Data & methodology

Public Roblox data vs owner analytics

Roblox game analysis has two evidence layers. Public data is useful for market discovery: it shows what Roblox exposes about a game and what an independent observer can record over time. Owner analytics describes unique users, cohorts, acquisition, play behavior, and business outcomes. Mixing the layers creates confident but false conclusions. The correct approach is to use public evidence to form questions, then use authorized owner data to answer the questions that involve players, sources, retention, or money.

MARPLA team · Published 2026-09-09 · Updated 2026-09-18 · 5 min read

Full guide

Start with the essentialsPublic vs owner Roblox analytics: the access boundary Knowledge sectionData & methodology →

Editorial illustration

What public observation can support

Roblox’s Analytics Home documentation lists title, owner, CCU, updated date, and like ratio as public watchlist statistics when the viewer lacks analytics permission. MARPLA also records publicly returned Visits, favorites, and vote counters and builds history from its own timestamped snapshots. From that history it can describe observed CCU means, peaks, growth between equal windows, Visits deltas, and public counter ratios.

These are market signals. They can answer whether activity was present, whether the observed baseline moved, and how a game compares with carefully chosen public peers. They cannot identify unique daily users, acquisition sources, cohort return behavior, actual session time, revenue, payer behavior, costs, or profit. A calculated session estimate or CCU-to-Visits ratio must remain labeled as an estimate or normalization, never renamed as a private KPI.

Public or derived	Owner-only	Why the boundary matters
CCU snapshot and observed history	DAU and new users	Concurrent activity is not unique audience
Cumulative Visits and deltas	Acquisition by source	Entries do not reveal where users came from
Rating, vote count, favorites	Retention and session time	Public actions do not show cohort behavior
Reported update time	Revenue, payers, ARPPU	Activity and commercial performance differ

What authorized analytics adds

Creator Analytics provides permitted owners and group members with DAU, new users, session time, retention, acquisition, demographics, feedback, monetization, and other KPI views. Retention is cohort-based: D1, D7, and D30 mature after their respective delays. Acquisition separates sources and reports conversion and downstream quality, while monetization includes revenue, paying users, conversion, ARPPU, and ARPDAU.

Access is also a data-governance boundary. Group games require sufficient analytics permissions, and some metrics are sensitive. A connection should request only the scopes required for the selected functionality, explain the target Universe, and avoid exposing credentials or copying private results into a public profile. Permission grants access to data; it does not prove ownership, accuracy of every business claim, or authorization to publish that data.

Move from public question to private answer

Begin with a public observation such as “mean CCU increased after 3 September.” Convert it into questions: did unique DAU rise, which source supplied the users, did new-user first-session retention change, did D1/D7 hold, and did revenue move without damaging payer conversion or player satisfaction? Ask the owner to open those charts for the same dates and segments.

Align definitions and time zones before reconciling numbers. Public snapshots may be more frequent but less complete; Creator Analytics aggregates metrics according to Roblox definitions and some data matures later. Keep source, interval, breakdown, and observation time beside each number. When the two layers disagree, investigate timing, scope, missing coverage, or definitions rather than choosing the more favorable figure.

Write the public fact with source, time, and coverage.
List the owner KPI needed to answer the decision question.
Obtain explicit authorized access or a date-filtered owner export.
Match periods, time zones, population, and metric definitions.
Keep private values inside the authorized workspace and audience.
Publish only the conclusion and fields the owner has approved for disclosure.

Claims to reject

Reject “high CCU means high revenue,” “Visits equals users,” “public history reveals D1 retention,” and “an API key proves the seller owns the game.” None follows from the evidence. Also reject a blank field as zero: unavailable owner data, an immature retention cohort, and a failed public collection are three different states.

Illustrative example: public CCU doubles while Visits accelerate. That supports increased observed activity and entry volume. Owner data may later show that most users came from a campaign and had lower D7 retention, or it may show strong Home traffic and healthy cohorts. Both stories fit the public surface. The owner layer decides between them; until then, keep both as possibilities.

When reach and audience composition change

Check source and cohort maturity before attributing lower averages to a worse game. The Home recommendations guide explains candidate selection, audience expansion, new countries and the corresponding MARPLA workflow.

Primary sources

Put this into practice in MARPLA

MARPLA tool diagram: Start analyzing a game

Check each metric’s provenance. Connect your game with the required permissions to analyze retention and other private metrics; public CCU does not replace them.

Open the tool →Select your connected game. Sign-in and access to its data are required.

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