Do Social Media Campaigns Affect Your Search Ranking?
Significant debate exists about whether social media interactions—such as shares, likes, and comments—affect search engine optimization (SEO). The central question remains: Do social signals influence search rankings?
While numerous discussions and studies have explored this topic, no definitive conclusion has been reached. If social signals do impact SEO, how exactly does this occur?
To address this question, we conducted an extensive study to determine whether social networking activity has any measurable connection to page rankings beyond anecdotal evidence.
This research required substantial data, so be prepared to invest some time (and perhaps a cup of coffee) to understand our findings fully.
Methodology: How Was The Research Conducted?
To keep things concise, we’ll outline the key aspects of our study:
| Aspect | Details |
| Social Platforms Analyzed | Facebook, Google+, Pinterest, and LinkedIn (Twitter was excluded due to the removal of share counts). |
| Data Scope | Approximately 300,000 pieces of content, based on ~34,000 randomly selected keywords ranking in positions 1–10 on Google. |
| Timeframe | Data was collected during May and June 2016. |
| Key Consideration | Correlation does not imply causation. |
We calculated mean values for entries with at least one like, share, or comment (greater than 0 but less than 100,000). The upper limit was set to ensure the data remained representative, as extremely high social signal counts are often non-organic and could skew results.
Key Findings
1. Strong Social Presence Correlates with Better Rankings
On average, a strong social media presence (likes, shares, and comments on Facebook, plus shares on Google+, LinkedIn, and Pinterest) is negatively associated with site rank.
This means that higher-ranked sites (lower rank numbers) tend to have more social activity. The relationship is nearly linear, especially for the top 5 positions.
2. Higher Rankings Linked to Combined Social Shares
This trend holds true for most individual platforms, though the strength of the relationship varies:
| Platform | Linearity of Relationship |
| Closest to perfectly linear, with minor deviations. | |
| Google+ | Nearly linear, with clear streaks between rank brackets (e.g., 1st–4th, 5th–8th). |
| Less linear, but the overall trend of higher social activity for higher ranks still applies. | |
| No linear relationship; highest shares are not associated with the top rank. |
3. Top 4 Positions Show Significantly Higher Facebook Activity
Facebook activity (likes, shares, and comments) is strongly associated with higher rankings:
- Likes: Linearity breaks after the 2nd rank, but the top 3 positions have significantly higher numbers.
- Shares: Clear linearity for the first 7 ranks, with the top 3 positions standing out.
- Comments: Linearity holds for the first 6 ranks, with the 1st rank having significantly more comments.
While causality cannot be proven, higher Facebook activity is clearly linked to better search rankings.
4. Google+ Shares Are Highest for the 1st Rank
Google+ shares show a linear relationship, particularly within specific rank brackets (e.g., 1st–4th and 5th–8th). The 1st rank has a significantly higher mean share count compared to other positions.
5. LinkedIn Activity Shows No Clear Correlation
LinkedIn’s relationship with rankings is less consistent. While the 1st rank has the highest mean share count, the 2nd highest mean corresponds to the 10th rank, and the lowest mean is for the 8th rank. This makes it difficult to draw any definitive conclusions.
Pinterest: High Shares Do Not Correlate with High Rankings
Pinterest stands out among social networks for two main reasons:
- There is no linear relationship between Pinterest shares and search rankings, unlike Facebook and Google+.
- The highest mean share counts are not associated with the top-ranked pages. Instead, the 8th and 7th ranks have the highest share counts, while the 1st rank has the 9th highest mean share count.
| Rank | Mean Pinterest Shares |
| 1 | 9th Highest |
| 7 | 2nd Highest |
| 8 | Highest |
| 9 | Lowest |
This suggests that while Pinterest shares may be valuable for other reasons, they are not a reliable indicator of high search rankings.
Content-Length, Social Shares, and Rankings
In a previous study, we found that shorter articles tend to rank higher. Building on this, we analyzed whether there is a connection between content length, social shares, and rankings. We categorized over 300,000 posts into word count groups, focusing on two key categories:
- Micro-content (1–50 words): Typically associated with social media.
- Long-form content (1001–5000 words): Often performs well in search rankings.
1. Micro-Content (1–50 Words)
Micro-content shows a strong correlation between high social activity and top rankings, particularly on Facebook and Google+.
| Platform | Observation |
| The 1st rank has significantly more likes, shares, and comments than all other ranks combined. | |
| Google+ | High shares are strongly correlated with the 1st rank, but not with other positions. |
| The 1st rank has the highest share count, but no linearity is observed for other ranks. | |
| No clear correlation between shares and rankings, even for micro-content. |
2. Long-Form Content (1001–5000 Words)
For longer content, the relationship between social shares and rankings is less clear.
| Platform | Observation |
| No direct correlation between social activity and rankings. | |
| Google+ | Slight linearity was observed for the top 6 ranks, though not consistent. |
| No strong correlation between shares and rankings. | |
| The most consistent linear relationship between shares and rankings among all platforms. |
Methodological Clarifications
Our study focused on the top 10 organic search results for two reasons:
- Pages beyond the first page of search results have significantly lower visibility.
- Studies show that the majority of clicks go to the first page of results.
| Study | Percentage of Clicks on First Page |
| Optify | 89.69% |
| Chitika | 91.5% |
| Moz | 52.40% |
While the exact percentage varies, the consensus is clear: ranking on the first page is crucial for visibility.
Other Relevant Studies and Google’s Position
The role of social signals in SEO remains a contentious topic. Some studies, like Moz’s, suggest that Google does not directly use social share counts in its ranking algorithm. Others, such as Neil Patel, argue that there may be an indirect connection.
| Study/Expert | Position on Social Signals |
| Moz | Social signals are not a direct ranking factor. |
| Neil Patel | Social signals may indirectly influence rankings through increased visibility and engagement. |
| Matt Cutts | Google indexes social media posts like any other web page but does not use them as a ranking factor. |
| John Mueller | Social signals are not a direct part of Google’s ranking algorithm. |
Why Google Avoids Using Social Signals as a Ranking Factor
Google’s reluctance to use social signals as a ranking factor stems from its commitment to reliable and meaningful data. The company has stated that it will only incorporate a signal into its algorithm if it can confidently interpret its significance.
Social signals, such as likes, shares, and comments, are often volatile and can be manipulated, making them less trustworthy as a ranking metric.
The Value of Social Media Beyond Rankings While social signals may not directly impact search rankings, social media remains a powerful tool for other purposes:
Purpose Description Brand Building Social media helps establish and grow a brand’s online presence and reputation.
Driving Traffic Platforms like Facebook, Twitter, and LinkedIn can direct qualified traffic to a website. Engagement Social media fosters interaction with audiences, enhancing customer relationships.
Conclusion
With all the data analyzed, it’s crucial to clarify one fundamental principle: correlation does not imply causation. Throughout this study, we have never aimed to prove or disprove that a more substantial social media presence leads to higher search engine rankings.
Instead, we’ve observed a relationship between the two, though the exact nature of this relationship is complex and may vary across different social networks.
Our analysis focused on measuring the strength of correlations, not on establishing causal links. While we’ve identified a connection between social shares and search rankings, we cannot determine whether higher shares lead to better rankings or if higher-ranked sites naturally attract more shares.
