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How Can You Use Backlink Data For SEO?

The art and science of search engine optimization is a procedural drama, where you start with the Crime Scene, aka the SERP (Search Engine Results Page) and try to determine just why. Why does it rank in that particular spot?

What’s the motive? What’s the cause? You can of course start with the body itself, the web-page being ranked having numerous details and clues. But this didn’t happen in isolation. You’ve got other suspects, and everyone’s “reputation” to consider. Of course, that reputation “signal” that’s used by search engines is actually hypertext links.

What can search engine divine from such signals? How do they use the specifically linked text, or the context of that link? How does it balance the number of links and the “quality” of those links?

What can these amateur sleuths known as SEOs learn by reviewing all the pieces of information that links can provide? Backlinks are a wealth of information, so let’s break it up piece by piece and determine the potential use cases for each little bit of backlink data.

Use the number/quality of links as a proxy for “authority” needed to rank for that keyword term.

 “You have x links, competitors have Y links, you need z links to have a hope of ranking for this keyword”.

What made Google unique? It wasn’t the first search engine, but it was the first to use links as a signal of “authority” for pages/sites.

“These are the links your competitor has, these ones are ones we want to poach/emulate”

You can ROUGHLY use the number of referring domains sending links to the sites currently ranking on the homepage as a BROAD SKETCH of how much “authority” your content will need to rank.

Why all the qualifiers? Because it’s never simple, there’s going to be some content that has other signals that’s sent it to the front page. But, it’s an “okay” place to start.

Use A Review Of Your Links To Identify How Hard You Need To Work & Identify Strange Or Dangerous Patterns In Your Links

“These are your links, these ones suck, these are good.”

 There’s a couple of useful ways to look at your links. You can look at your the anchor text, the blue clickable text like this, because Google and other search engines certainly do. Previous iterations of Google algorithm had to be updated because spammers found they could shift rankings by hitting large numbers of anchor text in their links.

Pay attention to what content pieces you’ve written that’ve gotten real links and how others have linked to them, they may not be what you expect!

“You’ve got 500 new backlinks this week to http://domain.com/viag-cialis-hacked-page … mayybe we need to see if that page exists, and see if you’ve been hacked.

I’ve unfortunately seen clients with WordPress instances celebrate because they just got a bunch more beautiful links out of the blue. However, that boost in links was because his site had been hacked, dozens of pages were created and received links from OTHER hacked sites. Not every link is golden.

Use Backlinks To Current Ranking Articles As Hit List For Outreach

“This article ranks for the same keyword phrase we’re targetting with our new article. Here’s that page’s backlinks, let’s reach out to those sites and see if they’ll link to us too/instead.”

Links are a cornucopia of competitor insights! Who links to your competitors, why they links and how they got those links are all clues to the most effective method for building links.

Use a competitor research tool that can give you a list of all of the links that domain has right now, and you can dissect that corpse and use it as a grocery list.

How To Use Links For Business Intelligence Purposes

Let’s see if we can figure out what’s going on in your competitors’ business.  What are their partnerships?  Are they hiring?  Who are their vendors or customers?  What causes do they support?  Link mining as business intel.

Nicole DeLeon

You can identify if perhaps competitors are mostly using outreach to ask to post guest articles or generating infographics. There’s fantastic competitor information to be gathered by reviewing the link profile of your organic and direct competitors.

These are the most commonly utilized link building strategies in your space.  We can do those too OR we can pursue other / harder / better links by building better content and not being lazy.

Nicole DeLeon of Northstar Inbound

Don’t just look at the links though, look at the anchor text and the pages being linked. Find common values that these bloggers found worthy of mentioning in a link.

All these sites link to the same type of pages, let’s see if we can find words or phrases they have in common so we can build a footprint to find more prospective link targets.

Nicole DeLeon

When these sites publish content, similar content appears on all these other sites and also links back.  Let’s see if we can identify other syndication networks.

Nicole DeLeon

How Else Can You Use Link Data?

Have a way to use this data that I didn’t cover? We’re happy to include your insight and link to your site or business for attribution.

Get A Rough Estimate Of Potential SEO Traffic

In Short: Forecast SEO REVENUE Potential & Not Just Traffic Volume

Don’t just blindly choose keywords based on the generic volume numbers you extract from any old SEO Tool, spend some time to estimate your potential conversions into leads, how many leads turn into sales, how much revenue gained per sale and if it’s a recurring revenue project then how long do people usually stick around.

Step By Step Process To Calculate SEO ROI

  • Do this process for each unique product(product type if they’re all super similar) or service
  • Calculate at what rate is of your traffic that turns into leads by filling out a form (Conversion rate)
  • Calculate how many leads turn into sales (Lead to Sale Rate)
  • Define how much revenue you make per sale. (Revenue per sale)
  • Optional: If this is a recurring service, multiply the revenue by the average lifespan of the client (how many times you will get to charge them)
  • Gather the list of relevant keywords that are most likely actually purchase the product or service
  • Get the total volume of those keywords
  • Multiply that volume by a PLAUSIBLE organic click through rate, this study by Advanced Web Rankings is pretty good.
  • Take your potential traffic number and multiply it by the conversion rate, lead to sale rate and revenue per sale. This will provide you with a realistic potential SEO Return on Investment and a solid number you can show your boss or client.

Organic Traffic Estimator: An SEO Forecasting Process

Process for attempting to evaluate traffic potential , I have taken the following, general approach:

  • I identify current device% breakout between mobile and desktop via analytics data
  • I use Rand/Jumpshots study of click death by device type (this may be controversial to some people, but I’ve noticed it models our actual data pretty decently)
  • desktop/mobile search volume from your tool of choice (e.g. SEMrush, Ahrefs, etc.)
  • averaged CTR for top five positions (generally what we’re shooting for re: rankings), pulled from top X keywords in GSC

So, for example:
I want to project what my outcomes may be if I rank in top 5 for any given set of terms, thereby projecting what my opportunity is if I try to invest. This can be used in conjunction with other metrics, such as average difficulty for a corpus of keywords, etc. to make decisions on re: do you invest your time in them or not.
Here are the things I work through –
Calculating target ranking position (target ranking position = top 5) average – I recommend doing this for desktop and mobile to use the relative CTR for each later on:

  • I pulled the top keywords from GSC into sheets for the last 6 months (capped out the pull at around 50k terms gathered)
  • I rounded the position data to nearest whole position and applied groupings to them (position 1, top 3, first page, etc.) for future analysis
  • I used averageif on CTR for all top 10 positions (averageif pos = 1, averageif pos =2, etc.)
  • Then, I average the top 5 position averages, giving me a relative average for if I ranked in the top 5 positions
  • this % gets used in final equation

Find device breakout for current audience:

  • from your analytics of record (Omniture, GA, etc.), find out the device breakout by mobile vs desktop
  • these % get used in final equation

Leverage click data from Rand/Jumpshot study:

  • While a recent study – and one which people may scoff at, or ignore – I find being mindful of loss-of-click to be an important element; if you trust the click potential data from Ahrefs or SEMrush, you could use that info on the keyword level instead of using this broad study
  • let’s say we don’t use Ahrefs or SEMrush click estimates though, I would use the 39% clicks on mobile (61% no clicks was the number referenced in the study), and 65% clicks on desktop (34.5% no clicks was number referenced in study) in my final equation

Get desktop AND mobile data for keywords, as available:

  • for each term I’m going to include in my corpus for this analysis, I will try to get both the desktop data as well as the mobile data; if mobile data is not available (or vice versa), then I will use whatever is available
  • the keyword data could be for existing rankings (current marketshare/footprint), and/or for new terms we want to go after (gap footprint) – these can be used to support different questions (e.g. should we invest in optimizing current content and what would outcomes potentially be if so)
  • data needed = search volume and current ranking position (if pulling for current footprint)

Based on all this data, we can now calculate traffic potential.

Traffic potential = ((mobile sv*0.39) * mobile traffic %) * avg T5 mobile CTR + ((desktop sv * 0.65) * desktop traffic %) * avg T5 desktop CTR

This equation is applied to every keyword we currently rank for, not in the top 5 (e.g. position 6-100).

This should give us insights into answering the question of “if we improve our ranking position for this corpus of keywords, what might the traffic estimate look like”.
You can then use this in comparison/conjunction with other metrics, like average difficulty for a topical category (e.g. risk reward based on comp to traffic opp), etc.

Actionable Recommendation: Group Your Keywords By Conversion Potential

 My recommendation for this is to not look at/forecast on a per-term basis, but instead to do it in groups or as a whole (e.g. all terms that make up a certain topical niche, or all terms that reflect the current footprint for a site).

By grouping things together, you get a better understanding of topical opportunity and risk/rewards (when looking at KW difficulty, revenue opps, etc).