Finding the right sites to get a link from is always a challenge, especially now. Link tools like Majestic, ahrefs, Moz and others can't account for disavow, so by definition their metrics are unreliable. But there are other ways of getting reliable link prospecting data. If you believe if a site ranks on Google and a link from that site has value, then the only rock solid metric is how well a site ranks. To date, its been really hard to bulk analyze 1,000's of domains to see their ranking profile...until now. Let Nick Garner explain how to use a powerful new free data mining tool which accesses SEMrush's API to bulk analyse 1000's of domains for link prospecting. In this webinar (originally aired on Thursday, February 26th, 2015) you will learn how to: - Simplify identification of potential link partners with massive link databases such as MajesticSEO and AHREFs - Rapidly use multiple factors* to evaluate a domain's organic success - Easily apply SEMrush API to qualify the best link sources at massive scale - Walk away with a huge list of highly-qualified link sources with which to dominate any industry, product or service Now you can unlock the massive power of 106M keyphrases and 45M domains and 2.8T links using 90 DataGrabber - a FREE new Excel®-based tool from 90 Digital. *inbound links, referring domains, keyword, monthly search volume, rank and traffic

5. Validating link sources

6. SEMrush & links
Simple idea:
Google ranks a website = links have value.
Google doesn't rank a site = no value to those links.
SEMrush = qualifier for rankings.
Link analysis tools don’t track rankings (typically), therefore their
metrics can be misleading.

7. Why?
Penguin Disavow

8. Correlations between Majestic & SEMrush are there, but loose

9. Example
There is a huge
disparity between
the number of
keywords a site
ranks for and its
majestic trust flow.

10. randomwebsite.com
http://www.randomwebsite.com/

11. Majestic/randomwebsite.com (link)

12. SEMrush/randomwebsite.com (Link)

13. ‘Best backlink’ analysis: DataGrabber

14. Referring domains over keywords

15. Outcome: identify sites worth approaching (Link)
Source file

16. Import into Buzzstream: custom mapping (link)
https://app.buzzstream.com/manage_configuration

17. Buzzstream (link)

18. Insight & Analysis

19. Casino. Ref Domain < TF15 / Maj TF / Organic cost of traffic.
Key: Blue is Referring Domains with a TF above 15 / Grey is trustflow / Black line is No. of keywords ranked.
Source Data (excel 14mb)

20. Majestic Million / iGaming Correlation tables.
SEMrush. No. of
keywords
SEMrush. Value/Cost
of keywords
SEMrush. Traffic
from keywords

21. Core insights
My main take: When Google trusts a domain, they will rank it
across anything the site is optimised for, almost irrespective
of topic. Links seem to be a driver, but not as much as I had
previously thought.
● Casino seems to be a links game with 71.1% Maj TF and
70.9% Maj CF correlation on number of keywords
ranked
● The more money in a sector, the better the link
correlations.
● For the rest of the internet, correlations with ‘links’ is
far lower for value and traffic volumes, but not for
number of keywords.
But...what about sites which aren't getting
expected volumes/ quality of links and rank
really well?

22. Do social shares get rankings?

23. Correlation tables on social shares. (Excel Link)
Based on this data, it seems links get
you rankings and a social shares are
indicative of the link-ability of a
page.
So if you're writing content, you
could say that a great KPI for linkable
content is getting more shares. Once
you have those shares, you can get
out and acquire links for those
pages.
Post here

24. Who is my competition?

25. Competition Analysis (Excel Link)
Being able to analyse competition for a particular keyword landscape quickly

26. Who is spending?

27. Mortgages (Excel Link)
90 DataGrabber also queries SEMrush pay per click
data. It behaves much like organic research data
acquisition.
For this table :
1. picked some key phrases
2. identified top ranking domains
3. looked at the top paid key phrases per
domain
4. filtered out everything except keyword
mortgages
5. sorted by cost per click

28. Wrapping up
Data science: key is to understand what questions to ask and have the data you need,
organised in the right way, to give you actionable answers.