X (Twitter) Case Study: How Engagement Impacts Visibility
Engagement is at the core of success on X (Twitter), but which metrics truly drive visibility and influence? In this case study, we put engagement to the test—analyzing the effects of Likes, Retweets, Views and Impressions on post performance.
By running multiple controlled experiments, we uncover how different engagement strategies impact organic growth. Does a higher volume of engagement lead to better results? Do certain types of post perform better when boosted? And which engagement metric is the most powerful?
Through four detailed case studies, we break down the data, reveal key trends, and provide actionable insights to help you maximize your reach on X. Let’s dive in.
Case Study #1
In this scenario, we tested whether increasing the amount of engagement sent to posts leads to higher natural growth in other metrics (such as views, retweets, and likes). The goal was to see if a post that receives a higher volume of likes, retweets, and impressions would naturally attract more engagement on its own.
Definitions
- Low Engagement Post: The X (Twitter) post that received the lowest amount of engagement.
- Moderate Engagement Post: The X (Twitter) post that received moderate engagement.
- High Engagement Post: The X (Twitter) post that received high engagement.
- Exceptional Engagement Post: The X (Twitter) post that received the highest amount of engagement.
The Process
- We selected 4 posts under a similar theme (we used #coffee), recency and overall engagement.
- We noted down the initial stats of each post.
- We sent an increasing amount of engagement to the posts.
- We monitored their growth over the next 24 hours.
Results
Initial Data
We started with four posts with varying levels of initial engagement. The engagement sent ranged from 20 likes, 10 retweets, and 100 impressions for the Low Engagement Post to 150 likes, 75 retweets, and 600 impressions for the Exceptional Engagement Post.
| Post | Initial Views | Initial Retweets | Initial Likes | Likes Sent | Retweets Sent | Impressions Sent |
|---|---|---|---|---|---|---|
| Low Engagement | 12 | 0 | 1 | 20 | 10 | 100 |
| Moderate Engagement | 9 | 0 | 1 | 50 | 20 | 200 |
| High Engagement | 5 | 0 | 0 | 100 | 50 | 400 |
| Exceptional Engagement | 1 | 0 | 0 | 150 | 75 | 600 |
Final Data
After sending the planned engagement amount, we tracked the changes in the metrics over the next 24 hours. These are the results highlighting the growth in views, comments, retweets, and likes for each post:
| Post | Views Growth | Retweets Growth | Likes Growth |
|---|---|---|---|
| Low Engagement | 164 (164%) | 1 (10%) | 4 (20%) |
| Moderate Engagement | 365 (182.5%) | 6 (30%) | 11 (22%) |
| High Engagement | 1605 (401.25%) | 11 (22%) | 21 (21%) |
| Exceptional Engagement | 205 (34.17%) | 16 (21.33%) | 28 (18.67%) |
Overall Growth
When looking at the total growth, we can see a clear trend that larger amounts of engagement led to greater increases in some metrics, especially views and retweets. However, there were notable differences across posts:
| Post | Total Growth | Total Engagement Sent | Overall Growth (%) |
|---|---|---|---|
| Low Engagement | 170 | 130 | 130.77% |
| Moderate Engagement | 382 | 270 | 141.48% |
| High Engagement | 1637 | 550 | 297.64% |
| Exceptional Engagement | 248 | 825 | 30.06% |
Conclusion
Views / Impressions Growth
Posts with higher engagement saw the most significant increase in views. While the Low and Moderate Engagement Posts showed substantial growth (164% and 182.5% respectively), the more engagement sent to the High Engagement Post (1605 views, 401.25% growth) resulted in far more significant natural growth.
Retweets and Likes Growth
Retweets grew consistently as engagement increased, with the High Engagement Post showing the largest natural increase in retweets (11 retweets, 22% growth), closely followed by the Moderate Engagement Post (6 retweets, 30% growth). Likes grew steadily, with the High Engagement Post seeing a significant increase (21 likes, 21% growth).
Overall Engagement
The results indicate that more engagement does lead to greater natural growth, but the growth is not always proportional. The most significant natural growth happened with the higher engagement levels with the High Engagement Post outshining even the Exceptional Engagement Post even though not by much.
Graphs
Overall Natural Growth
Best Performing Metric
Key Takeaways
Post achieved
Engagement saw
on average lead to
Case Study #2
In this scenario, we aimed to determine whether the type of post (text-only, image, or video) affects how much natural engagement it generates when boosted with the same amount of engagement. To keep the test fair, each post received 70 likes, 30 retweets, and 250 views/impressions, regardless of its type.
Definitions
- Text Post #1: The first text only X (Twitter) post that received engagement.
- Text Post #2: The second text only X (Twitter) post that received engagement.
- Image Post #1: The first image X (Twitter) post that received engagement.
- Image Post #2: The second image X (Twitter) post that received engagement.
- Video Post #1: The first video X (Twitter) post that received engagement.
- Video Post #2: The second video X (Twitter) post that received engagement.
The Process
- We selected 6 posts under a similar theme (we used #travel), recency and overall engagement:
- 2 text-only posts
- 2 image posts
- 2 video posts
- We noted down the initial stats of each post.
- We sent the same amount of engagement to all the posts (70 likes, 30 retweets and 250 likes/impressions).
- We monitored their growth over the next 24 hours.
Results
Initial Stats
| Post Type | Initial Views | Initial Retweets | Initial Likes |
|---|---|---|---|
| Text Post #1 | 5 | 0 | 1 |
| Text Post #2 | 31 | 0 | 0 |
| Image Post #1 | 4 | 0 | 1 |
| Image Post #2 | 7 | 0 | 0 |
| Video Post #1 | 23 | 0 | 1 |
| Video Post #2 | 11 | 0 | 0 |
Final Stats
| Post Type | Final Views | Final Retweets | Final Likes |
|---|---|---|---|
| Text Post #1 | 1470 | 35 | 88 |
| Text Post #2 | 1595 | 31 | 87 |
| Image Post #1 | 340 | 34 | 89 |
| Image Post #2 | 313 | 33 | 88 |
| Video Post #1 | 369 | 34 | 89 |
| Video Post #2 | 1264 | 34 | 87 |
Overall Growth
The data shows disparities in performance across different post types. By focusing on the natural growth, text posts stand out with an impressive 505.8% average increase in views, significantly surpassing both image and video posts. Video posts followed with a 220% average views growth, while image posts showed steady, though more modest, improvements. Retweets and Likes growth remained fairly consistent across all post types.
| Post Type | Average Views Growth | Average Retweets Growth | Average Likes Growth |
|---|---|---|---|
| Text | 1264.5 (505.8%) | 3 (10%) | 16.5 (23.57%) |
| Image | 71 (28.4%) | 3.5 (11.67%) | 9 (13.57%) |
| Video | 549.5 (220%) | 4 (13.33%) | 9.5 (13.57%) |
Conclusion
Retweets and Likes Were Similar Across Types
Retweet and like growth were fairly consistent across all three types, with only minor differences. For example, videos slightly edged out images and text in retweet growth at 13.33%, but the variation was small. Text posts showed slightly stronger performance in likes growth, with an average of 23.57%, while images and videos followed closely at 13.57% and 13.33%, respectively.
Images and Videos Saw Lower View Growth
Both image and video posts saw significantly less view growth than text posts (505.8%), though videos outperformed images in this regard, averaging 220% growth in views compared to 28.4% for images. Despite this disparity, both post types still demonstrated notable improvements in natural growth.
Best Overall Natural Engagement Growth
For those looking to maximize visibility, text posts appear to benefit the most from receiving engagement. Videos also showed promise in view growth, albeit to a lesser extent than text posts. Images performed the weakest overall in terms of natural growth, though they were still comparable to text and video posts in likes and retweet growth.
Graphs
Likes Growth
Views Growth
Retweets Growth
Key Takeaways
performed
achieved
achieved
Case Study #3
In this scenario, we investigated whether the recency of a post affects the natural engagement it generates when boosted with the same amount of engagement. To ensure fairness, each post—two recent and two older—received 50 likes, 25 retweets, and 200 views/impressions.
Definitions
- Recent Post #1: The first recent X (Twitter) post (<24 hours old) that received engagement.
- Recent Post #2: The second recent X (Twitter) post (<24 hours old) that received engagement.
- Old Post #1: The first old X (Twitter) post (>24 hours old) that received engagement.
- Old Post #2: The second old X (Twitter) post (>24 hours old) that received engagement.
The Process
- We selected 4 posts under a similar theme (we used #science), recency and overall engagement:
- 2 recent posts
- 2 older posts (>24 hours)
- We noted down the initial stats of each post.
- We sent the same amount of engagement to all the posts (50 likes, 25 retweets and 200 likes/impressions).
- We monitored their growth over the next 24 hours.
Results
Initial Data
The initial data highlights minimal engagement differences across posts, with older posts showing slightly higher numbers due to having over 24 hours to accumulate interaction. However, this difference is negligible, as the recent posts were selected within an hour of being published, ensuring they hadn’t had time to generate much engagement. Overall, the starting levels were low across the board, making the conditions consistent and fair for testing.
| Post Type | Initial Views | Initial Retweets | Initial Likes |
|---|---|---|---|
| Recent Post #1 | 4 | 0 | 0 |
| Recent Post #2 | 2 | 0 | 0 |
| Old Post #1 | 69 | 2 | 3 |
| Old Post #2 | 15 | 0 | 0 |
Final Data
The final stats reveal notable increases across all posts, with the Old Post #1 achieving the highest view count at 613 and garnering the most likes at 65. Retweets were relatively consistent across posts, ranging between 28 and 30.
Both recent and older posts showed similar engagement trends, suggesting reliable performance across varying post ages.
| Post Type | Final Views | Final Retweets | Final Likes |
|---|---|---|---|
| Recent Post #1 | 285 | 26 | 60 |
| Recent Post #2 | 534 | 30 | 62 |
| Old Post #1 | 613 | 28 | 65 |
| Old Post #2 | 283 | 29 | 60 |
Overall Growth
The analysis reveals that while there were significant differences in natural engagement between individual posts, these differences were not tied to the age of the posts. Both recent and older posts displayed comparable ranges of growth, with views seeing the most notable increases. Similarly, likes growth was consistent across all posts, ranging from 20% to 24%.
These findings suggest that the age of a post does not significantly impact its potential for natural growth when boosted.
| Post Type | Views Growth | Retweets Growth | Likes Growth |
|---|---|---|---|
| Recent Post #1 | 81 (40.5%) | 1 (4%) | 10 (20%) |
| Recent Post #2 | 332 (166%) | 5 (20%) | 12 (24%) |
| Old Post #1 | 344 (172%) | 1 (4%) | 12 (24%) |
| Old Post #2 | 68 (34%) | 4 (16%) | 10 (20%) |
Conclusion
Older Posts Had Higher Natural View Growth
The older posts, particularly Old Post #1, showed higher percentage growth in views compared to the recent posts. This indicates that older content may still have potential for visibility when boosted.
Recent Posts Outperformed in Likes and Retweets
Despite older posts excelling in views, recent posts matched or slightly exceeded older posts in natural like and retweet growth. For example, Recent Post #2 saw a 24% increase in likes and 20% in retweets, on par with Old Post #1‘s growth in these metrics.
Recent Posts Perform Better Overall
Recent Post #2 and Old Post #1 were clear outliers, with significantly higher view growth compared to Recent Post #1 and Old Post #2. This suggests that factors other than post age (e.g., initial content quality) may also play a role.
Graphs
Comparative Growth
Overall Natural Growth
Key Takeaways
only performed
achieved
achieved
Case Study #4
In this scenario, we explored the impact of sending likes, retweets, impressions, and views individually to different posts. The goal was to observe how each engagement metric affects natural growth when used in isolation, helping us determine which drives the most effective organic engagement.
Definitions
- Likes Post: The X (Twitter) post that only received likes.
- Retweets Post: The X (Twitter) post that only received retweets.
- Impressions Post: The X (Twitter) post that only received impressions.
- Views Post: The X (Twitter) post that only received views.
The Process
- We selected 4 posts under a similar theme (we used #food), recency and overall engagement.
- We noted down the initial stats of each post.
- We sent only one engagement type to each post.
- We monitored their growth over the next 24 hours.
Results
Initial Data
At the beginning, the Likes Post had solid engagement but low visibility, while the Retweets Post showed moderate reach with high potential for interaction. The Impressions Post had limited exposure, and the Views Post started strong in visibility but lacked direct engagement.
This baseline provides a foundation for analyzing how each post responded to the targeted engagement throughout the testing phase.
| Post | Initial Views / Impressions | Initial Retweets | Initial Likes | Engagement Sent |
|---|---|---|---|---|
| Likes Post | 590 | 2 | 4 | 60 likes |
| Retweets Post | 548 | 2 | 54 | 25 retweets |
| Impressions Post | 69 | 0 | 11 | 200 impressions |
| Views Post | 382 | 3 | 19 | 200 views |
Final Data
The final results show clear distinctions in the impact of each engagement service. The Likes Post experienced a 10.5% increase in views and a 20% boost in likes. The Retweets Post saw a 12% rise in retweets. The Impressions Post achieved a 167.5% growth in impressions, while the Views Post saw a 257.5% increase in views, surpassing expectations. Each service contributed differently, with some results exceeding expectations and others performing as anticipated.
| Post | Final Views / Impressions | Final Retweets | Final Likes |
|---|---|---|---|
| Likes Post | 652 | 2 | 76 |
| Retweets Post | 562 | 30 | 54 |
| Impressions Post | 604 | 0 | 11 |
| Views Post | 1097 | 4 | 27 |
Individual Natural Growth
| Post | Natural Views Growth | Natural Retweets Growth | Natural Likes Growth |
|---|---|---|---|
| Likes Post | 62 | 0 | 12 (20%) |
| Retweets Post | 14 | 3 (12.0%) | 0 |
| Impressions Post | 335 (167.5%) | 0 | 0 |
| Views Post | 515 (257.5%) | 1 | 8 |
Overall Natural Growth
| Post | Initial Engagement | Final Engagement | Sent Engagement | Natural Engagement Growth | Natural Engagement Growth (%) |
|---|---|---|---|---|---|
| Likes Post | 597 | 671 | 60 | 14 | 2.35% |
| Retweets Post | 604 | 662 | 25 | 33 | 5.46% |
| Impressions Post | 80 | 615 | 200 | 335 | 418.75% |
| Views Post | 405 | 1129 | 200 | 524 | 129.38% |
Conclusion
Likes
Likes showed steady growth, primarily within their own metric, but resulted in the lowest total engagement increase at 2.35%. While they boosted the likes of the Likes Post by 20%, the overall impact on total engagement remained relatively small compared to other services.
Retweets
Retweets provided a more focused boost in their metric, leading to a 5.46% growth in overall engagement. This indicates targeted engagement, but the contribution to broader interaction was more limited compared to posts with views and impressions.
Views / Impressions
The posts that received views and impressions saw an impressive average natural engagement growth of 275%. This clearly highlights their potential to drive significant visibility and natural interaction, with views growing by 167.5% and impressions by 257.5%.
Best Overall Performance
If the goal is to maximize overall engagement, impressions and views are clear winners. However, if you want to focus on a specific metric, such as likes or retweets, their respective services perform well in driving growth within their domain.
Ultimately, these different analytics complement each other, and the best approach for maximizing post engagement is to balance all of them proportionally, ensuring a well-rounded strategy that drives results from multiple angles.
Graphs
Individual Natural Growth
Overall Natural Growth
Key Takeaways
achieved
achieved
Key Findings
Having conducted multiple case studies analyzing the impact of likes, retweets, impressions, and views on Twitter post performance, we have gathered all results into one final section. This consolidated analysis provides a clearer understanding of how different engagement types contribute to organic growth and overall visibility. By examining various engagement strategies across post types, recency, and metric distribution, we can now establish the most effective approach for maximizing reach and interaction on Twitter. The following section presents a detailed breakdown of our final results and actionable insights based on the data we collected.
Results
Initial Data for Posts 1-9
| Post | Initial Views / Impressions | Initial Retweets | Initial Likes | Likes Sent | Retweets Sent | Views / Impressions Sent |
|---|---|---|---|---|---|---|
| #1 | 12 | 0 | 1 | 20 | 10 | 100 |
| #2 | 9 | 0 | 1 | 50 | 20 | 200 |
| #3 | 5 | 0 | 0 | 100 | 50 | 400 |
| #4 | 1 | 0 | 0 | 150 | 75 | 600 |
| #5 | 5 | 0 | 1 | 70 | 30 | 250 |
| #6 | 31 | 0 | 0 | 70 | 30 | 250 |
| #7 | 4 | 0 | 1 | 70 | 30 | 250 |
| #8 | 7 | 0 | 0 | 70 | 30 | 250 |
| #9 | 23 | 0 | 1 | 70 | 30 | 250 |
Initial Data for Posts 10-18
| Post | Initial Views / Impressions | Initial Retweets | Initial Likes | Likes Sent | Retweets Sent | Views / Impressions Sent |
|---|---|---|---|---|---|---|
| #10 | 11 | 0 | 0 | 70 | 30 | 250 |
| #11 | 4 | 0 | 0 | 50 | 25 | 200 |
| #12 | 2 | 0 | 0 | 50 | 25 | 200 |
| #13 | 69 | 2 | 3 | 50 | 25 | 200 |
| #14 | 15 | 0 | 0 | 50 | 25 | 200 |
| #15 | 548 | 2 | 54 | 0 | 25 | 0 |
| #16 | 69 | 0 | 11 | 0 | 0 | 200 |
| #17 | 382 | 3 | 19 | 0 | 0 | 200 |
| #18 | 590 | 2 | 4 | 60 | 0 | 0 |
Final Data for Posts 1-9
| Post | Final Views / Impressions | Final Retweets | Final Likes |
|---|---|---|---|
| #1 | 276 | 11 | 25 |
| #2 | 574 | 26 | 62 |
| #3 | 2010 | 61 | 121 |
| #4 | 806 | 91 | 178 |
| #5 | 1470 | 35 | 88 |
| #6 | 1595 | 31 | 87 |
| #7 | 340 | 34 | 89 |
| #8 | 313 | 33 | 88 |
| #9 | 369 | 34 | 89 |
Final Data for Posts 10-18
| Post | Final Views / Impressions | Final Retweets | Final Likes |
|---|---|---|---|
| #10 | 1264 | 34 | 87 |
| #11 | 285 | 26 | 60 |
| #12 | 534 | 30 | 62 |
| #13 | 613 | 28 | 65 |
| #14 | 283 | 29 | 60 |
| #15 | 562 | 30 | 54 |
| #16 | 604 | 0 | 11 |
| #17 | 1097 | 4 | 27 |
| #18 | 652 | 2 | 76 |
Our Findings
Average Expected Natural Growth
From our analysis, we calculated the average natural growth rates associated with each type of engagement. These averages represent the additional organic engagement posts can expect to receive for every 100 units of engagement sent. This data offers a baseline for understanding how various metrics contribute to organic reach and activity.
- Likes Growth: ~22.64%
- Retweets Growth: ~13.96%
- Views / Impressions Growth: ~195.46%
These percentages highlight the relative effectiveness of different metrics in driving natural engagement growth. While sending views/impressions had the highest impact, likes and retweets also proved to be valuable tools for fostering organic engagement when used strategically.
Note: These figures are estimations based on controlled tests and may vary depending on factors like audience behavior and content relevance.
Natural Growth Graph
