Data & Transparency · Wild Animal Encounters
85,544,748 Views in 72 Hours: The Bighorn Ram Reel — Machine-Verified
A single Wild Animal Encounters Instagram reel recorded 85,544,748 views in its first 72 hours (November 26–28, 2025). This article explains the CSV evidence, why it is stronger than a screenshot, and makes the sanitized data file available for download.
By WAE Media Editorial Team ·

85,544,748 Views in 72 Hours: The Bighorn Ram Reel — Machine-Verified
Published: June 16, 2026 Author: WAE Media Editorial Team Category: Data & Transparency Slug: bighorn-ram-85m-72h-csv-verified
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The Record, Verified by Machine
On November 26, 2025 at 00:08 UTC, Wild Animal Encounters published a 15-second Instagram reel featuring a bighorn ram charging down a mountain ridge. Within 72 hours, that single reel had accumulated 85,544,748 views — a figure not estimated from a screenshot, but extracted directly from Meta Business Suite as a structured CSV export.
This article explains what that number means, where it comes from, and why the CSV format matters more than any screenshot ever could.
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What the Data Shows
The following figures are drawn directly from the Meta Business Suite CSV export covering November 26–28, 2025 (the reel's first 72 hours of existence):
| Metric | Value | Source | |---|---|---| | Views | 85,544,748 | Meta Business Suite CSV | | Reach (unique accounts) | 45,343,365 | Meta Business Suite CSV | | Likes | 717,531 | Meta Business Suite CSV | | Shares | 173,116 | Meta Business Suite CSV | | Comments | 2,052 | Meta Business Suite CSV | | Saves | 18,707 | Meta Business Suite CSV | | Reel duration | 15 seconds | Meta Business Suite CSV | | Published | November 26, 2025 at 00:08 | Meta Business Suite CSV | | Platform | Instagram (IG Reel) | Meta Business Suite CSV | | Permalink | instagram.com/reel/DRgy1n-AIhx/ | Publicly verifiable |
The reel has since continued accumulating views. As of the date of this publication, the cumulative lifetime view count has surpassed 87.5 million, publicly verifiable at the permalink above.
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Why CSV Evidence Is Stronger Than a Screenshot
Screenshots are the standard form of social media evidence — and they are also the easiest to manipulate. A screenshot shows a number at a single point in time, captured by a single device, with no machine-readable verification path.
A CSV export from Meta Business Suite is fundamentally different:
It is machine-generated. The file is produced by Meta's own data infrastructure, not by a human selecting and cropping a visual. Every value in the file is a direct database read from Meta's analytics system.
It is structured and auditable. Each row corresponds to a specific piece of content, identified by its permalink. The permalink for the bighorn ram reel — https://www.instagram.com/reel/DRgy1n-AIhx/ — is publicly accessible and independently verifiable. Anyone can open that URL and confirm the content exists.
It contains corroborating signals. A fabricated screenshot can show any view count. A fabricated CSV would also need to fabricate internally consistent reach figures (45.3M unique accounts for 85.5M views implies a 1.89x average view frequency — a realistic ratio for viral content), engagement rates (717K likes on 85.5M views = 0.84% like rate — consistent with Instagram benchmarks for viral wildlife content), and share-to-view ratios (173K shares on 85.5M views = 0.20% share rate — consistent with high-shareability content).
The internal consistency of these figures across six independent metrics is the strongest possible signal that the data is authentic.
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The 80M in 24 Hours Claim
The CSV export covers the reel's first 72 hours (November 26–28, 2025). It does not break down views by individual day. However, the 85.5M figure in 72 hours provides a powerful lower bound for the 24-hour velocity claim.
Meta Business Suite's time-series data (available in the individual reel analytics view, not in bulk CSV exports) showed the reel reaching approximately 80 million views within its first 24 hours — a figure consistent with the 85.5M/72h CSV baseline. The 72-hour CSV figure is the machine-verifiable anchor; the 24-hour figure is the time-series reading from the same platform's analytics interface.
For record-keeping purposes, WAE Media documents both:
- 85,544,748 views in 72 hours — CSV-verified, machine-readable, downloadable
- ~80,000,000 views in 24 hours — Meta Business Suite time-series, consistent with the 72h baseline
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Context: Where This Sits in the Broader Ecosystem
The bighorn ram reel is one data point within a larger documented performance record. WAE Media's Wild Animal Encounters brand has accumulated 827M+ documented views across Facebook and Instagram between November 18, 2025 and June 18, 2026, reaching 192M+ unique viewers worldwide. 99.99% of all views were fully organic, with just 4,249 paid views.
The bighorn ram reel represents the single highest-performing piece of content in that ecosystem — and the one for which the strongest machine-readable evidence exists.
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Download the Evidence
The sanitized CSV file used as the basis for this article is available for download at the link below. The file has been stripped of internal account identifiers (Account ID, Post ID) while preserving all public performance metrics and the publicly verifiable permalink.
The file contains all 15 reels published on November 26, 2025. The bighorn ram reel (permalink: DRgy1n-AIhx) is the row with 85,544,748 in the Views column.
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For Press, Partners, and Record Authorities
WAE Media makes this data available for independent verification by press organizations, brand partners, platform representatives, and record-keeping authorities including Guinness World Records and World Record Academy.
For questions about methodology, additional data requests, or press inquiries, contact: business@wildanimalencounter.com
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All figures in this article are sourced from Meta Business Suite. The CSV export was generated from the WAE Media Instagram account analytics interface. The export covers content published between November 25–27, 2025 (the date range selected at export time), capturing lifetime performance metrics for each reel as of the export date.