@clipsrus115 vs @lancerande

Side-by-side Snapchat Spotlight performance comparison.

@clipsrus115 has 9.5K subscribers and @lancerande has 21.1K, so @lancerande has 2.2x as many. Across the 36 and 30 Spotlight posts we have collected, @clipsrus115 averages 178.0K views per post and @lancerande 2.5K; engagement is 5.59% against 0.63%.

@clipsrus115

ClipsRus ClipsRus

@clipsrus115

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@lancerande

Lance Rande

@lancerande

Scroll at your own risk: unexpected laughter ahead.

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@clipsrus115 Metric @lancerande
9.5K Subscribers 21.1K
36 Spotlight Posts 30
5.7M Total Views 29.8K
178.0K Avg Views / Post 2.5K
2.7M Best Post Views 4.3K
5.59% Engagement Rate (%) 0.63%
264 Subscribers per Post 703

What the posts and readings show

On the typical post, @clipsrus115 gets 19.0x the views of @lancerande (48,728 against 2,566 for the middle post).

@clipsrus115: Across the 31 of its 36 collected Spotlight posts that have a view count, the middle post has 48,728 views, while the average is 183,744: a few big posts lift it, and the most-viewed one holds 47% of these views. The most-viewed post (2,657,501 views) went up on August 19, 2026. The collected posts run from July 25, 2026 to October 8, 2026. Subscribers went from 6,800 on September 27, 2026 to 9,500 on October 22, 2026 (+39.7%).

@lancerande: Across the 12 of its 30 collected Spotlight posts that have a view count, the middle post has 2,566 views, close to the average of 2,487. The most-viewed post (4,329 views) went up on October 2, 2026. The collected posts run from September 30, 2026 to October 3, 2026.

Each account's full report has its growth chart, posting pattern and top posts: @clipsrus115 and @lancerande.

Methodology: the figures cover the Spotlight posts SnapDataHub has collected for each account, not every post it has made. Averages and the middle (median) post use only posts that came with a view count. Engagement rate = (likes + comments) / views × 100 over the collected posts. Subscriber counts are Snapchat's own; it rounds counts of 1 million or more to the nearest 100,000. How we calculate these numbers.