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DIGITAL BRAND MEDIA & MARKETING GROUP, INC.: revenue

Revenue for DIGITAL BRAND MEDIA & MARKETING GROUP, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All DIGITAL BRAND MEDIA & MARKETING GROUP, INC. financial histories

What this measure means

Revenue under this specific accounting concept. A missing value is not zero; filers can use other revenue concepts.

Exact concept: us-gaap:Revenues. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2016-09-01 to 2025-08-31. The SEC response was captured on 2026-09-20.

Context from the filing

In the annual report for the year ended August 31, 2025, the statement of operations and the United States/Great Britain revenue breakdown report the same total. The geographic breakdown is a presentation of that revenue, not another revenue stream. Read the source filing.

Selected filing history

Revenue in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2024-09-012025-08-31137,998USD2025-11-2810-K · 0001185185-25-001887
2023-09-012024-08-31237,868USD2025-11-2810-K · 0001185185-25-001887
2022-09-012023-08-31309,644USD2024-11-2910-K · 0001185185-24-001176
2021-09-012022-08-31225,842USD2023-11-2910-K · 0001185185-23-001264
2020-09-012021-08-31171,712USD2022-11-2910-K · 0001185185-22-001360
2019-09-012020-08-31268,957USD2021-11-0510-K · 0001185185-21-001609
2018-09-012019-08-31415,662USD2020-12-1510-K · 0001185185-20-001749
2017-09-012018-08-31536,501USD2019-11-2710-K · 0001185185-19-001663
2016-09-012017-08-31486,369USD2018-12-1410-K · 0001185185-18-002178

Related financial histories

Inspect the source

Entity
DIGITAL BRAND MEDIA & MARKETING GROUP, INC. / CIK 0001127475
Captured
2026-09-20T07:40:37.958Z
SEC response SHA-256
1d83049f899cbff9a062f8d19500599a1f079e18e925526b11f1306ca7a36021

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001127475.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))