Moving 5 Domains to 1: An SEO Case Study

Posted by Dr-Pete

People often ask me if they should change domain names, and I always shudder just a little. Changing domains is a huge, risky undertaking, and too many people rush into it seeing only the imaginary upside. The success of the change also depends wildly on the details, and it’s not the kind of question anyone should be asking casually on social media.

Recently, I decided that it was time to find a new permanent home for my personal and professional blogs, which had gradually spread out over 5 domains. I also felt my main domain was no longer relevant to my current situation, and it was time for a change. So, ultimately I ended up with a scenario that looked like this:

The top three sites were active, with UserEffect.com being my former consulting site and blog (and relatively well-trafficked). The bottom two sites were both inactive and were both essentially gag sites. My one-pager, AreYouARealDoctor.com, did previously rank well for “are you a real doctor”, so I wanted to try to recapture that.

I started migrating the 5 sites in mid-January, and I’ve been tracking the results. I thought it would be useful to see how this kind of change plays out, in all of the gory details. As it turns out, nothing is ever quite “textbook” when it comes to technical SEO.

Why Change Domains at All?

The rationale for picking a new domain could fill a month’s worth of posts, but I want to make one critical point – changing domains should be about your business goals first, and SEO second. I did not change domains to try to rank better for “Dr. Pete” – that’s a crap shoot at best. I changed domains because my old consulting brand (“User Effect”) no longer represented the kind of work I do and I’m much more known by my personal brand.

That business case was strong enough that I was willing to accept some losses. We went through a similar transition here
from SEOmoz.org to Moz.com. That was a difficult transition that cost us some SEO ground, especially short-term, but our core rationale was grounded in the business and where it’s headed. Don’t let an SEO pipe dream lead you into a risky decision.

Why did I pick a .co domain? I did it for the usual reason – the .com was taken. For a project of this type, where revenue wasn’t on the line, I didn’t have any particular concerns about .co. The evidence on how top-level domains (TLDs) impact ranking is tough to tease apart (so many other factors correlate with .com’s), and Google’s attitude tends to change over time, especially if new TLDs are abused. Anecdotally, though, I’ve seen plenty of .co’s rank, and I wasn’t concerned.

Step 1 – The Boring Stuff

It is absolutely shocking how many people build a new site, slap up some 301s, pull the switch, and hope for the best. It’s less shocking how many of those people end up in Q&A a week later, desperate and bleeding money.


Planning is hard work, and it’s boring – get over it.

You need to be intimately familiar with every page on your existing site(s), and, ideally, you should make a list. Not only do you have to plan for what will happen to each of these pages, but you’ll need that list to make sure everything works smoothly later.

In my case, I decided it might be time to do some housekeeping – the User Effect blog had hundreds of posts, many outdated and quite a few just not very good. So, I started with the easy data – recent traffic. I’m sure you’ve seen this Google Analytics report (Behavior > Site Content > All Pages):

Since I wanted to focus on recent activity, and none of the sites had much new content, I restricted myself to a 3-month window (Q4 of 2014). Of course, I looked much deeper than the top 10, but the principle was simple – I wanted to make sure the data matched my intuition and that I wasn’t cutting off anything important. This helped me prioritize the list.

Of course, from an SEO standpoint, I also didn’t want to lose content that had limited traffic but solid inbound links. So, I checked my “Top Pages” report in
Open Site Explorer:

Since the bulk of my main site was a blog, the top trafficked and top linked-to pages fortunately correlated pretty well. Again, this is only a way to prioritize. If you’re dealing with sites with thousands of pages, you need to work methodically through the site architecture.

I’m going to say something that makes some SEOs itchy – it’s ok not to move some pages to the new site. It’s even ok to let some pages 404. In Q4, UserEffect.com had traffic to 237 URLs. The top 10 pages accounted for 91.9% of that traffic. I strongly believe that moving domains is a good time to refocus a site and concentrate your visitors and link equity on your best content. More is not better in 2015.

Letting go of some pages also means that you’re not 301-redirecting a massive number of old URLs to a new home-page. This can look like a low-quality attempt to consolidate link-equity, and at large scale it can raise red flags with Google. Content worth keeping should exist on the new site, and your 301s should have well-matched targets.

In one case, I had a blog post that had a decent trickle of traffic due to ranking for “50,000 push-ups,” but the post itself was weak and the bounce rate was very high:

The post was basically just a placeholder announcing that I’d be attempting this challenge, but I never recapped anything after finishing it. So, in this case,
I rewrote the post.

Of course, this process was repeated across the 3 active sites. The 2 inactive sites only constituted a handful of total pages. In the case of AreYouARealDoctor.com, I decided to turn the previous one-pager
into a new page on the new site. That way, I had a very well-matched target for the 301-redirect, instead of simply mapping the old site to my new home-page.

I’m trying to prove a point – this is the amount of work I did for a handful of sites that were mostly inactive and producing no current business value. I don’t need consulting gigs and these sites produce no direct revenue, and yet I still considered this process worth the effort.

Step 2 – The Big Day

Eventually, you’re going to have to make the move, and in most cases, I prefer ripping off the bandage. Of course, doing something all at once doesn’t mean you shouldn’t be careful.

The biggest problem I see with domain switches (even if they’re 1-to-1) is that people rely on data that can take weeks to evaluate, like rankings and traffic, or directly checking Google’s index. By then, a lot of damage is already done. Here are some ways to find out quickly if you’ve got problems…

(1) Manually Check Pages

Remember that list you were supposed to make? It’s time to check it, or at least spot-check it. Someone needs to physically go to a browser and make sure that each major section of the site and each important individual page is resolving properly. It doesn’t matter how confident your IT department/guy/gal is – things go wrong.

(2) Manually Check Headers

Just because a page resolves, it doesn’t mean that your 301-redirects are working properly, or that you’re not firing some kind of 17-step redirect chain. Check your headers. There are tons of free tools, but lately I’m fond of
URI Valet. Guess what – I screwed up my primary 301-redirects. One of my registrar transfers wasn’t working, so I had to have a setting changed by customer service, and I inadvertently ended up with 302s (Pro tip: Don’t change registrars and domains in one step):

Don’t think that because you’re an “expert”, your plan is foolproof. Mistakes happen, and because I caught this one I was able to correct it fairly quickly.

(3) Submit Your New Site

You don’t need to submit your site to Google in 2015, but now that Google Webmaster Tools allows it, why not do it? The primary argument I hear is “well, it’s not necessary.” True, but direct submission has one advantage – it’s fast.

To be precise, Google Webmaster Tools separates the process into “Fetch” and “Submit to index” (you’ll find this under “Crawl” > “Fetch as Google”). Fetching will quickly tell you if Google can resolve a URL and retrieve the page contents, which alone is pretty useful. Once a page is fetched, you can submit it, and you should see something like this:

This isn’t really about getting indexed – it’s about getting nearly instantaneous feedback. If Google has any major problems with crawling your site, you’ll know quickly, at least at the macro level.

(4) Submit New XML Sitemaps

Finally, submit a new set of XML sitemaps in Google Webmaster Tools, and preferably tiered sitemaps. While it’s a few years old now, Rob Ousbey has a great post on the subject of
XML sitemap structure. The basic idea is that, if you divide your sitemap into logical sections, it’s going to be much easier to diagnosis what kinds of pages Google is indexing and where you’re running into trouble.

A couple of pro tips on sitemaps – first, keep your old sitemaps active temporarily. This is counterintuitive to some people, but unless Google can crawl your old URLs, they won’t see and process the 301-redirects and other signals. Let the old accounts stay open for a couple of months, and don’t cut off access to the domains you’re moving.

Second (I learned this one the hard way), make sure that your Google Webmaster Tools site verification still works. If you use file uploads or meta tags and don’t move those files/tags to the new site, GWT verification will fail and you won’t have access to your old accounts. I’d recommend using a more domain-independent solution, like verifying with Google Analytics. If you lose verification, don’t panic – your data won’t be instantly lost.

Step 3 – The Waiting Game

Once you’ve made the switch, the waiting begins, and this is where many people start to panic. Even executed perfectly, it can take Google weeks or even months to process all of your 301-redirects and reevaluate a new domain’s capacity to rank. You have to expect short term fluctuations in ranking and traffic.

During this period, you’ll want to watch a few things – your traffic, your rankings, your indexed pages (via GWT and the site: operator), and your errors (such as unexpected 404s). Traffic will recover the fastest, since direct traffic is immediately carried through redirects, but ranking and indexation will lag, and errors may take time to appear.

(1) Monitor Traffic

I’m hoping you know how to check your traffic, but actually trying to determine what your new levels should be and comparing any two days can be easier said than done. If you launch on a Friday, and then Saturday your traffic goes down on the new site, that’s hardly cause for panic – your traffic probably
always goes down on Saturday.

In this case, I redirected the individual sites over about a week, but I’m going to focus on UserEffect.com, as that was the major traffic generator. That site was redirected, in full on January 21st, and the Google Analytics data for January for the old site looked like this:

So far, so good – traffic bottomed out almost immediately. Of course, losing traffic is easy – the real question is what’s going on with the new domain. Here’s the graph for January for DrPete.co:

This one’s a bit trickier – the first spike, on January 16th, is when I redirected the first domain. The second spike, on January 22nd, is when I redirected UserEffect.com. Both spikes are meaningless – I announced these re-launches on social media and got a short-term traffic burst. What we really want to know is where traffic is leveling out.

Of course, there isn’t a lot of history here, but a typical day for UserEffect.com in January was about 1,000 pageviews. The traffic to DrPete.co after it leveled out was about half that (500 pageviews). It’s not a complete crisis, but we’re definitely looking at a short-term loss.

Obviously, I’m simplifying the process here – for a large, ecommerce site you’d want to track a wide range of metrics, including conversion metrics. Hopefully, though, this illustrates the core approach. So, what am I missing out on? In this day of [not provided], tracking down a loss can be tricky. Let’s look for clues in our other three areas…

(2) Monitor Indexation

You can get a broad sense of your indexed pages from Google Webmaster Tools, but this data often lags real-time and isn’t very granular. Despite its shortcomings, I still prefer
the site: operator. Generally, I monitor a domain daily – any one measurement has a lot of noise, but what you’re looking for is the trend over time. Here’s the indexed page count for DrPete.co:

The first set of pages was indexed fairly quickly, and then the second set started being indexed soon after UserEffect.com was redirected. All in all, we’re seeing a fairly steady upward trend, and that’s what we’re hoping to see. The number is also in the ballpark of sanity (compared to the actual page count) and roughly matched GWT data once it started being reported.

So, what happened to UserEffect.com’s index after the switch?

The timeframe here is shorter, since UserEffect.com was redirected last, but we see a gradual decline in indexation, as expected. Note that the index size plateaus around 60 pages – about 1/4 of the original size. This isn’t abnormal – low-traffic and unlinked pages (or those with deep links) are going to take a while to clear out. This is a long-term process. Don’t panic over the absolute numbers – what you want here is a downward trend on the old domain accompanied by a roughly equal upward trend on the new domain.

The fact that UserEffect.com didn’t bottom out is definitely worth monitoring, but this timespan is too short for the plateau to be a major concern. The next step would be to dig into these specific pages and look for a pattern.

(3) Monitor Rankings

The old domain is dropping out of the index, and the new domain is taking its place, but we still don’t know why the new site is taking a traffic hit. It’s time to dig into our core keyword rankings.

Historically, UserEffect.com had ranked well for keywords related to “split test calculator” (near #1) and “usability checklist” (in the top 3). While [not provided] makes keyword-level traffic analysis tricky, we also know that the split-test calculator is one of the top trafficked pages on the site, so let’s dig into that one. Here’s the ranking data from Moz Analytics for “split test calculator”:

The new site took over the #1 position from the old site at first, but then quickly dropped down to the #3/#4 ranking. That may not sound like a lot, but given this general keyword category was one of the site’s top traffic drivers, the CTR drop from #1 to #3/#4 could definitely be causing problems.

When you have a specific keyword you can diagnose, it’s worth taking a look at the live SERP, just to get some context. The day after relaunch, I captured this result for “dr. pete”:

Here, the new domain is ranking, but it’s showing the old title tag. This may not be cause for alarm – weird things often happen in the very short term – but in this case we know that I accidentally set up a 302-redirect. There’s some reason to believe that Google didn’t pass full link equity during that period when 301s weren’t implemented.

Let’s look at a domain where the 301s behaved properly. Before the site was inactive, AreYouARealDoctor.com ranked #1 for “are you a real doctor”. Since there was an inactive period, and I dropped the exact-match domain, it wouldn’t be surprising to see a corresponding ranking drop.

In reality, the new site was ranking #1 for “are you a real doctor” within 2 weeks of 301-redirecting the old domain. The graph is just a horizontal line at #1, so I’m not going to bother you with it, but here’s a current screenshot (incognito):

Early on, I also spot-checked this result, and it wasn’t showing the strange title tag crossover that UserEffect.com pages exhibited. So, it’s very likely that the 302-redirects caused some problems.

Of course, these are just a couple of keywords, but I hope it provides a starting point for you to understand how to methodically approach this problem. There’s no use crying over spilled milk, and I’m not going to fire myself, so let’s move on to checking any other errors that I might have missed.

(4) Check Errors (404s, etc.)

A good first stop for unexpected errors is the “Crawl Errors” report in Google Webmaster Tools (Crawl > Crawl Errors). This is going to take some digging, especially if you’ve deliberately 404’ed some content. Over the couple of weeks after re-launch, I spotted the following problems:

The old site had a “/blog” directory, but the new site put the blog right on the home-page and had no corresponding directory. Doh. Hey, do as I say, not as I do, ok? Obviously, this was a big blunder, as the old blog home-page was well-trafficked.

The other two errors here are smaller but easy to correct. MinimalTalent.com had a “/free” directory that housed downloads (mostly PDFs). I missed it, since my other sites used a different format. Luckily, this was easy to remap.

The last error is a weird looking URL, and there are other similar URLs in the 404 list. This is where site knowledge is critical. I custom-designed a URL shortener for UserEffect.com and, in some cases, people linked to those URLs. Since those URLs didn’t exist in the site architecture, I missed them. This is where digging deep into historical traffic reports and your top-linked pages is critical. In this case, the fix isn’t easy, and I have to decide whether the loss is worth the time.

What About the New EMD?

My goal here wasn’t to rank better for “Dr. Pete,” and finally unseat Dr. Pete’s Marinades, Dr. Pete the Sodastream flavor (yes, it’s hilarious – you can stop sending me your grocery store photos), and 172 dentists. Ok, it mostly wasn’t my goal. Of course, you might be wondering how switching to an EMD worked out.

In the short term, I’m afraid the answer is “not very well.” I didn’t track ranking for “Dr. Pete” and related phrases very often before the switch, but it appears that ranking actually fell in the short-term. Current estimates have me sitting around page 4, even though my combined link profile suggests a much stronger position. Here’s a look at the ranking history for “dr pete” since relaunch (from Moz Analytics):

There was an initial drop, after which the site evened out a bit. This less-than-impressive plateau could be due to the bad 302s during transition. It could be Google evaluating a new EMD and multiple redirects to that EMD. It could be that the prevalence of natural anchor text with “Dr. Pete” pointing to my site suddenly looked unnatural when my domain name switched to DrPete.co. It could just be that this is going to take time to shake out.

If there’s a lesson here (and, admittedly, it’s too soon to tell), it’s that you shouldn’t rush to buy an EMD in 2015 in the wild hope of instantly ranking for that target phrase. There are so many factors involved in ranking for even a moderately competitive term, and your domain is just one small part of the mix.

So, What Did We Learn?

I hope you learned that I should’ve taken my own advice and planned a bit more carefully. I admit that this was a side project and it didn’t get the attention it deserved. The problem is that, even when real money is at stake, people rush these things and hope for the best. There’s a real cheerleading mentality when it comes to change – people want to take action and only see the upside.

Ultimately, in a corporate or agency environment, you can’t be the one sour note among the cheering. You’ll be ignored, and possibly even fired. That’s not fair, but it’s reality. What you need to do is make sure the work gets done right and people go into the process with eyes wide open. There’s no room for shortcuts when you’re moving to a new domain.

That said, a domain change isn’t a death sentence, either. Done right, and with sensible goals in mind – balancing not just SEO but broader marketing and business objectives – a domain migration can be successful, even across multiple sites.

To sum up: Plan, plan, plan, monitor, monitor, monitor, and try not to panic.

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Reblogged 4 years ago from tracking.feedpress.it

What Deep Learning and Machine Learning Mean For the Future of SEO – Whiteboard Friday

Posted by randfish

Imagine a world where even the high-up Google engineers don’t know what’s in the ranking algorithm. We may be moving in that direction. In today’s Whiteboard Friday, Rand explores and explains the concepts of deep learning and machine learning, drawing us a picture of how they could impact our work as SEOs.

For reference, here’s a still of this week’s whiteboard!

Video transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we are going to take a peek into Google’s future and look at what it could mean as Google advances their machine learning and deep learning capabilities. I know these sound like big, fancy, important words. They’re not actually that tough of topics to understand. In fact, they’re simplistic enough that even a lot of technology firms like Moz do some level of machine learning. We don’t do anything with deep learning and a lot of neural networks. We might be going that direction.

But I found an article that was published in January, absolutely fascinating and I think really worth reading, and I wanted to extract some of the contents here for Whiteboard Friday because I do think this is tactically and strategically important to understand for SEOs and really important for us to understand so that we can explain to our bosses, our teams, our clients how SEO works and will work in the future.

The article is called “Google Search Will Be Your Next Brain.” It’s by Steve Levy. It’s over on Medium. I do encourage you to read it. It’s a relatively lengthy read, but just a fascinating one if you’re interested in search. It starts with a profile of Geoff Hinton, who was a professor in Canada and worked on neural networks for a long time and then came over to Google and is now a distinguished engineer there. As the article says, a quote from the article: “He is versed in the black art of organizing several layers of artificial neurons so that the entire system, the system of neurons, could be trained or even train itself to divine coherence from random inputs.”

This sounds complex, but basically what we’re saying is we’re trying to get machines to come up with outcomes on their own rather than us having to tell them all the inputs to consider and how to process those incomes and the outcome to spit out. So this is essentially machine learning. Google has used this, for example, to figure out when you give it a bunch of photos and it can say, “Oh, this is a landscape photo. Oh, this is an outdoor photo. Oh, this is a photo of a person.” Have you ever had that creepy experience where you upload a photo to Facebook or to Google+ and they say, “Is this your friend so and so?” And you’re like, “God, that’s a terrible shot of my friend. You can barely see most of his face, and he’s wearing glasses which he usually never wears. How in the world could Google+ or Facebook figure out that this is this person?”

That’s what they use, these neural networks, these deep machine learning processes for. So I’ll give you a simple example. Here at MOZ, we do machine learning very simplistically for page authority and domain authority. We take all the inputs — numbers of links, number of linking root domains, every single metric that you could get from MOZ on the page level, on the sub-domain level, on the root-domain level, all these metrics — and then we combine them together and we say, “Hey machine, we want you to build us the algorithm that best correlates with how Google ranks pages, and here’s a bunch of pages that Google has ranked.” I think we use a base set of 10,000, and we do it about quarterly or every 6 months, feed that back into the system and the system pumps out the little algorithm that says, “Here you go. This will give you the best correlating metric with how Google ranks pages.” That’s how you get page authority domain authority.

Cool, really useful, helpful for us to say like, “Okay, this page is probably considered a little more important than this page by Google, and this one a lot more important.” Very cool. But it’s not a particularly advanced system. The more advanced system is to have these kinds of neural nets in layers. So you have a set of networks, and these neural networks, by the way, they’re designed to replicate nodes in the human brain, which is in my opinion a little creepy, but don’t worry. The article does talk about how there’s a board of scientists who make sure Terminator 2 doesn’t happen, or Terminator 1 for that matter. Apparently, no one’s stopping Terminator 4 from happening? That’s the new one that’s coming out.

So one layer of the neural net will identify features. Another layer of the neural net might classify the types of features that are coming in. Imagine this for search results. Search results are coming in, and Google’s looking at the features of all the websites and web pages, your websites and pages, to try and consider like, “What are the elements I could pull out from there?”

Well, there’s the link data about it, and there are things that happen on the page. There are user interactions and all sorts of stuff. Then we’re going to classify types of pages, types of searches, and then we’re going to extract the features or metrics that predict the desired result, that a user gets a search result they really like. We have an algorithm that can consistently produce those, and then neural networks are hopefully designed — that’s what Geoff Hinton has been working on — to train themselves to get better. So it’s not like with PA and DA, our data scientist Matt Peters and his team looking at it and going, “I bet we could make this better by doing this.”

This is standing back and the guys at Google just going, “All right machine, you learn.” They figure it out. It’s kind of creepy, right?

In the original system, you needed those people, these individuals here to feed the inputs, to say like, “This is what you can consider, system, and the features that we want you to extract from it.”

Then unsupervised learning, which is kind of this next step, the system figures it out. So this takes us to some interesting places. Imagine the Google algorithm, circa 2005. You had basically a bunch of things in here. Maybe you’d have anchor text, PageRank and you’d have some measure of authority on a domain level. Maybe there are people who are tossing new stuff in there like, “Hey algorithm, let’s consider the location of the searcher. Hey algorithm, let’s consider some user and usage data.” They’re tossing new things into the bucket that the algorithm might consider, and then they’re measuring it, seeing if it improves.

But you get to the algorithm today, and gosh there are going to be a lot of things in there that are driven by machine learning, if not deep learning yet. So there are derivatives of all of these metrics. There are conglomerations of them. There are extracted pieces like, “Hey, we only ant to look and measure anchor text on these types of results when we also see that the anchor text matches up to the search queries that have previously been performed by people who also search for this.” What does that even mean? But that’s what the algorithm is designed to do. The machine learning system figures out things that humans would never extract, metrics that we would never even create from the inputs that they can see.

Then, over time, the idea is that in the future even the inputs aren’t given by human beings. The machine is getting to figure this stuff out itself. That’s weird. That means that if you were to ask a Google engineer in a world where deep learning controls the ranking algorithm, if you were to ask the people who designed the ranking system, “Hey, does it matter if I get more links,” they might be like, “Well, maybe.” But they don’t know, because they don’t know what’s in this algorithm. Only the machine knows, and the machine can’t even really explain it. You could go take a snapshot and look at it, but (a) it’s constantly evolving, and (b) a lot of these metrics are going to be weird conglomerations and derivatives of a bunch of metrics mashed together and torn apart and considered only when certain criteria are fulfilled. Yikes.

So what does that mean for SEOs. Like what do we have to care about from all of these systems and this evolution and this move towards deep learning, which by the way that’s what Jeff Dean, who is, I think, a senior fellow over at Google, he’s the dude that everyone mocks for being the world’s smartest computer scientist over there, and Jeff Dean has basically said, “Hey, we want to put this into search. It’s not there yet, but we want to take these models, these things that Hinton has built, and we want to put them into search.” That for SEOs in the future is going to mean much less distinct universal ranking inputs, ranking factors. We won’t really have ranking factors in the way that we know them today. It won’t be like, “Well, they have more anchor text and so they rank higher.” That might be something we’d still look at and we’d say, “Hey, they have this anchor text. Maybe that’s correlated with what the machine is finding, the system is finding to be useful, and that’s still something I want to care about to a certain extent.”

But we’re going to have to consider those things a lot more seriously. We’re going to have to take another look at them and decide and determine whether the things that we thought were ranking factors still are when the neural network system takes over. It also is going to mean something that I think many, many SEOs have been predicting for a long time and have been working towards, which is more success for websites that satisfy searchers. If the output is successful searches, and that’ s what the system is looking for, and that’s what it’s trying to correlate all its metrics to, if you produce something that means more successful searches for Google searchers when they get to your site, and you ranking in the top means Google searchers are happier, well you know what? The algorithm will catch up to you. That’s kind of a nice thing. It does mean a lot less info from Google about how they rank results.

So today you might hear from someone at Google, “Well, page speed is a very small ranking factor.” In the future they might be, “Well, page speed is like all ranking factors, totally unknown to us.” Because the machine might say, “Well yeah, page speed as a distinct metric, one that a Google engineer could actually look at, looks very small.” But derivatives of things that are connected to page speed may be huge inputs. Maybe page speed is something, that across all of these, is very well connected with happier searchers and successful search results. Weird things that we never thought of before might be connected with them as the machine learning system tries to build all those correlations, and that means potentially many more inputs into the ranking algorithm, things that we would never consider today, things we might consider wholly illogical, like, “What servers do you run on?” Well, that seems ridiculous. Why would Google ever grade you on that?

If human beings are putting factors into the algorithm, they never would. But the neural network doesn’t care. It doesn’t care. It’s a honey badger. It doesn’t care what inputs it collects. It only cares about successful searches, and so if it turns out that Ubuntu is poorly correlated with successful search results, too bad.

This world is not here yet today, but certainly there are elements of it. Google has talked about how Panda and Penguin are based off of machine learning systems like this. I think, given what Geoff Hinton and Jeff Dean are working on at Google, it sounds like this will be making its way more seriously into search and therefore it’s something that we’re really going to have to consider as search marketers.

All right everyone, I hope you’ll join me again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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Reblogged 4 years ago from tracking.feedpress.it

International SEO Study: How Searchers Perceive Country Code Top-Level Domains

Posted by 5le

The decision to focus your site on an international audience is a big step and one fraught with complexities. There are, of course, issues to deal with around language and user experience, but in addition there are some big technical choices to make including what domains to use.

Any authoritative
international SEO guide will elaborate on the differences between the options of subdirectory, subdomain, and country-code top level domain (CCTLD). One of the most common suggestions is for a site to opt to use a ccTLD (e.g. domain.co.uk) as the domain extension. The reasoning behind this is the theory that the ccTLD extension will “hint” to search engines and users exactly who your target audience should be versus the other, less explicit options. For example, a search engine and human user would know, even without clicking into a site, that a site that ends with .co.uk is targeting a user looking for UK content. 

We have solid data from
Google that a ccTLD does indicate country targeting; however, when it comes to users there is only an assumption that users even notice and make choices based on the ccTLD. However, this is a fairly broad assumption that doesn’t address whether a ccTLD is more important than a brand name in the domain or the quality of a website’s content. To test this theory, we ran a survey to discover what users really thought.

User knowledge of TLDs

Even before trying to understand how users related to ccTLDs it is essential to validate the assumption that users even know that general TLDs exist. To establish this fact, we asked respondents to pick which TLD might be the one in use by a non-profit. Close to
100% of respondents correctly identified a TLD ending with .org as the one most likely to be used by a non-profit. Interestingly, only 4% of people in the US stated that they were unsure of the correct TLD compared to 13% of Australians. Predictably, nearly all marketers (98%) chose the .org answer.

Another popular TLD is the .edu in use by educational assumptions, and we wanted to understand if users thought that content coming from a .edu domain might be more trustworthy. We asked users if they received an unsolicited email about water quality in their town whether they would place more trust in a sender’s email address that ended with .edu or .com.
89% of respondents in the US chose the .edu as more trustworthy, while only 79% said the same in Australia. Quite interestingly, the marketer responses (from the survey posted on Inbound.org were exactly the same as the Australians with 79% declaring the .edu to be more trustworthy.

.org cctld survey australia

If users can identify a .org as the correct TLD for a non-profit, and a .edu as a TLD that might be more trustworthy, it is likely that users are familiar with the existence of TLDs and how they might be used. The next question to answer is if users are aware of the connection between TLDs and locations.

Country relationship awareness

Next, we asked respondents to identify the location of a local business using a .ca TLD extension. The majority of respondents across all three surveys correctly chose Canada; and nearly all marketers (92%) got this correct. Oddly, more Australians (67%) correctly identified Canada than Americans (62%). We would have thought Americans should have been more familiar with the TLD of a neighboring country. Additionally, more Americans (23%) fell for the trick answer of California than Australians (15%). Regardless, we were able to conclude that most Internet users are aware of TLDs and that they are tied to a specific country.

canada cctld survey

To really gauge how much users know about TLDs and countries, we asked users to pick the right domain extension for a website in another country. In the US survey, we asked users to pick the correct TLD for an Australian company, and in the Australian survey we used a British company. In each of the questions we gave one correct answer possibility, one almost correct, and two entire wrong choices.For example, we gave .co.uk and .uk as answer choices to Australians.

In both the US and Australia, the majority of respondents chose the correct TLD, although Americans seem to have been confused by whether Australia’s TLD was .AU (35%) or .com.AU (24%).

There is a common practice of using country-code domain extensions as a vanity URL for content that is not geotargeted. For example, .ly is the domain extension for Libya, but it is frequently used on domains that have a word that ends with “ly.” Additionally, .me is the domain extension for Montenegro; however, the TLD is used for many purposes other than Montenegro content.

We wanted to understand if users noticed this type of TLD usage or if they thought the content might still be related to another country. We asked respondents what might be on a website that ended with .TV which is the TLD for the island nation of Tuvalu and is also a popular TLD for TV show websites. 51% of US respondents thought it might be a TV show and 42% chose the “it could be anything” answer. In Australia, 43% thought the site would be a TV show, and 44% said “it could be anything”.

tuvalu cctld survey

One of the answer options was that it could be a website in Tuvalu and interestingly twice as many Australian (9%) chose this option vs US respondents (4.5%). This question was one of the areas where marketers’ answers were very different from those in the US and Australia. 77% of marketers chose the TV show option and only 19% said it could be anything.

Based on the these three results, it is apparent that
users recognize TLDs, know that they are from other countries, and appear to make some judgments around the content based on the TLD.

Decision making using TLDs

Since users know that TLDs are an important part of a URL that is tied to a country of origin, it is important to understand how the TLD factors into their decision-making processes about whether or not they visit certain websites.

We asked users whether they thought medical content on a foreign TLD would be as reliable as similar content found on their local TLD. In the US, only 24% thought the content on the non-local TLD (.co.uk) was less reliable than content on a .com. In Australia, the results were nearly identical to what we saw in the US with only 28% answering that the non-local TLD (.co.uk) was less reliable than the content on a .com.au. Even 24% of marketers answered that the content was less reliable. The remaining respondents chose either that the content equally reliable or they just didn’t know. Based on these results, the TLD (at least as long as it was a reputable one)
does not seem to impact user trust.

UK cctld survey

Digging into the idea of trust and TLD a bit further, we asked the same reliability question about results on Google.com vs Google.de. In the US, 56% of respondents said that the results on Google.de are equally reliable to those on Google.com, and in Australia, 51% said the same thing when compared to Google.com.au. In the marketer survey, 66% of respondents said the results were equally reliable. The fact that the majority of respondents stated that results are equally reliable should mean that users are more focused on the brand portion of a domain rather than its country extension.

CcTLD’s impact on ecommerce

Making the decision to use a ccTLD on a website can be costly, so it is important to justify this cost with an actual revenue benefit. Therefore the real test of TLD choice is how it impacts revenue. This type of answer is of course hard to gauge in a survey where customers are not actually buying products, but we did want to try to see if there might be a way to measure purchasing decisions.

To achieve this result, we compared two different online retailers and asked respondents to choose the establishment that they thought would have the most reliable express shipping. In the US survey, we compared Amazon.co.jp to BestBuy.com. In the Australian survey, we compared Bigw.com.au (a well known online retailer) to Target.com. (Interesting fact: there is a Target in Australia that is not affiliated with Target in the US and their website is target.com.au) The intent of the question was to see if users zeroed in on the recognizable brand name or the domain extension.

cctld trust survey

In the US, while 39% said that both websites would offer reliable shipping, 42% still said that Best Buy would be the better option. Australians may have been confused by the incorrect Target website, since 61% said both websites would have reliable shipping, but 34% chose Big W. Even marketers didn’t seem oblivious to domain names with only 34% choosing the equally reliable option, and 49% choosing Best Buy. The data in this question is a bit inconclusive, but we can definitively say that while a large portion of users are blind to domain names, however, when selling online it would be best to use a familiar domain extension.

cctld trust survey australia

New TLDs

Late last year, ICANN (the Internet governing body) announced that they would be releasing dozens of new
GTLDs, which opened up a new domain name land grab harkening back to the early days of the Internet. Many of these domain names can be quite expensive, and we wanted to discover whether they even mattered to users.

gtld survey

We asked users if, based solely on the domain name, they were more likely to trust an insurance quote from a website ending in .insurance.
62% of Americans, 53% of Australians, and 67% of marketers said they were unlikely to trust the quote based on the domain alone. Based on this result, if you’re looking to invest in a new TLD simply to drive more conversions, you should probably do more research first. 

A new gTLD is probably not a silver bullet.

Methodology

For this survey, I collaborated with
Sam Mallikarjunan at HubSpot and we decided that the two assumptions we absolutely needed to validate where 1) whether users even notice ccTLDs and 2) if so do they really prefer the TLD of their country. While we received 101 responses from a version of the survey targeted at marketers on an Inbound.org discussion, we primarily used SurveyMonkey Audience, which allowed us to get answers from a statistically significant random selection of people in both the United States and Australia.

We created two nearly identical surveys with one targeted to a US-only audience and the other targeted to an Australian-only audience. A proper sample set is essential when conducting any survey that attempts to draw conclusions about people’s general behavior and preferences. And in this case, the minimum number of respondents we needed in order to capture a representative example was 350 for the U.S. and 300 for Australia.

Additionally, in order for a sample to be valid, the respondents have to be chosen completely at random. SurveyMonkey Audience recruits its 4-million+ members from SurveyMonkey’s 40 million annual unique visitors, and members are not paid for their participation. Instead, they are rewarded for taking surveys with charitable donations, made on their behalf by SurveyMonkey.

When tested against much larger research projects, Audience data has been exactly in line with larger sample sizes. For example, an Audience survey with just 400 respondents about a new Lay’s potato chip flavor had the same results as a wider contest that had 3 million participants.

SurveyMonkey’s survey research team was also able to use SurveyMonkey Audience to accurately predict election results in both 2012 and 2013. With a US sample size of 458 respondents and an Australian one of 312 all drawn at random, our ccTLD user preferences should reliably mirror the actual reality.

Summary

There will be many reasons that you may or may not want to use ccTLDs for your website, and a survey alone can never answer whether a ccTLD is the right strategy for any particular site. If you are thinking about making any big decisions about TLDs on your site, you should absolutely conduct some testing or surveying of your own before relying on just the recommendations of those who advise a TLD as the best strategy or the others that tell you it doesn’t matter at all.

Launching a PPC campaign with a landing page on a ccTLD and measuring CTRs against a control is far cheaper than replicating your entire site on a new TLD.

Based on our survey results, here’s what you should keep in mind when it comes to whether or not investing your time and money in a ccTLD is worth it:

  1. Users are absolutely aware of the TLDs and how they might relate to the contents of a website
  2. Users are aware of the connection between TLDs and countries
  3. Users do make decisions about websites based on the TLD; however there are no absolutes. Brand and content absolutely matter.

As to whether a ccTLD will work for you on your own site, give it a try and report back!

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Reblogged 4 years ago from moz.com

Back to Fundamentals: 6 Untapped Keyword Sources that Will Boost Organic Traffic

Posted by neilpatel

I used to perform keyword research in the typical, perfunctory way—go to the Keyword Tool, type in some words, and punch out a list of terms.

Easy. Quick. Simple.

Today, things are different. The much-loved
keyword tool has been replaced, long-tail keywords have the ascendancy, and it’s harder to figure out what users are actually searching for.

The rules have changed, and so have the ways of playing the game. I still use the
Keyword Planner, but I’ve also discovered a medley of not-so-obvious ways to get keywords that improve my organic traffic.

1. Wikipedia

Do you think of Wikipedia as just a massive encyclopedia? Think again.
I use Wikipedia for keyword research.

Image from Search Engine Journal.

My process is pretty simple.

Step 1: Google inurl:Wikipedia and my topic. Or just Google the topic or head term. Wikipedia is often the first organic result.

Step 2: Look at the SERP to identify the most relevant terms and possible keywords within a Wikipedia entry.

Step 3: Open the entry in Wikipedia and identify the most relevant terms from the first few paragraphs, morphing them into longail iterations.

Step 4: Identify other relevant terms from Wikipedia’s table of contents on the topic.

Step 5: Link to other associated Wikipedia to see related subjects, and identify even more keywords.

Wikipedia is the world’s
sixth most popular website, and ranks it at number #4 on Google’s list. It boasts 310,000,000 unique visitors (20% of its traffic), and has 7,900,000,000 pageviews. All of this with absolutely no advertising.

In other words, Wikipedia has one of the best organic SEO strategies on the planet. Obviously, these are keywords that matter. Wikipedia’s popularity shows us that people want information. It’s like the greatest content marketing strategy ever, combining user-generated content with prolific publishing on a grand scale.

Do what Wikipedia does. Use the terms that people search for. You won’t outrank Wikipedia, but you will start to rank organically for the longtail varieties that you discern from Wikipedia.

2. Google autocomplete

When you type stuff into Google’s search bar, Google predicts your query and types it out for you. The feature has been around
for a long time. The more time that goes by, the more intelligent the autocomplete algorithm becomes.

These autocomplete suggestions are all based on real user queries. They vary based on geographic location and language. However, in spite of the variation, autocomplete provides a fairly accurate representation of what people are looking for.

Here is why autocomplete is a killer source of keywords:

Step 1: It indicates some of the most popular keywords.

Step 2: It provides longtail suggestions.

Step 3: The keywords are ranked according to the “freshness layer” algorithm. That means that currently popular search terms will rank higher in the autocomplete list.

How do you use autocomplete for keyword research? Well, you can go about this the good old-fashioned spade and shovel way, like this:

Google 2014-08-11 13-50-24

Step 4: Open Google. To prevent Google from autocompleting previously-searched for terms, log out of Google or open an “incognito” window (Chrome: Shift + Cmnd + N).

Step 5: Type in your main keyword or longtail keyword E.g. “lawnmower.”

Step 6: Write down the suggestions that appear in autocomplete.

Step 7: After you type in your main keyword or head term, type in “A” and write down the autocomplete suggestions.

Step 8: Repeat Step 7 for rest of the alphabet.

Or, you can do it the easy way, with Übersuggest. It’s called”suggest on steroids.” It will do all the work for you. The only downside is that it doesn’t suggest keyword extensions based on search popularity.

Keyword suggestion tool — Google suggest scraper — Übersuggest 2014-08-11 13-53-48

If you can get past the eye-popping UI, Übersuggest is a pretty awesome tool.

Keep in mind that Google is not going to provide suggestions for everything.
As quoted in Search Engine Land, here is what the algorithm will filter out:

  • Hate- or violence-related suggestions
  • Personally identifiable information in suggestions
  • Porn & adult content-related suggestions
  • Legally mandated removals
  • Piracy-related suggestions

3. Google Related Searches

Since Google is the biggest search engine, we’ve got to take our cues from its mighty algorithm, imperfect and agonizing though it may be.

Google’s related searches is a really easy way to snag some instant keyword research.


Step 1:
Search for your keyword in Google.


Step 2:
Scroll to the bottom, and ignore everything in between.

There, at the bottom is a harvest of keywords, ripe for the selection:

lawn mower - Google Search 2014-08-11 14-05-22

The idea is similar to Google suggest. However, instead of providing autocomplete suggestions, Google takes the keyword and mixes it up with other words. These other words may be at the end, at the beginning, or sprinkled throughout. These related searches might not even include the actual keyword, but are simply connected in a tangential way.

Whatever the case, you will undoubtedly find some keyword ideas from this list.

4. MetaGlossary.com

Not a whole lot of people know about MetaGlossary.com. You won’t find a lot of information about the company itself, but you will find a ton of keyword ideas.

Here are the instructions. Not too hard.

MetaGlossary.com 2014-08-11 14-53-43

The whole point of the glossary is to provide definitions. But along with the many definitions, you’ll get “related terms.” That’s what we’re looking for.

When I type in “Search Engine Optimization,” my head term, here’s what I get:

Metaglossary.com - Definitions for "search engine optimization" 2014-08-11 14-56-26

All of those are potential keywords.

I can take this a step further by looking through the definitions. These can provide even more keyword fodder:

Metaglossary.com - Definitions for "search engine optimization" 2014-08-11 14-57-28

For this particular term, I found 117 definitions. That’s enough to keep me busy for a while.

5. Competitor keywords

Another great way to get keyword ideas is to snag them from the competition.

Not only are you going to identify some great keywords, but you’ll be able to gain these keywords ideas from the top-ranking organic sites in the SERPs.

Here’s how to do it.

Step 1: Google your top keyword.

Step 2: Click the first organic result.

Step 3: View the page source (Chrome: Cmnd + Alt + u)

Step 4: Search for “<Title>”. Identify any non-branded terms as possible keywords.

Step 5: Search for “<h1>”. Identify any potential keywords in the H1 text.

Step 6: Search for “<keywords>”. Identify any potential keywords that they have identified as such. Some websites have this, such as specific WordPress themed sites, or WP sites using an SEO plugin. Most websites don’t.

Step 7: Look at all the content and locate any additional longtail keywords or keyword variations.

The competitors that are first in the SERP for a given head term or longtail query are ranking high for a variety of reasons. One of those reasons is their keyword selection. Sure, they may have good link profiles, but you can’t rank for a keyword unless you actually have that keyword (or some variation thereof) on your page.

6. Amazon.com

Amazon.com is king of the ecommerce jungle, no questions asked.

Part of their power is that they have total domination of the organic search results for just about any purchase-related keyword. When your audience circles closer to a transactional search query, Amazon is ranking somewhere.

Why? They’ve got keywords—lots of them. And they have reviews—lots of them. This means one thing for you: Lots of keywords ideas.

Let me make a quick clarification. Not everyone is going to find keyword ideas on Amazon. This works best if you have a physical products, and obviously only if Amazon sells it.

Here’s how to skim the cream off of Amazon’s great keywords.

Step 1: Google your keyword.

Step 2: Locate the Amazon entry in the SERP.

Step 3: Click on the result to see the product/landing page on Google.

Step 4: Locate keywords in the following places.

-“Show results for” menu

-Main header

-Text underneath main header

-“## Results for” text.

-Breadcrumb

-Items listed

Here’s a quick survey of where you can find these keywords. Notice the highlighted text.

Amazon.com: Bags & Cases: Electronics: Sleeves & Slipcases, Messenger Bags, Shoulder Bags, Backpacks & More 2014-08-11 14-28-16

You’ll find even more keywords once you dive into individual products.

Pay special attention to these areas on product pages:

-“Customers Who Bought This Item Also Bought”

-“Product Description”

-“Product Ads from External Websites”

-“Customer Questions & Answers.” You’ll find some nice query-like longtail keywords here.

-“Customer Reviews.” Again, this is a great source of longtails.

Let Amazon be your guide. They’re the biggest e-retailer around, and they have some great keyword clout going for them.

Conclusion

Keyword research is a basic skill for any SEO. The actual process of finding those keywords, however, does not require expensive tools, formula-driven methods, or an extremely limited pool of options.

I’ve used each of these methods for myself and my clients with incredible success.


What is your favorite source for finding great keywords? 

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Reblogged 5 years ago from feedproxy.google.com