Analyzing Backlinks for 500,000 Websites

We’ve read the studies regarding the correlation between website traffic and the number of backlinks, but are we right to take their assumptions for granted?
I wanted to analyze this correlation a little closer so that you could see once and for all whether this correlation was valid.

Methodology

To conduct this study I collected data on backlinks for the top 100,000 websites and split this into 5 different groups.

• Overall traffic
• Organic search traffic
• PPC traffic
• Referrals traffic
• Social Media traffic

After I had determined the 100,000 top websites using traffic data for January 2016, I needed to dig a little deeper to glean the underlying correlations for backlinks in each group. In order to realize this, I approached Majestic who were able to deliver some amazing data I could integrate into the results.
I was then able to push forward and take a closer, more accurate look at the correlations between the top sites ranking and their associated backlinks (these included referring domains, IP addresses, and more).
In order to demonstrate this, I analyzed the workings of backlinks for 500,000 websites which were divided into 5 different groups:

1. Top 100,000 websites in the world by global rank
2. Top 100,000 websites in the world by organic traffic
3. Top 100,000 websites in the world by PPC traffic
4. Top 100,000 websites in the world by referral traffic
5. Top 100,000 websites in the world by social media traffic

Let’s take a look at my findings and discuss the true impact of backlinks on website traffic.

Top 100,000 websites in global rank

Correlation

1. Referring domains with 0.8
2. IP addressed – 0.69
3. Referring domain Edu – 0.65
4. External backlinks gov – 0.59
5. Referring domains gov – 0.56

Top 100,000 websites in the world by organic traffic

Correlation

1. Referring domains – 0.67
2. IP addresses – 0.66
3. Referring domains Edu – 0.60
4. Referring domains gov – 0.51
5. External backlinks gov – 0.48

Top 100,000 websites in the world by PPC traffic

Correlation

1. Referring domains – 0.32
2. IP addresses – 0.31
3. Referring domains EDU – 0.29
4. Class C Subnets – 0.29
5. External backlinks gov – 0.26

Top 100,000 websites in the world by referral traffic

Correlation

1. Referring domains – 0.62
2. IP addresses – 0.54
3. Referring domains EDU – 0.52
4. External backlinks gov – 0.49
5. Referring domains gov – 0.41

Top 100,000 websites in the world by social media traffic

Correlation

1. Referring domains – 0.58
2. IP addresses – 0.57
3. Referring domains EDU – 0.51
4. External backlinks gov – 0.47
5. Referring domains gov – 0.40

Conclusion

As is evident from the results, the highest correlation between all the traffic groups came through referring domains. Referrals held the strongest correlation across all groups, though it was most striking in the ‘global traffic’ group where there was a high correlation of 0.8.
Additionally, I was also surprised to discover the impact of IP addresses in the results. They accounted for a significant amount of traffic and you can see this reflected in their number 2 position across all groups.
EDU and GOV websites also proved to be dark horses when providing website traffic due to their positive correlation in all groups. For PPC, there’s clear evidence of a high correlation between Class C Subnets and the results.
The overall impression I’m left with is that backlinks still have a very high correlation to the amount of website traffic. However, it would be detrimental to your SEO efforts to assume this is the only avenue for link-building. Instead, you need to adopt a more holistic approach that takes in the valuable assets of IP addresses and EDU/GOV websites to gain an overall larger share of traffic.
To learn more about Similarweb, and to try out a free demo, contact us here.

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