Kick Case Study: How Live Views Impact Visibility On Streams
In the competitive world of live streaming, visibility is essential for attracting and engaging viewers. Our team conducted this case study to understand how the number of live views affects stream rankings on Kick, examining both the nuances of Kick’s recommendation algorithms and the significance of viewership levels in different ranking categories. By understanding these dynamics, streamers can make informed decisions about optimizing their reach and increasing engagement.
Case Study
To uncover the true influence of live views on stream rankings, we tested streams at three engagement levels to see how each performed in Kick’s sorting categories. This study provides insights into how viewership volume correlates with ranking positions, offering a detailed look at what it takes to stand out in each sorting option on Kick’s platform.
Objectives
- Figure out how the number of Live Viewers affect stream ranking.
- Determine the optimal amount of Live Views for maximum impact.
Definitions
- Low Engagement Kick Stream (60%): The Kick stream that received 60% of the live views compared to the top stream for the chosen category.
- Moderate Engagement Kick Stream (100%): The Kick stream that received 100% of the live views compared to the top stream for the chosen category.
- High Engagement Kick Stream (140%): The Kick stream that received 140% of the live views compared to the top stream for the chosen category.
The Process
- We picked a streaming category to monitor.
- We selected 3 streams of similar content and viewer count.
- We noted the view count of the top stream in our chosen category.
- Top stream live view count: 712 Live Views
- We sent an increasing number of Kick Live Views to each stream at 60%, 100% and 140% of the top stream’s view count.
- We started monitoring their performance immediately after receiving the Live Views.
Results
Initial Statisctics
At the beginning of the test, each stream held a similar view count: 4 views for the Low Engagement Kick Stream (60%), 5 views for the Moderate Engagement Kick Stream (100%), and 7 views for the High Engagement Kick Stream (140%). Despite these comparable starting numbers, a noticeable discrepancy emerged when sorting them by “Recommended” for the Moderate Engagement Kick Stream (100%), which initially ranked significantly lower at #148 compared to the Low Engagement Kick Stream (60%) at #25 and the High Engagement Kick Stream (140%) at #26. This suggests that factors beyond initial view count—potentially including Kick’s recommendation algorithm criteria—may contribute to how streams rank when sorted by “Recommended”.
Low Engagement Kick
Stream (60%)
The stream receiving 60% of the top category’s views showed significant upward movement, with placements rising from #52 to #4 on the Category screen under “High to Low” sorting—a jump of approximately 92%. In “Recommended” sorting, the stream improved from #25 to #8, marking a 68% improvement. However, in the broader “Browse” screen, this stream only achieved a rank of #98, indicating that 60% of views, while helpful in the category listing, may not yield competitive results in the platform-wide “Browse” view.
Moderate Engagement Kick Stream (100%)
With 100% of the top view count, this stream rose from #53 to #3 on the Category screen under “High to Low” sorting, a notable 94% increase. In “Recommended” sorting, the improvement was less pronounced, moving from #148 to #121 (18% increase), likely influenced by its initial, lower position assigned by the algorithm. This discrepancy suggests that the algorithm’s initial ranking may impact streams differently, even when view counts are similar.
High Engagement Kick Stream (140%)
Receiving 140% of the top stream’s views, it ranked highest across all metrics. In “High to Low” sorting, it jumped from #54 to #1 in its category, achieving a 100% improvement and claiming the top spot. For “Recommended” sorting, it rose from #26 to #6, a 77% increase and the highest position among the other streams in this category. On the Browse screen, it ranked at #36—a significant improvement, albeit less impactful than in category-specific placements.
Conclusion
High to Low Sorting
Each stream benefitted from Live Views, with rank improvements correlating directly with the view percentage. The High Engagement Kick Stream (140%) achieved the top rank, but the Moderate Engagement Kick Stream (100%) was only one position behind, suggesting diminishing returns beyond 70% views for category-specific ranking.
Recommended Sorting
The High Engagement Kick Stream (140%) led with a ranking improvement to #6, followed by the Low Engagement Kick Stream (60%) at #8, while the Moderate Engagement Kick Stream (100%) saw minimal improvement to #121. This gap, which appears independent of starting view count, hints that Kick’s recommendation algorithm might weigh additional factors beyond views alone when initially ranking streams.
Default Sorting
The High Engagement Kick Stream (140%) achieved the highest ranking at #36, followed by the Moderate Engagement Kick Stream (100%) at #54 and the Low Engagement Kick Stream (60%) trailing at #98. This result highlights that higher view percentages are essential for achieving visibility on the broader Browse screen, where only high engagement appears to translate to substantial rank increases.
Direct Comparison of Results
This comparison highlights the relative impact of each engagement level, revealing that while high engagement consistently delivered the best results, the Moderate Engagement Kick Stream (100%) performed comparably within category-specific sorting, potentially offering a more efficient boost for those focused on a single category.
Graph
