@l-ondn vs @abusalehoffer

Side-by-side Snapchat Spotlight performance comparison.

@l-ondn has 119.9K subscribers and @abusalehoffer has 59.4K, so @l-ondn has 2.0x as many. Across the 27 and 30 Spotlight posts we have collected, @l-ondn averages 122.7K views per post and @abusalehoffer 0; engagement is 3.81% against 0.00%.

@l-ondn

تعلم الإنجليزية 🇬🇧 ٰ

@l-ondn

ٰ 📚 اللغة الإنجليزية من قلب لندن 🇬🇧 🎬 دروس يومية بأسلوب حياة واقعي 📂 أرشيف بالملف التعريفي - القصص 🚀 تابعني لتمارس اللغة كما يتحدثها أهلها

View full profile →
@abusalehoffer

ابوصالح مُحطم الاسعار

@abusalehoffer

لا تفوتكم اقوى التخفيضات والعروض (اسواق - معارض - أسعار جملة) الدمام، الخبر، الجبيل تابعني ولن تندم 🇸🇦 تنسيق الإعلانات واتساب:

View full profile →
@l-ondn Metric @abusalehoffer
119.9K Subscribers 59.4K
27 Spotlight Posts 30
2.0M Total Views 0
122.7K Avg Views / Post 0
913.8K Best Post Views 0
3.81% Engagement Rate (%) 0.00%
4.4K Subscribers per Post 2.0K

What the posts and readings show

@l-ondn: Across the 16 of its 27 collected Spotlight posts that have a view count, the middle post has 4,828 views, while the average is 122,691: a few big posts lift it, and the most-viewed one holds 47% of these views. The most-viewed post (913,784 views) went up on December 13, 2024. The collected posts run from December 13, 2024 to August 4, 2026. Subscribers went from 118,500 on May 14, 2026 to 119,900 on October 25, 2026 (+1.2%).

@abusalehoffer: None of the 30 Spotlight posts we have collected came with a view count. The collected posts run from February 15, 2026 to February 21, 2026.

Each account's full report has its growth chart, posting pattern and top posts: @l-ondn and @abusalehoffer.

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.