As much as I enjoy link prospecting, in my heart of hearts, I know it’s not where my time is best spent.
I work in an agency and my time is better served on the outreach and acquisition phase of link building than it is drumming up lists of prospects.
I know the less time I have to spend link prospecting, the more time I can spend on the work that creates value. The 20% that gives 80% of the results.
One thing I love about Citation Labs link prospector is that it drastically reduces the time I need to spend link gathering link prospects.
Crudely broken down, here is how I used to break up my time spent link building for individual campaigns.
This is how it looked when I was doing a lot of manual link prospecting:
Compared to now, with a large part of the link prospecting automated…
Less time prospecting means more time spent making contact and following up, which increases the chance of building more links.
Tools like Citation Labs link prospector, BuzzStream and Ontolo are only ever as good as the people using them.
It is important to strive to find ways of making them work for you. A good tool lets you work smarter, as well as quicker.
It is good to be creative in their application and challenge them to complete tasks that would be impossible, or highly time consuming, to complete manually.
With this then, I’ve been experimenting and testing new ways of using Citation Labs using custom, advanced search operators.
Here’s what happened:
I blogged recently about my love for ‘related:’ search operator.
Usually, I just manually run these queries one site at a time, scrape the results and then qualify them.
It is particularly useful at the beginning at campaigns when you’re researching competitors. I like to make sure I’m aware of every conceivable competitor to the site I’m working on.
Usually, the more obscure, the better, as they’ll have backlink profiles that haven’t been mined by other SEOs.
I was curious to see what would happen then if I run these queries in bulk.
First then, I set up a custom report…
For the sake of this experiment, the niche I was researching was boxing and the keyword I chose was boxing gloves.
I’ll start by taking 10 competitors and putting them next to the related search query for my search:
My hunch was that the related sites here wouldn’t tell me much I didn’t already know, as I was seeing similar results in all the different variations of ‘boxing gloves’ I searched for.
I took a sample of urls from different search queries here, as opposed to just the 10 that appear for the term boxing gloves, to try make sure I got a bit of diversity, whilst still being relevant.
I also think it is important to find out who your client identifies as their competitors, as they may not actively be optimising their site for the search engines.
If they do come up with someone I’ve not already found, I’ll always throw that site in.
My trepidation here was definitely a bit misplaced, the search yielded 225 domains. As you would expect, there was a bit of junk in here (MySpace, Facebook etc.), on the whole though, the sites it brought back were relevant and useful.
Although they weren’t the crème de la crème of the competition but this was a good thing. They were decaying websites but, the point is, they have relevant backlinks I otherwise wouldn’t have found.
If I was being thorough here, I’d run another custom related report on the new sites the previous report had identified.
I’d then compare the two lists using Ontolo’s Filter Prospects tool to see if there were any more new related domains.
I would then have a comprehensive list of sites competing with my own. I’d download every backlink these sites have and then review to see which might be worth trying to accrue.
If you want to pull out all the stops in competitor link analysis, then running a custom related search in link prospector should definitely be part of your process.
Next up I experimented by using tildes. Tildes (~) is the synonym operator.
(If you want to read more, Garrett French’s Guide to the Tilde is a good place to start.)
Again, I used boxing in my experiment, just because I like boxing.
First of all I defined the opportunity I was looking for. In this case, it was guest posting.
To keep this experiment simple, I’m just used the head term ‘fitness’.
One thing Garrett underlines in his post on tildes is that the impact on using them is diversity.
If you construct your queries to include all variations (which I would advise at least testing) and aggregate your SERP results, you clearly get a far greater diversity of domains. This obviously doesn’t mean that the results are more qualified, just that there’s more diversity with less thinking on your part about what prospecting phrases to use.
What I want then, is for link prospector to run the tilde operation quickly and bring me a diverse set of domains, with
My three operators were:
I popped these into Ontolo’s Query Generator, which shows 132 footprint queries that could yield good results.
Normally my next step would be to go through these individually and use the scraper tool. Needless to say, this is tedious time consuming. With the link prospector tool, I just download these queries as a csv and copy and pasted them into a custom report.
When it came back I’ve got the results from the 132 tilde queries above in about, 4 minutes, meaning I could move quickly onto the qualification stage and more importantly, the outreach
My process from here on in is this:
- Export the paths to csv (I like to see the path, rather than the domain, so I can work out why it has been identified)
- Next I want to trim the fat. I order the results by PageRank and cut out anything above 5. These are normally too high profile or sites like Facebook and Twitter
- Then it is just a case of going through the normal qualification process using Ontolo’s prospect reviewer
Ultimately, the Link Prospector is a time saving device that runs multiple search queries for you . It allows you to weight your time onto the business-end of getting links.
The point of these experiments was not so much to show the quality of results, but the ease of which run complex search query combinations. It feels like a mathematician being given a calculator to use when you’ve been previously laboured with an abacus.
I’ve only really tipped the ice berg here. Would like to see other people experimenting with custom reports, see their process and see what kind of results they get.