partner media to the property outcome.

Official, commissioned, earned, and discovered content are classified together. Marble shows what traveled, who helped it travel, and what the current evidence can attribute to that activity.

Illustrative example

Creator and content intelligence

Demo data

Official channel

Owned footprint

Reference

Creator clip

Creator footprint

Tracked

Distribution partner

Partner footprint

Connected

Press mention

Earned footprint

Classified

Unbriefed public post

Discovered footprint

Auto-linked

Auto-discovery links public content back to the property even when it has no campaign tag or tracking link.

Impact

Compare what happened with what likely would have happened.

Observed signals sit beside an expected baseline, uncertainty, and inferred incremental range. Release markers and external drivers remain visible so the model supports judgment without claiming proof.

Illustrative example

Observed performance vs. expected baseline

Demo data

Measured result

measured

What happened

Expected baseline

Counterfactual

What likely would have happened

Inferred incremental

estimated

The modeled difference

ObservedExpected baselineInferred incrementalRelease

Observed. Direct platform and partner signals.

Compared. Seasonality and known drivers controlled.

Qualified. Range and likelihood attached.

Contributing signals · relative model weight

estimated

Release timingHigh

Partner contentMedium

Earned conversationDirectional

Decompose by release window, unit, and channel to inspect how the modeled contribution changes.

Inspect sources and assumptions

Commercial Value

Translate impact into a defensible range—not a revenue claim.

Conservative, expected, and upper cases make the valuation useful for rights, distribution, sponsorship, content, and reinvestment discussions while keeping assumptions inspectable.

Illustrative example

Commercial value range

Demo data

Modeled media-equivalent value

Lower bound — upper bound

derived

ConservativeExpectedUpper case

Audience-growth value

Scenario range

Earned-media value

Comparable basis

Sponsorship scenarios

Compare packages

Sponsor-category fit

Fit + inventory

A decision range, not booked revenue. Inputs, scenarios, and confidence remain inspectable.

Investment Case

Turn evidence into the next commitment.

The investment case answers six executive questions: did it work, what was uniquely created, what it is worth, what to do next and why, how confident the read is, and what would change the answer.

Illustrative example

Executive investment case

Demo data

Illustrative verdict

Continue selectively, strengthen distribution, and connect first-party data before scaling the commitment.

1Did it work?
2What did the property uniquely create?
3What is that impact worth?
4What should we do next — and why?
5How confident are we?
6What would change the answer?

Ranked next-best dollar

1Strengthen the best-performing distribution windowEvidence attached
2Connect first-party audience outcomesEvidence attached
3Test the highest-fit sponsor categoryEvidence attached

Data Sources

Coverage by analytical question—not a generic completeness score.

Every answer names the source, freshness, assumptions, gaps, and the connection most likely to narrow uncertainty.

More episodes will not fix this — the connection will.

Illustrative example

Data sources and confidence

Demo data

Public platform signals

Baseline coverage

Active

Creator and content graph

Partner context

Active

Partner reporting

Medium confidence gain

Optional

First-party outcomes

High confidence gain

Connect

Illustrative example

Coverage by analytical question

Demo data

Did the property create net-new audience?

Strong

Potential confidence uplift · Small remaining gain

Which release and partner activity mattered?

Directional

Potential confidence uplift · Partner data: medium gain

What is the impact worth?

Emerging

Potential confidence uplift · Outcome data: high gain

What should change next?

Directional

Potential confidence uplift · Cost data: medium gain

Public data starts the read. Connected partner and first-party sources narrow uncertainty.

Public data begins the viewConfidence improves without hiding earlier assumptions

See your first property read.

Bring a property and the decision behind it. Marble can begin with public evidence, then show exactly which additional connection would strengthen the case.

Request a Demo