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How to Write Meta Descriptions in a Constantly Changing World (AKA Google Giveth, Google Taketh Away)

Posted by Dr-Pete

Summary: As of mid-May 2018, Google has reverted back to shorter display snippets. Our data suggests these changes are widespread and that most meta descriptions are being cut off in the previous range of about 155–160 characters.

Back in December, Google made a significant shift in how they displayed search snippets, with our research showing many snippets over 300 characters. Over the weekend, they seem to have rolled back that change (Danny Sullivan partially confirmed this on Twitter on May 14). Besides the obvious question — What are the new limits? — it may leave you wondering how to cope when the rules keep changing. None of us have a crystal ball, but I’m going to attempt to answer both questions based on what we know today.

Lies, dirty lies, and statistics…

I pulled all available search snippets from the MozCast 10K (page-1 Google results for 10,000 keywords), since that’s a data set we collect daily and that has a rich history. There were 89,383 display snippets across that data set on the morning of May 15.

I could tell you that, across the entire data set, the minimum length was 6 characters, the maximum was 386, and the mean was about 159. That’s not very useful, for a couple of reasons. First, telling you to write meta descriptions between 6–386 characters isn’t exactly helpful advice. Second, we’re dealing with a lot of extremes. For example, here’s a snippet on a search for “USMC”:

Marine Corps Community Services may be a wonderful organization, but I’m sorry to report that their meta description is, in fact, “apple” (Google appends the period out of, I assume, desperation). Here’s a snippet for a search on the department store “Younkers”:

Putting aside their serious multi-brand confusion, I think we can all agree that “BER Meta TAG1” is not optimal. If these cases teach you anything, it’s only about what not to do. What about on the opposite extreme? Here’s a snippet with 386 characters, from a search for “non-compete agreement”:

Notice the “Jump to Exceptions” and links at the beginning. Those have been added by Google, so it’s tough to say what counts against the character count and what doesn’t. Here’s one without those add-ons that clocks in at 370 characters, from a search for “the Hunger Games books”:

So, we know that longer snippets do still exist. Note, though, that both of these snippets come from Wikipedia, which is an exception to many SEO rules. Are these long descriptions only fringe cases? Looking at the mean (or even the median, in this case) doesn’t really tell us.

The big picture, part 1

Sometimes, you have to let the data try to speak for itself, with a minimum of coaxing. Let’s look at all of the snippets that were cut off (ending in “…”) and remove video results (we know from previous research that these skew a bit shorter). This leaves 42,863 snippets (just under half of our data set). Here’s a graph of all of the cut-off lengths, gathered into 25 character bins (0–25, 26–50, etc.):

This looks very different from our data back in December, and is clearly clustered in the 150–175 character range. We see a few Google display snippets cut off after the 300+ range, but those are dwarfed by the shorter cut-offs.

The big picture, part 2

Obviously, there’s a lot happening in that 125–175 character range, so let’s zoom in and look at just the middle portion of the frequency distribution, broken up into smaller, 5-character buckets:

We can see pretty clearly that the bulk of cut-offs are happening in the 145–165 character range. Before December, our previous guidelines for meta descriptions were to keep them below 155 characters, so it appears that Google has more-or-less reverted to the old rules.

Keep in mind that Google uses proportional fonts, so there is no exact character limit. Some people have hypothesized a pixel-width limit, like with title tags, but I’ve found that more difficult to pin down with multi-line snippets (the situation gets even weirder on mobile results). Practically, it’s also difficult to write to a pixel limit. The data suggests that 155 characters is a reasonable approximation.

To the Wayback Machine… ?!

Should we just go back to a 155 character cut-off? If you’ve already written longer meta descriptions, should you scrap that work and start over? The simple truth is that none of us know what’s going to happen next week. The way I see it, we have four viable options:

(1) Let Google handle it

Some sites don’t have meta descriptions at all. Wikipedia happens to be one of them. Now, Google’s understanding of Wikipedia’s content is much deeper than most sites (thanks, in part, to Wikidata), but many sites do fare fine without the tag. If your choice is to either write bad, repetitive tags or leave them blank, then I’d say leave them blank and let Google sort it out.

(2) Let the … fall where it may

You could just write to the length you think is ideal for any given page (within reason), and if the snippets get cut off, don’t worry about it. Maybe the ellipsis (…) adds intrigue. I’m half-joking, but the reality is that a cut-off isn’t the kiss of death. A good description should entice people to want to read more.

(3) Chop everything at 155 characters

You could go back and mercilessly hack all of your hard work back to 155 characters. I think this is generally going to be time badly spent and may result in even worse search snippets. If you want to rewrite shorter Meta Descriptions for your most important pages, that’s perfectly reasonable, but keep in mind that some results are still showing longer snippets and this situation will continue to evolve.

(4) Write length-adaptive descriptions

Is it possible to write a description that works well at both lengths? I think it is, with some care and planning. I wouldn’t necessarily recommend this for every single page, but maybe there is a way to have our cake and eat at least half of it, too…

The 150/150 approach

I’ve been a bit obsessed with the “inverted pyramid” style of writing lately. This is a journalistic style where you start with the lead or summary of your main point and then break that down into the details, data, and context. While this approach is well suited to the web, its origins come from layout limitations in print. You never knew when your editor would have to cut your article short to fit the available space, so the inverted pyramid style helped guarantee that the most important part would usually be spared.

What if we took this approach to meta descriptions? In other words, why not write a 150-character “lead” that summarizes the page, and then add 150 characters of useful but less essential detail (when adding that detail makes sense and provides value)? The 150/150 isn’t a magic number — you could even do 100/100 or 100/200. The key is to make sure that the text before the cut can stand on its own.

Think of it a bit like an ad, with two separate lines of copy. Let’s take this blog post:

Line 1 (145 chars.)

In December, we reported that Google increased search snippets to over 300 characters. Unfortunately, it looks like the rules have changed again.

Line 2 (122 chars.)

According to our new research (May 2018), the limit is back to 155-160 characters. How should SEOs adapt to these changes?

Line 1 has the short version of the story and hopefully lets searchers know they’re heading down the right path. Line 2 dives into a few details and gives away just enough data (hopefully) to be intriguing. If Google uses the longer description, it should work nicely, but if they don’t, we shouldn’t be any worse for wear.

Should you even bother?

Is this worth the effort? I think writing effective descriptions that engage search visitors is still very important, in theory (and that this indirectly impacts even ranking), but you may find you can write perfectly well within a 155-character limit. We also have to face the reality that Google seems to be rewriting more and more descriptions. This is difficult to measure, as many rewrites are partial, but there’s no guarantee that your meta description will be used as written.

Is there any way to tell when a longer snippet (>300 characters) will still be used? Some SEOs have hypothesized a link between longer snippets and featured snippets at the top of the page. In our overall data set, 13.3% of all SERPs had featured snippets. If we look at just SERPs with a maximum display snippet length of 160 characters (i.e. no result was longer than 160 characters), the featured snippet occurrence was 11.4%. If we look at SERPs with at least one display snippet over 300 characters, featured snippets occurred at a rate of 41.8%. While that second data set is fairly small, it is a striking difference. There does seem to be some connection between Google’s ability to extract answers in the form of featured snippets and their ability or willingness to display longer search snippets. In many cases, though, these longer snippets are rewrites or taken directly from the page, so even then there’s no guarantee that Google will use your longer meta description.

For now, it appears that the 155-character guideline is back in play. If you’ve already increased some of your meta descriptions, I don’t think there’s any reason to panic. It might make sense to rewrite overly-long descriptions on critical pages, especially if the cut-offs are leading to bad results. If you do choose to rewrite some of them, consider the 150/150 approach — at least then you’ll be a bit more future-proofed.


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Monitoring Featured Snippets – Whiteboard Friday

Posted by BritneyMuller

We’ve covered finding featured snippet opportunities. We’ve covered the process of targeting featured snippets you want to win. Now it’s time for the third and final piece of the puzzle: how to monitor and measure the effectiveness of all your efforts thus far. In this episode of Whiteboard Friday, Britney shares three pro tips on how to make sure your featured snippet strategy is working.

Monitoring featured snippets

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Video Transcription

Hey, Moz fans. Welcome to another edition of Whiteboard Friday. Today we are going over part three of our three-part series all about featured snippets. So part one was about how to discover those featured snippet opportunities, part two was about how to target those, and this final one is how to properly monitor and measure the effectiveness of your targeting.

So we’ll jump right in. So there are a couple different steps and things you can do to go through this.

I. Manually resubmit URL and check SERP in incognito

First is just to manually resubmit a URL after you have tweaked that page to target that featured snippet. Super easy to do. All you do is go to Google and you type in “add URL to Google.” You will see a box pop up where you can submit that URL. You can also go through Search Console and submit it manually there. But this just sort of helps Google to crawl it a little faster and hopefully get it reprioritized to, potentially, a featured snippet.

From there, you can start to check for the keyword in an incognito window. So, in Chrome, you go to File > New Incognito. It tends to be a little bit more unbiased than your regular browser page when you’re doing a search. So this way, you’d start to get an idea of whether or not you’re moving up in that search result. So this can be anywhere from, I kid you not, a couple of minutes to months.

So Google tends to test different featured snippets over a long period of time, but occasionally I’ve had experience and I know a lot of you watching have had different experiences where you submit that URL to Google and boom — you’re in that featured snippet. So it really just depends, but you can keep an eye on things this way.

II. Track rankings for target keyword and Search Console data!

But you also want to keep in mind that you want to start also tracking for rankings for your target keyword as well as Search Console data. So what does that click-through rate look like? How are the impressions? Is there an upward trend in you trying to target that snippet?

So, in my test set, I have seen an average of around 80% increase in those keywords, just in rankings alone. So that’s a good sign that we’re improving these pages and hopefully helping to get us more featured snippets.

III. Check for other featured snippets

Then this last kind of pro tip here is to check for other instances of featured snippets. This is a really fun thing to do. So if you do just a basic search for “what are title tags,” you’re going to see Moz in the featured snippet. Then if you do “what are title tags” and then you do a -site:Moz.com, you’re going to see another featured snippet that Google is pulling is from a different page, that is not on Moz.com. So really interesting to sort of evaluate the types of content that they are testing and pulling for featured snippets.

Another trick that you can do is to append this ampersand, &num=1, &num=2 and so forth. What this is doing is you put this at the end of your Google URL for a search. So, typically, you do a search for “what are title tags,” and you’re going to see Google.com/search/? that typical markup. You can do a close-up on this, and then you’re just going to append it to pull in only three results, only two results, only four results, or else you can go longer and you can see if Google is pulling different featured snippets from that different quota of results. It’s really, really interesting, and you start to see what they’re testing and all that great stuff. So definitely play around with these two hacks right here.


Then lastly, you really just want to set the frequency of your monitoring to meet your needs. So hopefully, you have all of this information in a spreadsheet somewhere. You might have the keywords that you’re targeting as well as are they successful yet, yes or no. What’s the position? Is that going up or down?

Then you can start to prioritize. If you’re doing hundreds, you’re trying to target hundreds of featured snippets, maybe you check the really, really important ones once a week. Some of the others maybe are monthly checks.

From there, you really just need to keep track of, “Okay, well, what did I do to make that change? What was the improvement to that page to get it in the featured snippet?” That’s where you also want to keep detailed notes on what’s working for you and in your space and what’s not.

So I hope this helps. I look forward to hearing all of your featured snippet targeting stories. I’ve gotten some really awesome emails and look forward to hearing more about your journey down below in the comments. Feel free to ask me any questions and I look forward to seeing you on our next edition of Whiteboard Friday. Thanks.

Video transcription by Speechpad.com


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How to Discover and Monitor Bad Backlinks

Posted by rjonesx.

Identifying bad backlinks has become easier over the past few years with better tool sets, bigger link indexes, and increased knowledge, but for many in our industry it’s still crudely implemented. While the ideal scenario would be to have a professional poring over your link profile and combing each link one-by-one for concerns, for many webmasters that’s just too expensive (and, frankly, overkill).

I’m going to walk through a simple methodology using Link Explorer and Excel (although you could do this with Google Sheets just as easily) to combine together the power of Moz Link Explorer, Keyword Explorer Lists, and finally Link Lists to do a comprehensive link audit.

The basics

There are several components involved in determining whether a link is “bad” and should potentially be removed. Ultimately, we want to be able to measure the riskiness of the link (how likely is Google to flag the link as manipulative and how much do we depend on the link for value). Let me address three common factors used by SEOs to determine this score:

Trust metrics:

There are a handful of metrics in our industry that are readily available to help point out concerning backlinks. The two that come to mind most often are Moz Spam Score and Majestic Trust Flow (or, better yet, the difference between Citation Flow and Trust Flow). These two scores actually work quite differently. Moz’s Spam Score predicts the likelihood a domain is banned or penalized based on certain site features. Majestic Trust Flow determines the trustworthiness of a domain or page based on the quality of links pointing to it. While calculated quite differently, the goal is to help webmasters identify which sites are trustworthy and which are not. However, while these are a good starting point, they aren’t sufficient on their own to give you a clear picture of whether a link is good or bad.

Anchor text manipulation:

One of the first things an SEO learns is that using valuable anchor text can help increase your rankings. The very next thing they learn is that using valuable anchor text can bring on a penalty. The reason for this is pretty clear: the likelihood a webmaster will give you valuable anchor text out of the goodness of their heart is very rare, so over-optimization sticks out like a sore thumb. So, how do we measure anchor text manipulation? If we look at anchor text with our own eyes, this seems to be rather intuitive, but there’s a better way to do it in an automated, at-scale fashion that will allow us to better judge links.

Low authority:

Finally, low-authority links — especially when you would expect higher authority based on the domain — are concerning. A good link should come from an internally well-linked page on a site. If the difference between the Domain Authority and Page Authority is very high, it can be a concern. It isn’t a strong signal, but it is one worth looking at. This is especially obvious in certain types of spam, like paginated comment spam or forum profile spam.

So, let’s jump into how we can pull together a quick backlink analysis taking into account these various features of a bad backlink profile. If you’d like to follow along with this tutorial, hop into Link Explorer in another tab:

Follow along with Link Explorer

Step 1: Get the backlink data

The first and easiest step is just to get your backlink data from Link Explorer’s huge backlink index. With nearly 30 trillion links in our index, you can rest assured that we will find most of the bad backlinks with which you should be concerned. To begin, visit the Link Explorer > Inbound Links section and enter in the domain or page which you wish to analyze.

How to Find Bad Backlinks

Because we aren’t concerned with nofollow links, you will want to set the “follow” filter so that we only export followed links. We also aren’t concerned with deleted links, so we can set the Link Status to “Active.”

How to Find Bad Backlinks

Once you have set these filters, hit the “Export” button. You will have a couple of choices. If your site has fewer than 1,000 backlinks, go ahead and choose the immediate download. However, if your link profile is larger, choose the largest setting and be patient for the download to be prepared. We can keep going with other steps of the project in the meantime, but you don’t want to miss out on bad links, which means you need to export them all.

A lot of SEOs will stop at this point. With PA, DA, and Spam Score included in the standard export, you can do a damn good job of finding bad links. Link Explorer does all of that out-of-the-box for you. But for our purposes here, we wan’t to go a step further and do “anchor text qualification.” This is especially valuable for large link profiles.

Step 2: Get anchor text

Getting anchor text out of the new Link Explorer is incredibly simple. Just visit Link Explorer > Anchor Text and hit the Export button. No extra filters will be needed here.

How to Find Bad Backlinks

Step 3: Measure anchor text value

Now here is a quick trick where we can take advantage of Moz Keyword Explorer’s Keyword Lists to find anchor text that appears to be manipulated. First, we want to remove some of the extraneous anchor text which we know absolutely won’t be concerning, such as URLs as anchor text. This step isn’t completely necessary, but will save you some some credits in Moz Keyword Explorer, so it might be worth it.

How to Find Bad Backlinks

After you’ve removed the extraneous anchor text, we’ll just copy and paste our anchor text into a new keyword list for Keyword Explorer.

How to Find Bad Backlinks

By putting the anchor text into Keyword Explorer, we’ll be able to sort anchor text by search volume. It isn’t very common that anchor text happens to have a high search volume, but when webmasters are trying to manipulate search results they often use the keyword for which they’d like to rank in the anchor text. Thus, we can use the search volume of anchor text as a proxy for manipulated anchor text. In fact, when working with Remove’em before I joined Moz, we discovered the anchor text manipulation was the most predictive factor in link penalties.

Step 4: Merge, filter, sort, & model

We will now merge the data (backlinks export and keyword list export) to finally get that list of concerning backlinks. Let’s start with the backlink export. We’ll open it up in Excel and then remove duplicate domain-anchor text pairs.

I’ll start by showing you a quick trick to extract out the domains from a long list of URLs. I copied the list of URLs from the first column to the last column in Excel, and then chose Data > Text to Columns > Delimited > Other > /. This will cause the URLs to be split into different columns wherever the slash occurs, leaving you with the 4th new column being just the domain names.

How to Find Bad Backlinks

Once you have completed this step, we are going to remove duplicate domain-anchor text pairs. Notice that we aren’t going to limit ourselves to one link per domain, which is what many SEOs do. This would be a mistake, since there could be multiple concerning links on the site with different anchor text.

How to Find Bad Backlinks

After choosing Data > Remove Duplicates, I select the column of Anchor Text and the column of Domain. With the duplicates removed, we are now left with the links we want to judge as good or bad. We need one more thing, though. We need to merge in the search volume data we got from Keyword Explorer. Hit the export button on the keyword list you created from anchor text in Keyword Explorer:

How to Find Bad Backlinks

Open up the export and then copy and paste the data into a second sheet in Excel, next to the backlinks sheet you already created and filtered. In this case, I named the two sheets “Raw Data” and “Anchor Text Data”:

How to Find Bad Backlinks

You’ll then want to do a VLOOKUP on the backlinks spreadsheet to create a column with the search volume for the anchor text on each link. I’ve taken a screenshot of the VLOOKUP formula I used, but yours will look a little different depending upon the the names of the sheets and the exact columns you’ve created.

Excel formula: =IF(ISNA(VLOOKUP(C2,'Anchor Text Data'!$A$1:$I$402,3,FALSE)),0,VLOOKUP(C2,'Anchor Text Data'!$1:$I$402,3,FALSE))

=IF(ISNA(VLOOKUP(C2,’Anchor Text Data’!$A$1:$I$402,3,FALSE)),0,VLOOKUP(C2,’Anchor Text Data’!$1:$I$402,3,FALSE))

It looks a little complicated, but that’s simply because I’m using two VLOOKUPs simultaneously to replace N/A results with the number 0. You can always manually put in 0 wherever N/A shows up.

Now it’s time for the fun part: modeling. First, I recommend sorting by the volume column you just created just so you can see the most concerning anchor text at the top. It’s amazing to see links with anchor text like “ring” or “jewelry” automatically populate at the top of the list, since they’re also keywords with high search volume.

How to Find Bad Backlinks

Second, we’ll create a new column with a formula that takes into account the quality of the link, the riskiness of the anchor text, and the Spam Score:

Excel formula: =D11+(F11-E11)+(LOG(G11+1)*10)+(LOG(O11+1)*10)

=D11+(F11-E11)+(LOG(G11+1)*10)+(LOG(O11+1)*10)

Let’s break down that formula real quickly:

  • D11: This is simply the Spam Score
  • (F11-E11): This is the Domain Authority minus the Page Authority. (This is a bit debatable — some people might just prefer to choose 100-E11)
  • (Log(G11+1)*10): This is a fancy way of converting the number of times this anchor text link occurs into a consistent number for our equation. Without taking the log(), having a high number here could overcome the other signals.
  • (Log(O11+1)*10): This is a fancy way of converting the search volume to a number consistent for our equation. Without taking the log(), having a high search volume could also overcome other signals.

Once we run this equation and create a new column, we can sort by “Riskiness” and find the links with which we should be most concerned.

How to Find Bad Backlinks

As you can see, examples of comment spam and paid links popped to the top of the list because the formula gives a higher value to low-quality, spammy links with risky anchor text. But wait, there’s more!

Step 5: Build a Link List

Link Explorer doesn’t just leave you hanging after doing analysis. Our goal is to help you do SEO, not just analyze it. Your next step is to start a new Link List.

The Link List feature allows you to track whether certain links are alive. If you embark on a campaign to try and remove some of these spammier links, you can create a Link List and use it to monitor the status of those links. Just create a new list by naming it, adding your domain, and then copying and pasting the concerning links.

How to Find Bad Backlinks

You can now just monitor the Link List as you do your outreach to remove bad links. The Link List will track all the metrics, including whether the link has been removed.

How to Find Bad Backlinks

Wrapping up

Whether you want to do a cursory backlink audit by just looking at Spam Score and PA, or a deep-dive taking into account anchor text qualification, Link Explorer + Keyword Explorer and Link Lists make it possible. With our greatly improved backlink index, you can now rest assured that the data you need is right at your finger tips and, if you need to get down-and-dirty in Excel, you can readily export it to do deeper analysis.

Find your spammy links!

Good luck hunting bad backlinks!


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Moz’s Link Data Used to Suck… But Not Anymore! The New Link Explorer is Here – Whiteboard Friday

Posted by randfish

Earlier this week we launched our brand-new link building tool, and we’re happy to say that Link Explorer addresses and improves upon a lot of the big problems that have plagued our legacy link tool, Open Site Explorer. In today’s Whiteboard Friday, Rand transparently lists out many of the biggest complaints we’ve heard about OSE over the years and explains the vast improvements Link Explorer provides, from DA scores updated daily to historic link data to a huge index of almost five trillion URLs.

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

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Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week I’m very excited to say that Moz’s Open Site Explorer product, which had a lot of challenges with it, is finally being retired, and we have a new product, Link Explorer, that’s taking its place. So let me walk you through why and how Moz’s link data for the last few years has really kind of sucked. There’s no two ways about it.

If you heard me here on Whiteboard Friday, if you watched me at conferences, if you saw me blogging, you’d probably see me saying, “Hey, I personally use Ahrefs, or I use Majestic for my link research.” Moz has a lot of other good tools. The crawler is excellent. Moz Pro is good. But Open Site Explorer was really lagging, and today, that’s not the case. Let me walk you through this.

The big complaints about OSE/Mozscape

1. The index was just too small

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

Mozscape was probably about a fifth to a tenth the size of its competitors. While it got a lot of the quality good links of the web, it just didn’t get enough. As SEOs, we need to know all of the links, the good ones and the bad ones.

2. The data was just too old

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

So, in Mozscape, a link that you built on November 1st, you got a link added to a website, you’re very proud of yourself. That’s excellent. You should expect that a link tool should pick that up within maybe a couple weeks, maybe three weeks at the outside. Google is probably picking it up within just a few days, sometimes hours.

Yet, when Mozscape would crawl that, it would often be a month or more later, and by the time Mozscape processed its index, it could be another 40 days after that, meaning that you could see a 60- to 80-day delay, sometimes even longer, between when your link was built and when Mozscape actually found it. That sucks.

3. PA/DA scores took forever to update

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

PA/DA scores, likewise, took forever to update because of this link problem. So the index would say, oh, your DA is over here. You’re at 25, and now maybe you’re at 30. But in reality, you’re probably far ahead of that, because you’ve been building a lot of links that Mozscape just hasn’t picked up yet. So this is this lagging indicator. Sometimes there would be links that it just didn’t even know about. So PA and DA just wouldn’t be as accurate or precise as you’d want them to be.

4. Some scores were really confusing and out of date

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

MozRank and MozTrust relied on essentially the original Google PageRank paper from 1997, which there’s no way that’s what’s being used today. Google certainly uses some view of link equity that’s passed between links that is similar to PageRank, and I think they probably internally call that PageRank, but it looks nothing like what MozRank was called.

Likewise, MozTrust, way out of date, from a paper in I think 2002 or 2003. Much more advancements in search have happened since then.

Spam score was also out of date. It used a system that was correlated with what spam looked like three, four years ago, so much more up to date than these two, but really not nearly as sophisticated as what Google is doing today. So we needed to toss those out and find their replacements as well.

5. There was no way to see links gained and lost over time

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

Mozscape had no way to see gained and lost links over time, and folks thought, “Gosh, these other tools in the SEO space give me this ability to show me links that their index has discovered or links they’ve seen that we’ve lost. I really want that.”

6. DA didn’t correlate as well as it should have

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

So over time, DA became a less and less indicative measure of how well you were performing in Google’s rankings. That needed to change as well. The new DA, by the way, much, much better on this front.

7. Bulk metrics checking and link reporting was too hard and manual

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

So folks would say, “Hey, I have this giant spreadsheet with all my link data. I want to upload that. I want you guys to crawl it. I want to go fetch all your metrics. I want to get DA scores for these hundreds or thousands of websites that I’ve got. How do I do that?” We didn’t provide a good way for you to do that either unless you were willing to write code and loop in our API.

8. People wanted distribution of their links by DA

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

They wanted distributions of their links by domain authority. Show me where my links come from, yes, but also what sorts of buckets of DA do I have versus my competition? That was also missing.

So, let me show you what the new Link Explorer has.

Moz's new Link Explorer

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Wow, look at that magical board change, and it only took a fraction of a second. Amazing.

What Link Explorer has done, as compared to the old Open Site Explorer, is pretty exciting. I’m actually very proud of the team. If you know me, you know I am a picky SOB. I usually don’t even like most of the stuff that we put out here, but oh my god, this is quite an incredible product.

1. Link Explorer has a GIANT index

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

So I mentioned index size was a big problem. Link Explorer has got a giant index. Frankly, it’s about 20 times larger than what Open Site Explorer had and, as you can see, very, very competitive with the other services out there. Majestic Fresh says they have about a trillion URLs from their I think it’s the last 60 days. Ahrefs, about 3 trillion. Majestic’s historic, which goes all time, has about 7 trillion, and Moz, just in the last 90 days, which I think is our index — maybe it’s a little shorter than that, 60 days — 4.7 trillion, so almost 5 trillion URLs. Just really, really big. It covers a huge swath of the web, which is great.

2. All data updates every 24 hours

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

So, unlike the old index, it is very fresh. Every time it finds a new link, it updates PA scores and DA scores. The whole interface can show you all the links that it found just yesterday every morning.

3. DA and PA are tracked daily for every site

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

You don’t have to track them yourself. You don’t have to put them into your campaigns. Every time you go and visit a domain, you will see this graph showing you domain authority over time, which has been awesome.

For my new company, I’ve been tracking all the links that come in to SparkToro, and I can see my DA rising. It’s really exciting. I put out a good blog post, I get a bunch of links, and my DA goes up the next day. How cool is that?

4. Old scores are gone, and new scores are polished and high quality

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

So we got rid of MozRank and MozTrust, which were very old metrics and, frankly, very few people were using them, and most folks who were using them didn’t really know how to use them. PA basically takes care of both of them. It includes the weight of links that come to you and the trustworthiness. So that makes more sense as a metric.

Spam score is now on a 0 to 100% risk model instead of the old 0 to 17 flags and the flags correlate to some percentage. So 0 to 100 risk model. Spam score is basically just a machine learning built model against sites that Google penalized or banned.

So we took a huge amount of domains. We ran their names through Google. If they couldn’t rank for their own name, we said they were penalized. If we did a site: the domain.com and Google had de-indexed them, we said they were banned. Then we built this risk model. So in the 90% that means 90% of sites that had these qualities were penalized or banned. 2% means only 2% did. If you have a 30% spam score, that’s not too bad. If you have a 75% spam score, it’s getting a little sketchy.

5. Discovered and lost links are available for every site, every day

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

So again, for this new startup that I’m doing, I’ve been watching as I get new links and I see where they come from, and then sometimes I’ll reach out on Twitter and say thank you to those folks who are linking to my blog posts and stuff. But it’s very, very cool to see links that I gain and links that I lose every single day. This is a feature that Ahrefs and Majestic have had for a long time, and frankly Moz was behind on this. So I’m very glad that we have it now.

6. DA is back as a high-quality leading indicator of ranking ability

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

So, a note that is important: everyone’s DA has changed. Your DA has changed. My DA has changed. Moz’s DA changed. Google’s DA changed. I think it went from a 98 to a 97. My advice is take a look at yourself versus all your competitors that you’re trying to rank against and use that to benchmark yourself. The old DA was an old model on old data on an old, tiny index. The new one is based on this 4.7 trillion size index. It is much bigger. It is much fresher. It is much more accurate. You can see that in the correlations.

7. Building link lists, tracking links that you want to acquire, and bulk metrics checking is now easy

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

Building link lists, tracking links that you want to acquire, and bulk metrics checking, which we never had before and, in fact, not a lot of the other tools have this link tracking ability, is now available through possibly my favorite feature in the tool called Link Tracking Lists. If you’ve used Keyword Explorer and you’ve set up your keywords to watch those over time and to build a keyword research set, very, very similar. If you have links you want to acquire, you add them to this list. If you have links that you want to check on, you add them to this list. It will give you all the metrics, and it will tell you: Does this link to your website that you can associate with a list, or does it not? Or does it link to some page on the domain, but maybe not exactly the page that you want? It will tell that too. Pretty cool.

8. Link distribution by DA

Moz's Link Data Used to Suck... But Not Anymore! The New Link Explorer is Here - Whiteboard Friday

Finally, we do now have link distribution by DA. You can find that right on the Overview page at the bottom.

Look, I’m not saying Link Explorer is the absolute perfect, best product out there, but it’s really, really damn good. I’m incredibly proud of the team. I’m very proud to have this product out there.

If you’d like, I’ll be writing some more about how we went about building this product and a bunch of agency folks that we spent time with to develop this, and I would like to thank all of them of course. A huge thank you to the Moz team.

I hope you’ll do me a favor. Check out Link Explorer. I think, very frankly, this team has earned 30 seconds of your time to go check it out.

Try out Link Explorer!

All right. Thanks, everyone. We’ll see you again for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com


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Efficient Link Reclamation: How to Speed Up & Scale Your Efforts

Posted by DarrenKingman

Link reclamation: Tools, tools everywhere

Every link builder, over time, starts to narrow down their favorite tactics and techniques. Link reclamation is pretty much my numero-uno. In my experience, it’s one of the best ROI activities we can use for gaining links particularly to the homepage, simply because the hard work — the “mention” (in whatever form that is) — is already there. That mention could be of your brand, an influencer who works there, or a tagline from a piece of content you’ve produced, whether it’s an image asset, video, etc. That’s the hard part. But with it done, and after a little hunting and vetting the right mentions, you’re just left with the outreach.

Aside from the effort-to-return ratio, there are various other benefits to link reclamation:

  1. It’s something you can start right away without assets
  2. It’s a low risk/low investment form of link building
  3. Nearly all brands have unlinked mentions, but big brands tend to have the most and therefore see the biggest routine returns
  4. If you’re doing this for clients, they get to see an instant return on their investment

Link reclamation isn’t a new tactic, but it is becoming more complex and tool providers are out there helping us to optimize our efforts. In this post, I’m going to talk a little about those tools and how to apply them to speed up and scale your link reclamation.

Finding mentions

Firstly, we want to find mentions. No point getting too fancy at this stage, so we just head over to trusty Google and search for the range of mentions we’re working on.

As I described earlier, these mentions can come in a variety of shapes and sizes, so I would generally treat each type of mention that I’m looking for as a separate project. For example, if Moz were the site I was working on, I would look for mentions of the brand and create that as one “project,” then look for mentions of Followerwonk and treat that as another, and so on. The reasons why will become clear later on!

So, we head to the almighty Google and start our searches.

To help speed things up it’s best to expand your search result to gather as many URLs as you can in as few clicks as possible. Using Google’s Search Settings, you can quickly max out your SERPs to one hundred results, or you can install a plugin like GInfinity, which allows you to infinitely scroll through the results and grab as many as you can before your hand cramps up.

Now we want to start copying as many of these results as possible into an Excel sheet, or wherever it is you’ll be working from. Clicking each one and copying/pasting is hell, so another tool to quickly install for Chrome is Linkclump. With this one, you’ll be able to right click, drag, and copy as many URLs as you want.

Linkclump Pro Tip: To ensure you don’t copy the page titles and cache data from a SERP, head over to your Linkclump settings by right-clicking the extension icon and selecting “options.” Then, edit your actions to include “URLs only” and “copied to clipboard.” This will make the next part of the process much easier!

Filtering your URL list

Now we’ve got a bunch of URLs, we want to do a little filtering, so we know a) the DA of these domains as a proxy metric to qualify mentions, and b) whether or not they already link to us.

How you do this bit will depend on which platforms you have access to. I would recommend using BuzzStream as it combines a few of the future processes in one place, but URL Profiler can also be used before transferring your list over to some alternative tools.

Using BuzzStream

If you’re going down this road, BuzzStream can pretty much handle the filtering for you once you’ve uploaded your list of URLs. The system will crawl through the URLs and use their API to display Domain Authority, as well as tell you if the page already links to you or not.

The first thing you’ll want to do is create a “project” for each type of mention you’re sourcing. As I mentioned earlier this could be “brand mentions,” “creative content,” “founder mentions,” etc.

When adding your “New Project,” be sure to include the domain URL for the site you’re building links to, as shown below. BuzzStream will then go through and crawl your list of URLs and flag any that are already linking to you, so you can filter them out.

Next, we need to get your list of URLs imported. In the Websites view, use Add Websites and select “Add from List of URLs”:

The next steps are really easy: Upload your list of URLs, then ensure you select “Websites and Links” because we want BuzzStream to retrieve the link data for us.

Once you’ve added them, BuzzStream will work through the list and start displaying all the relevant data for you to filter through in the Link Monitoring tab. You can then sort by: link status (after hitting “Check Backlinks” and having added your URL), DA, and relationship stage to see if you/a colleague have ever been in touch with the writer (especially useful if you/your team uses BuzzStream for outreach like we do at Builtvisible).

Using URL Profiler

If you’re using URL Profiler, firstly, make sure you’ve set up URL Profiler to work with your Moz API. You don’t need a paid Moz account to do this, but having one will give you more than 500 checks per day on the URLs you and the team are pushing through.

Then, take the list of URLs you’ve copied using Linkclump from the SERPs (I’ve just copied the top 10 from the news vertical for “moz.com” as my search), then paste the URLs in the list. You’ll need to select “Moz” in the Domain Level Data section (see screenshot) and also fill out the “Domain to Check” with your preferred URL string (I’ve put “Moz.com” to capture any links to secure, non-secure, alternative subdomains and deeper level URLs).

Once you’ve set URL Profiler running, you’ll get a pretty intimidating spreadsheet, which can simply be cut right down to the columns: URL, Target URL and Domain Mozscape Domain Authority. Filter out any rows that have returned a value in the Target URL column (essentially filtering out any that found an HREF link to your domain), and any remaining rows with a DA lower than your benchmark for links (if you work with one).

And there’s my list of URLs that we now know:

1) don’t have any links to our target domain,

2) have a reference to the domain we’re working on, and

3) boast a DA above 40.

Qualify your list

Now that you’ve got a list of URLs that fit your criteria, we need to do a little manual qualification. But, we’re going to use some trusty tools to make it easy for us!

The key insight we’re looking for during our qualification is if the mention is in a natural linking element of the page. It’s important to avoid contacting sites where the mention is only in the title, as they’ll never place the link. We particularly want placements in the body copy as these are natural link locations and so increase the likelihood of your efforts leading somewhere.

So from my list of URLs, I’ll copy the list and head over to URLopener.com (now bought by 10bestseo.com presumably because it’s such an awesome tool) and paste in my list before asking it to open all the URLs for me:

Now, one by one, I can quickly scan the URLs and look for mentions in the right places (i.e. is the mention in the copy, is it in the headline, or is it used anywhere else where a link might not look natural?).

When we see something like this (below), we’re making sure to add this URL to our final outreach list:

However, when we see this (again, below), we’re probably stripping the URL out of our list as there’s very little chance the author/webmaster will add a link in such a prominent and unusual part of the page:

The idea is to finish up with a list of unlinked mentions in spots where a link would fit naturally for the publisher. We don’t want to get in touch with everyone, with mentions all over the place, as it can harm your future relationships. Link building needs to make sense, and not just for Google. If you’re working in a niche that mentions your client, you likely want not only to get a link but also build a relationship with this writer — it could lead to 5 links further down the line.

Getting email addresses

Now that you’ve got a list of URLs that all feature your brand/client, and you’ve qualified this list to ensure they are all unlinked and have mentions in places that make sense for a link, we need to do the most time-consuming part: finding email addresses.

To continue expanding our spreadsheet, we’re going to need to know the contact details of the writer or webmaster to request our link from. To continue our theme of efficiency, we just want to get the two most important details: email address and first name.

Getting the first name is usually pretty straightforward and there’s not really a need to automate this. However, finding email addresses could be an entirely separate article in itself, so I’ll be brief and get to the point. Read this, and here’s a summary of places to look and the tools I use:

  • Author page
  • Author’s personal website
  • Author’s Twitter profile
  • Rapportive & Email Permutator
  • Allmytweets
  • Journalisted.com
  • Mail Tester

More recently, we’ve been also using Skrapp.io. It’s a LinkedIn extension (like Hunter.io) that installs a “Find Email” button on LinkedIn with a percentage of accuracy. This can often be used with Mail Tester to discover if the suggested email address provided is working or not.

It’s likely to be a combination of these tools that helps you navigate finding a contact’s email address. Once we have it, we need to get in touch — at scale!

Pro Tip: When using Allmytweets, if you’re finding that searches for “email” or “contact” aren’t working, try “dot.” Usually journalists don’t put their full email address on public profiles in a scrapeable format, so they use “me@gmail [dot] com” to get around it.

Making contact

So, because this is all about making the process efficient, I’m not going to repeat or try to build on the other already useful articles that provide templates for outreach (there is one below, but that’s just as an example!). However, I am going to show you how to scale your outreach and follow-ups.

Mail merges

If you and your team aren’t set in your ways with a particular paid tool, your best bet for optimizing scale is going to be a mail merge. There are a number of them out there, and honestly, they are all fairly similar with either varying levels of free emails per day before you have to pay, or they charge from the get-go. However, for the costs we’re talking about and the time it saves, building a business case to either convince yourself (freelancers) or your finance department (everyone else!) will be a walk in the park.

I’ve been a fan of Contact Monkey for some time, mainly for tracking open rates, but their mail merge product is also part of the $10-a-month package. It’s a great deal. However, if you’re after something a bit more specific, YAMM is free to a point (for personal Gmail accounts) and can send up to 50 emails a day.

You’ll likely need to work through the process with the whatever tool you pick but, using your spreadsheet, you’ll be able to specify which fields you want the mail merge to select from, and it’ll insert each element into the email.

For link reclamation, this is really as personable as you need to get — no lengthy paragraphs on how much you loved [insert article related to my infographic] or how long you’ve been following them on Twitter, just a good old to the point email:

Hi [first name],

I recently found a mention of a company I work with in one of your articles.

Here’s the article:
[insert URL]

Where you’ve mentioned our company, Moz, would you be able to provide a link back to the domain Moz.com, in case users would like to know more about us?

Many thanks,
Darren.

If using BuzzStream

Although BuzzStream’s mail merge options are pretty similar to the process above, the best “above and beyond” feature that BuzzStream has is that you can schedule in follow up emails as well. So, if you didn’t hear back the first time, after a week or so their software will automatically do a little follow-up, which in my experience, often leads to the best results.

When you’re ready to start sending emails, select the project you’ve set up. In the “Websites” section, select “Outreach.” Here, you can set up a sequence, which will send your initial email as well as customized follow-ups.

Using the same extremely brief template as above, I’ve inserted my dynamic fields to pull in from my data set and set up two follow up emails due to send if I don’t hear back within the next 4 days (BuzzStream hooks up with my email through Outlook and can monitor if I receive an email from this person or not).

Each project can now use templates set up for the type of mention you’re following up. By using pre-set templates, you can create one for brand mention, influencers, or creative projects to further save you time. Good times.

I really hope this has been useful for beginners and seasoned link reclamation pros alike. If you have any other tools you use that people may find useful or have any questions, please do let us know below.

Thanks everyone!


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