Hey, it's Sam Oh and welcome to the second lesson in the link prospecting module.
In this lesson, we're going to talk about how to grow your list of prospects with
"lookalike prospects."
And the name "lookalike prospects" is inspired by lookalike audiences which
is commonly used in online advertising.
Now, if you're unfamiliar with lookalike audiences, ad platforms like Google and Facebook let you target
people who are similar to an existing audience.
For example, people that are like your customers or website visitors.
And by targeting these lookalike audiences, you're able to reach new people who are likely
to be interested in your business because they share similar characteristics to your
existing customers or website visitors.
Now, lookalike prospects in link building are very much the same.
You're trying to find people who are similar to a seed prospect – which is something we
covered in the previous lesson.
But as a refresher, seed prospects are people who link to a page for a specific reason.
And these specific reasons are what I call "linkable points," which are usually identified
by patterns in a competing page's link profile.
Best of all, these linkable points help us define our pitch angles.
Now, if this went over your head, then I highly recommend watching lesson 2.1.
on finding seed prospects so you can get the most value from this lesson.
Alright so there are 3 tools I use to find lookalike prospects.
The first is Ahrefs.
More specifically, Ahrefs Site Explorer, Content Explorer, SEO toolbar, and batch analysis.
The second tool is Google and the third is the Scraper Chrome Extension.
With that said, let's go through some examples of finding lookalike prospects based on a seed.
And we'll continue with the examples we discussed in the previous lesson.
Alright, the first example is for our SEO statistics page.
When we were creating this page, we analyzed a competing page's anchors report in Ahrefs
Site Explorer.
And we noticed a pattern that the majority of links to this page were because of a specific stat.
Now, when we went to visit these competing pages, we noticed that a lot of the stats that
were in the anchors report weren't even on the page or they were just super outdated.
So we had a couple pitch angles to run with.
Now, usually when you find these patterns or linkable points in a competitor's backlink
profile, you'll likely want to get an understanding of the breadth of the opportunity.
And this will help you gauge whether it'll be worth your time and effort to pursue it.
The easiest way to do that is to look for a footprint within the pattern.
And a footprint is just a common mark among a dataset.
So in this case, the footprint would be the percent sign.
Now, with footprint in hand, we can go to the backlinks report and use
the filters to narrow in on relevant opportunities.
And because our footprint is a percent sign in the anchor or surrounding text of the backlink,
I'll type that into the search box and choose anchors with surrounding text
as the search mode.
And as you can see, there are around 1,800 pages from unique websites that link to this
page because of a specific stat.
That's a pretty nice opportunity in my opinion.
Now, we didn't stop here.
We also looked at other anchors profiles for other top ranking pages that had a significant
number of referring domains.
And we basically just did the exact same thing and found well over 3,000 lookalike
prospects to our seed.
Alright the next example was when we found an opportunity for our link building guide.
What we noticed was that a competing page was getting backlinks because they used to
have a downloadable ebook in their link building guide.
And like the previous example, there was no CTA or mention of a downloadable ebook on the page.
Now, the pattern I noticed is that all of the referring pages are on the topic of
"top seo ebooks."
So that means our seed prospects are people who have a listicle on the top SEO ebooks.
So what we need to search for are titles of pages that include the word "best or top,"
which implies a listicle and "seo ebooks," which implies the main topic.
So to find our lookalike prospects, we can use Google search or Ahrefs' Content Explorer.
In Google search, you can type in something like intitle:best intitle:seo intitle:ebook.
And we're left with a few hundred results.
Now, you can enable Ahrefs' SEO toolbar to get both domain and page level metrics on the results.
And if you prefer to work in Excel or Sheets, you can export the SERP as needed.
But this job is much easier if you use Ahrefs' Content Explorer.
So I'll search for "best OR top" within parentheses, and then SEO ebook.
Finally, I'll change the search mode to Title and run the search.
And now you can see a few hundred results along with their SEO metrics.
And this report is also filterable and exportable too.
Now, if you want to further expand your list of lookalike prospects, you can simply
change the word "SEO" to something like marketing since link building is a smaller
part of the broader marketing category.
And now we have well over 1,000 prospects in total for this campaign.
Alright, the final seed we talked about was for our page that debunks myths
behind so-called "LSI keywords."
Now, we established that our seed prospect is any page that recommends using LSI keywords,
because there's no such thing as LSI keywords.
And while there were a few hundred prospects in the link profile we looked at in lesson 2.1,
we can easily find a bigger list of lookalike prospects using Content Explorer.
So this time, I'm going to search for "use LSI keywords" as a phrase match, which should
surface pages where authors are recommending visitors to use so-called LSI keywords.
And now we have thousands of prospects who've said this phrase on their page.
So it would just be a matter of vetting these pages and we'll get into this in the next module.
Now, these are just a few methods that I would use to find lookalike prospects for
these hypothetical campaigns.
And while there are other ways to generate similar results, I won't bother going into them
because the most important part of this exercise is to understand
how seed prospects help to broaden the scope of your campaign with lookalike prospects.
Now, there's one more technique to finding lookalike prospects I want to talk about.
And it's not so much about finding them necessarily, but it's an efficient technique
that I find myself using pretty frequently.
And that's scraping.
There are going to be times when you're browsing the web and you
notice a potential seed that's worth exploring.
For example, I was looking for ways to build links to our SEO course landing page in Ahrefs Academy.
And I went through the usual routine of analyzing the backlink profiles of competing pages.
Now, this was all well and good, but then I happened to find another low-hanging
opportunity that none of our organic search competitors would be able to do.
And I discovered it in YouTube analytics.
I realized that our SEO course videos had gotten over a million views in less than a year.
So I was like… man… I'm sure someone has linked to these videos or embedded it in their
posts at some point.
Meaning, these are warm prospects who I could reach out to and ask to link to our
academy instead.
Basically, my idea followed a similar concept to unlinked mentions, which usually has a pretty
high conversion rate for us.
So I ran the video URL in Ahrefs' Site Explorer, and sure enough, this video had collected a ton
of referring domains.
And I also checked the embed URL for this same video in Site Explorer.
And there were even more referring domains to sort through.
So our seed prospect for this hypothetical campaign is anyone linking to one of our
SEO course videos on our YouTube channel.
Or anyone that's embedded the video on their page.
Now, because there's a total of 15 videos of this course on our YouTube channel,
I needed to get all of the URLs so I can run them through a tool like Ahrefs' Batch Analysis.
And to do that, I used the Chrome Scraper Extension.
All you need to do is right click on the information you want to scrape
and click "Scrape similar."
From here, I modified the Xpath code a bit and within seconds, we had a full list of
URLs ready to batch analyze.
Finally, I ran the URLs through Ahrefs' Batch Analysis, sorted by Referring Domains, and I
could instantly see that we had a huge list of lookalike prospects
that might be willing to link to our academy page.
As you can see, finding lookalike prospects is all about finding a footprint within your seed
and following the rabbit hole.
And when you have a general scope of the breadth of the campaign, you're able
to get an idea if actually running the campaign will be worth your time and effort.
Now, when you're dealing with thousands of potential link prospects with multiple seeds,
it can get quite messy.
Plus, sending personalized emails at scale is tough.
And that's where segmenting your link prospects is going to help you stay organized,
convert more emails into links and save you a ton of time.
So in the next lesson, we're going to talk about how you can effectively segment
your prospects so you can scale personalized outreach campaigns.
I'll see you there.