Should I Use Relative or Absolute URLs? – Whiteboard Friday

Posted by RuthBurrReedy

It was once commonplace for developers to code relative URLs into a site. There are a number of reasons why that might not be the best idea for SEO, and in today’s Whiteboard Friday, Ruth Burr Reedy is here to tell you all about why.

For reference, here’s a still of this week’s whiteboard. Click on it to open a high resolution image in a new tab!

Let’s discuss some non-philosophical absolutes and relatives

Howdy, Moz fans. My name is Ruth Burr Reedy. You may recognize me from such projects as when I used to be the Head of SEO at Moz. I’m now the Senior SEO Manager at BigWing Interactive in Oklahoma City. Today we’re going to talk about relative versus absolute URLs and why they are important.

At any given time, your website can have several different configurations that might be causing duplicate content issues. You could have just a standard http://www.example.com. That’s a pretty standard format for a website.

But the main sources that we see of domain level duplicate content are when the non-www.example.com does not redirect to the www or vice-versa, and when the HTTPS versions of your URLs are not forced to resolve to HTTP versions or, again, vice-versa. What this can mean is if all of these scenarios are true, if all four of these URLs resolve without being forced to resolve to a canonical version, you can, in essence, have four versions of your website out on the Internet. This may or may not be a problem.

It’s not ideal for a couple of reasons. Number one, duplicate content is a problem because some people think that duplicate content is going to give you a penalty. Duplicate content is not going to get your website penalized in the same way that you might see a spammy link penalty from Penguin. There’s no actual penalty involved. You won’t be punished for having duplicate content.

The problem with duplicate content is that you’re basically relying on Google to figure out what the real version of your website is. Google is seeing the URL from all four versions of your website. They’re going to try to figure out which URL is the real URL and just rank that one. The problem with that is you’re basically leaving that decision up to Google when it’s something that you could take control of for yourself.

There are a couple of other reasons that we’ll go into a little bit later for why duplicate content can be a problem. But in short, duplicate content is no good.

However, just having these URLs not resolve to each other may or may not be a huge problem. When it really becomes a serious issue is when that problem is combined with injudicious use of relative URLs in internal links. So let’s talk a little bit about the difference between a relative URL and an absolute URL when it comes to internal linking.

With an absolute URL, you are putting the entire web address of the page that you are linking to in the link. You’re putting your full domain, everything in the link, including /page. That’s an absolute URL.

However, when coding a website, it’s a fairly common web development practice to instead code internal links with what’s called a relative URL. A relative URL is just /page. Basically what that does is it relies on your browser to understand, “Okay, this link is pointing to a page that’s on the same domain that we’re already on. I’m just going to assume that that is the case and go there.”

There are a couple of really good reasons to code relative URLs

1) It is much easier and faster to code.

When you are a web developer and you’re building a site and there thousands of pages, coding relative versus absolute URLs is a way to be more efficient. You’ll see it happen a lot.

2) Staging environments

Another reason why you might see relative versus absolute URLs is some content management systems — and SharePoint is a great example of this — have a staging environment that’s on its own domain. Instead of being example.com, it will be examplestaging.com. The entire website will basically be replicated on that staging domain. Having relative versus absolute URLs means that the same website can exist on staging and on production, or the live accessible version of your website, without having to go back in and recode all of those URLs. Again, it’s more efficient for your web development team. Those are really perfectly valid reasons to do those things. So don’t yell at your web dev team if they’ve coded relative URLS, because from their perspective it is a better solution.

Relative URLs will also cause your page to load slightly faster. However, in my experience, the SEO benefits of having absolute versus relative URLs in your website far outweigh the teeny-tiny bit longer that it will take the page to load. It’s very negligible. If you have a really, really long page load time, there’s going to be a whole boatload of things that you can change that will make a bigger difference than coding your URLs as relative versus absolute.

Page load time, in my opinion, not a concern here. However, it is something that your web dev team may bring up with you when you try to address with them the fact that, from an SEO perspective, coding your website with relative versus absolute URLs, especially in the nav, is not a good solution.

There are even better reasons to use absolute URLs

1) Scrapers

If you have all of your internal links as relative URLs, it would be very, very, very easy for a scraper to simply scrape your whole website and put it up on a new domain, and the whole website would just work. That sucks for you, and it’s great for that scraper. But unless you are out there doing public services for scrapers, for some reason, that’s probably not something that you want happening with your beautiful, hardworking, handcrafted website. That’s one reason. There is a scraper risk.

2) Preventing duplicate content issues

But the other reason why it’s very important to have absolute versus relative URLs is that it really mitigates the duplicate content risk that can be presented when you don’t have all of these versions of your website resolving to one version. Google could potentially enter your site on any one of these four pages, which they’re the same page to you. They’re four different pages to Google. They’re the same domain to you. They are four different domains to Google.

But they could enter your site, and if all of your URLs are relative, they can then crawl and index your entire domain using whatever format these are. Whereas if you have absolute links coded, even if Google enters your site on www. and that resolves, once they crawl to another page, that you’ve got coded without the www., all of that other internal link juice and all of the other pages on your website, Google is not going to assume that those live at the www. version. That really cuts down on different versions of each page of your website. If you have relative URLs throughout, you basically have four different websites if you haven’t fixed this problem.

Again, it’s not always a huge issue. Duplicate content, it’s not ideal. However, Google has gotten pretty good at figuring out what the real version of your website is.

You do want to think about internal linking, when you’re thinking about this. If you have basically four different versions of any URL that anybody could just copy and paste when they want to link to you or when they want to share something that you’ve built, you’re diluting your internal links by four, which is not great. You basically would have to build four times as many links in order to get the same authority. So that’s one reason.

3) Crawl Budget

The other reason why it’s pretty important not to do is because of crawl budget. I’m going to point it out like this instead.

When we talk about crawl budget, basically what that is, is every time Google crawls your website, there is a finite depth that they will. There’s a finite number of URLs that they will crawl and then they decide, “Okay, I’m done.” That’s based on a few different things. Your site authority is one of them. Your actual PageRank, not toolbar PageRank, but how good Google actually thinks your website is, is a big part of that. But also how complex your site is, how often it’s updated, things like that are also going to contribute to how often and how deep Google is going to crawl your site.

It’s important to remember when we think about crawl budget that, for Google, crawl budget cost actual dollars. One of Google’s biggest expenditures as a company is the money and the bandwidth it takes to crawl and index the Web. All of that energy that’s going into crawling and indexing the Web, that lives on servers. That bandwidth comes from servers, and that means that using bandwidth cost Google actual real dollars.

So Google is incentivized to crawl as efficiently as possible, because when they crawl inefficiently, it cost them money. If your site is not efficient to crawl, Google is going to save itself some money by crawling it less frequently and crawling to a fewer number of pages per crawl. That can mean that if you have a site that’s updated frequently, your site may not be updating in the index as frequently as you’re updating it. It may also mean that Google, while it’s crawling and indexing, may be crawling and indexing a version of your website that isn’t the version that you really want it to crawl and index.

So having four different versions of your website, all of which are completely crawlable to the last page, because you’ve got relative URLs and you haven’t fixed this duplicate content problem, means that Google has to spend four times as much money in order to really crawl and understand your website. Over time they’re going to do that less and less frequently, especially if you don’t have a really high authority website. If you’re a small website, if you’re just starting out, if you’ve only got a medium number of inbound links, over time you’re going to see your crawl rate and frequency impacted, and that’s bad. We don’t want that. We want Google to come back all the time, see all our pages. They’re beautiful. Put them up in the index. Rank them well. That’s what we want. So that’s what we should do.

There are couple of ways to fix your relative versus absolute URLs problem

1) Fix what is happening on the server side of your website

You have to make sure that you are forcing all of these different versions of your domain to resolve to one version of your domain. For me, I’m pretty agnostic as to which version you pick. You should probably already have a pretty good idea of which version of your website is the real version, whether that’s www, non-www, HTTPS, or HTTP. From my view, what’s most important is that all four of these versions resolve to one version.

From an SEO standpoint, there is evidence to suggest and Google has certainly said that HTTPS is a little bit better than HTTP. From a URL length perspective, I like to not have the www. in there because it doesn’t really do anything. It just makes your URLs four characters longer. If you don’t know which one to pick, I would pick one this one HTTPS, no W’s. But whichever one you pick, what’s really most important is that all of them resolve to one version. You can do that on the server side, and that’s usually pretty easy for your dev team to fix once you tell them that it needs to happen.

2) Fix your internal links

Great. So you fixed it on your server side. Now you need to fix your internal links, and you need to recode them for being relative to being absolute. This is something that your dev team is not going to want to do because it is time consuming and, from a web dev perspective, not that important. However, you should use resources like this Whiteboard Friday to explain to them, from an SEO perspective, both from the scraper risk and from a duplicate content standpoint, having those absolute URLs is a high priority and something that should get done.

You’ll need to fix those, especially in your navigational elements. But once you’ve got your nav fixed, also pull out your database or run a Screaming Frog crawl or however you want to discover internal links that aren’t part of your nav, and make sure you’re updating those to be absolute as well.

Then you’ll do some education with everybody who touches your website saying, “Hey, when you link internally, make sure you’re using the absolute URL and make sure it’s in our preferred format,” because that’s really going to give you the most bang for your buck per internal link. So do some education. Fix your internal links.

Sometimes your dev team going to say, “No, we can’t do that. We’re not going to recode the whole nav. It’s not a good use of our time,” and sometimes they are right. The dev team has more important things to do. That’s okay.

3) Canonicalize it!

If you can’t get your internal links fixed or if they’re not going to get fixed anytime in the near future, a stopgap or a Band-Aid that you can kind of put on this problem is to canonicalize all of your pages. As you’re changing your server to force all of these different versions of your domain to resolve to one, at the same time you should be implementing the canonical tag on all of the pages of your website to self-canonize. On every page, you have a canonical page tag saying, “This page right here that they were already on is the canonical version of this page. ” Or if there’s another page that’s the canonical version, then obviously you point to that instead.

But having each page self-canonicalize will mitigate both the risk of duplicate content internally and some of the risk posed by scrappers, because when they scrape, if they are scraping your website and slapping it up somewhere else, those canonical tags will often stay in place, and that lets Google know this is not the real version of the website.

In conclusion, relative links, not as good. Absolute links, those are the way to go. Make sure that you’re fixing these very common domain level duplicate content problems. If your dev team tries to tell you that they don’t want to do this, just tell them I sent you. Thanks guys.

Video transcription by Speechpad.com

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Deconstructing the App Store Rankings Formula with a Little Mad Science

Posted by AlexApptentive

After seeing Rand’s “Mad Science Experiments in SEO” presented at last year’s MozCon, I was inspired to put on the lab coat and goggles and do a few experiments of my own—not in SEO, but in SEO’s up-and-coming younger sister, ASO (app store optimization).

Working with Apptentive to guide enterprise apps and small startup apps alike to increase their discoverability in the app stores, I’ve learned a thing or two about app store optimization and what goes into an app’s ranking. It’s been my personal goal for some time now to pull back the curtains on Google and Apple. Yet, the deeper into the rabbit hole I go, the more untested assumptions I leave in my way.

Hence, I thought it was due time to put some longstanding hypotheses through the gauntlet.

As SEOs, we know how much of an impact a single ranking can mean on a SERP. One tiny rank up or down can make all the difference when it comes to your website’s traffic—and revenue.

In the world of apps, ranking is just as important when it comes to standing out in a sea of more than 1.3 million apps. Apptentive’s recent mobile consumer survey shed a little more light this claim, revealing that nearly half of all mobile app users identified browsing the app store charts and search results (the placement on either of which depends on rankings) as a preferred method for finding new apps in the app stores. Simply put, better rankings mean more downloads and easier discovery.

Like Google and Bing, the two leading app stores (the Apple App Store and Google Play) have a complex and highly guarded algorithms for determining rankings for both keyword-based app store searches and composite top charts.

Unlike SEO, however, very little research and theory has been conducted around what goes into these rankings.

Until now, that is.

Over the course of five studies analyzing various publicly available data points for a cross-section of the top 500 iOS (U.S. Apple App Store) and the top 500 Android (U.S. Google Play) apps, I’ll attempt to set the record straight with a little myth-busting around ASO. In the process, I hope to assess and quantify any perceived correlations between app store ranks, ranking volatility, and a few of the factors commonly thought of as influential to an app’s ranking.

But first, a little context

Image credit: Josh Tuininga, Apptentive

Both the Apple App Store and Google Play have roughly 1.3 million apps each, and both stores feature a similar breakdown by app category. Apps ranking in the two stores should, theoretically, be on a fairly level playing field in terms of search volume and competition.

Of these apps, nearly two-thirds have not received a single rating and 99% are considered unprofitable. These studies, therefore, single out the rare exceptions to the rule—the top 500 ranked apps in each store.

While neither Apple nor Google have revealed specifics about how they calculate search rankings, it is generally accepted that both app store algorithms factor in:

  • Average app store rating
  • Rating/review volume
  • Download and install counts
  • Uninstalls (what retention and churn look like for the app)
  • App usage statistics (how engaged an app’s users are and how frequently they launch the app)
  • Growth trends weighted toward recency (how daily download counts changed over time and how today’s ratings compare to last week’s)
  • Keyword density of the app’s landing page (Ian did a great job covering this factor in a previous Moz post)

I’ve simplified this formula to a function highlighting the four elements with sufficient data (or at least proxy data) for our analysis:

Ranking = fn(Rating, Rating Count, Installs, Trends)

Of course, right now, this generalized function doesn’t say much. Over the next five studies, however, we’ll revisit this function before ultimately attempting to compare the weights of each of these four variables on app store rankings.

(For the purpose of brevity, I’ll stop here with the assumptions, but I’ve gone into far greater depth into how I’ve reached these conclusions in a 55-page report on app store rankings.)

Now, for the Mad Science.

Study #1: App-les to app-les app store ranking volatility

The first, and most straight forward of the five studies involves tracking daily movement in app store rankings across iOS and Android versions of the same apps to determine any trends of differences between ranking volatility in the two stores.

I went with a small sample of five apps for this study, the only criteria for which were that:

  • They were all apps I actively use (a criterion for coming up with the five apps but not one that influences rank in the U.S. app stores)
  • They were ranked in the top 500 (but not the top 25, as I assumed app store rankings would be stickier at the top—an assumption I’ll test in study #2)
  • They had an almost identical version of the app in both Google Play and the App Store, meaning they should (theoretically) rank similarly
  • They covered a spectrum of app categories

The apps I ultimately chose were Lyft, Venmo, Duolingo, Chase Mobile, and LinkedIn. These five apps represent the travel, finance, education banking, and social networking categories.

Hypothesis

Going into this analysis, I predicted slightly more volatility in Apple App Store rankings, based on two statistics:

Both of these assumptions will be tested in later analysis.

Results

7-Day App Store Ranking Volatility in the App Store and Google Play

Among these five apps, Google Play rankings were, indeed, significantly less volatile than App Store rankings. Among the 35 data points recorded, rankings within Google Play moved by as much as 23 positions/ranks per day while App Store rankings moved up to 89 positions/ranks. The standard deviation of ranking volatility in the App Store was, furthermore, 4.45 times greater than that of Google Play.

Of course, the same apps varied fairly dramatically in their rankings in the two app stores, so I then standardized the ranking volatility in terms of percent change to control for the effect of numeric rank on volatility. When cast in this light, App Store rankings changed by as much as 72% within a 24-hour period while Google Play rankings changed by no more than 9%.

Also of note, daily rankings tended to move in the same direction across the two app stores approximately two-thirds of the time, suggesting that the two stores, and their customers, may have more in common than we think.

Study #2: App store ranking volatility across the top charts

Testing the assumption implicit in standardizing the data in study No. 1, this one was designed to see if app store ranking volatility is correlated with an app’s current rank. The sample for this study consisted of the top 500 ranked apps in both Google Play and the App Store, with special attention given to those on both ends of the spectrum (ranks 1–100 and 401–500).

Hypothesis

I anticipated rankings to be more volatile the higher an app is ranked—meaning an app ranked No. 450 should be able to move more ranks in any given day than an app ranked No. 50. This hypothesis is based on the assumption that higher ranked apps have more installs, active users, and ratings, and that it would take a large margin to produce a noticeable shift in any of these factors.

Results

App Store Ranking Volatility of Top 500 Apps

One look at the chart above shows that apps in both stores have increasingly more volatile rankings (based on how many ranks they moved in the last 24 hours) the lower on the list they’re ranked.

This is particularly true when comparing either end of the spectrum—with a seemingly straight volatility line among Google Play’s Top 100 apps and very few blips within the App Store’s Top 100. Compare this section to the lower end, ranks 401–)500, where both stores experience much more turbulence in their rankings. Across the gamut, I found a 24% correlation between rank and ranking volatility in the Play Store and 28% correlation in the App Store.

To put this into perspective, the average app in Google Play’s 401–)500 ranks moved 12.1 ranks in the last 24 hours while the average app in the Top 100 moved a mere 1.4 ranks. For the App Store, these numbers were 64.28 and 11.26, making slightly lower-ranked apps more than five times as volatile as the highest ranked apps. (I say slightly as these “lower-ranked” apps are still ranked higher than 99.96% of all apps.)

The relationship between rank and volatility is pretty consistent across the App Store charts, while rank has a much greater impact on volatility at the lower end of Google Play charts (ranks 1-100 have a 35% correlation) than it does at the upper end (ranks 401-500 have a 1% correlation).

Study #3: App store rankings across the stars

The next study looks at the relationship between rank and star ratings to determine any trends that set the top chart apps apart from the rest and explore any ties to app store ranking volatility.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

As discussed in the introduction, this study relates directly to one of the factors commonly accepted as influential to app store rankings: average rating.

Getting started, I hypothesized that higher ranks generally correspond to higher ratings, cementing the role of star ratings in the ranking algorithm.

As far as volatility goes, I did not anticipate average rating to play a role in app store ranking volatility, as I saw no reason for higher rated apps to be less volatile than lower rated apps, or vice versa. Instead, I believed volatility to be tied to rating volume (as we’ll explore in our last study).

Results

Average App Store Ratings of Top Apps

The chart above plots the top 100 ranked apps in either store with their average rating (both historic and current, for App Store apps). If it looks a little chaotic, it’s just one indicator of the complexity of ranking algorithm in Google Play and the App Store.

If our hypothesis was correct, we’d see a downward trend in ratings. We’d expect to see the No. 1 ranked app with a significantly higher rating than the No. 100 ranked app. Yet, in neither store is this the case. Instead, we get a seemingly random plot with no obvious trends that jump off the chart.

A closer examination, in tandem with what we already know about the app stores, reveals two other interesting points:

  1. The average star rating of the top 100 apps is significantly higher than that of the average app. Across the top charts, the average rating of a top 100 Android app was 4.319 and the average top iOS app was 3.935. These ratings are 0.32 and 0.27 points, respectively, above the average rating of all rated apps in either store. The averages across apps in the 401–)500 ranks approximately split the difference between the ratings of the top ranked apps and the ratings of the average app.
  2. The rating distribution of top apps in Google Play was considerably more compact than the distribution of top iOS apps. The standard deviation of ratings in the Apple App Store top chart was over 2.5 times greater than that of the Google Play top chart, likely meaning that ratings are more heavily weighted in Google Play’s algorithm.

App Store Ranking Volatility and Average Rating

Looking next at the relationship between ratings and app store ranking volatility reveals a -15% correlation that is consistent across both app stores; meaning the higher an app is rated, the less its rank it likely to move in a 24-hour period. The exception to this rule is the Apple App Store’s calculation of an app’s current rating, for which I did not find a statistically significant correlation.

Study #4: App store rankings across versions

This next study looks at the relationship between the age of an app’s current version, its rank and its ranking volatility.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

In alteration of the above function, I’m using the age of a current app’s version as a proxy (albeit not a very good one) for trends in app store ratings and app quality over time.

Making the assumptions that (a) apps that are updated more frequently are of higher quality and (b) each new update inspires a new wave of installs and ratings, I’m hypothesizing that the older the age of an app’s current version, the lower it will be ranked and the less volatile its rank will be.

Results

How update frequency correlates with app store rank

The first and possibly most important finding is that apps across the top charts in both Google Play and the App Store are updated remarkably often as compared to the average app.

At the time of conducting the study, the current version of the average iOS app on the top chart was only 28 days old; the current version of the average Android app was 38 days old.

As hypothesized, the age of the current version is negatively correlated with the app’s rank, with a 13% correlation in Google Play and a 10% correlation in the App Store.

How update frequency correlates with app store ranking volatility

The next part of the study maps the age of the current app version to its app store ranking volatility, finding that recently updated Android apps have less volatile rankings (correlation: 8.7%) while recently updated iOS apps have more volatile rankings (correlation: -3%).

Study #5: App store rankings across monthly active users

In the final study, I wanted to examine the role of an app’s popularity on its ranking. In an ideal world, popularity would be measured by an app’s monthly active users (MAUs), but since few mobile app developers have released this information, I’ve settled for two publicly available proxies: Rating Count and Installs.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

For the same reasons indicated in the second study, I anticipated that more popular apps (e.g., apps with more ratings and more installs) would be higher ranked and less volatile in rank. This, again, takes into consideration that it takes more of a shift to produce a noticeable impact in average rating or any of the other commonly accepted influencers of an app’s ranking.

Results

Apps with more ratings and reviews typically rank higher

The first finding leaps straight off of the chart above: Android apps have been rated more times than iOS apps, 15.8x more, in fact.

The average app in Google Play’s Top 100 had a whopping 3.1 million ratings while the average app in the Apple App Store’s Top 100 had 196,000 ratings. In contrast, apps in the 401–)500 ranks (still tremendously successful apps in the 99.96 percentile of all apps) tended to have between one-tenth (Android) and one-fifth (iOS) of the ratings count as that of those apps in the top 100 ranks.

Considering that almost two-thirds of apps don’t have a single rating, reaching rating counts this high is a huge feat, and a very strong indicator of the influence of rating count in the app store ranking algorithms.

To even out the playing field a bit and help us visualize any correlation between ratings and rankings (and to give more credit to the still-staggering 196k ratings for the average top ranked iOS app), I’ve applied a logarithmic scale to the chart above:

The relationship between app store ratings and rankings in the top 100 apps

From this chart, we can see a correlation between ratings and rankings, such that apps with more ratings tend to rank higher. This equates to a 29% correlation in the App Store and a 40% correlation in Google Play.

Apps with more ratings typically experience less app store ranking volatility

Next up, I looked at how ratings count influenced app store ranking volatility, finding that apps with more ratings had less volatile rankings in the Apple App Store (correlation: 17%). No conclusive evidence was found within the Top 100 Google Play apps.

Apps with more installs and active users tend to rank higher in the app stores

And last but not least, I looked at install counts as an additional proxy for MAUs. (Sadly, this is a statistic only listed in Google Play. so any resulting conclusions are applicable only to Android apps.)

Among the top 100 Android apps, this last study found that installs were heavily correlated with ranks (correlation: -35.5%), meaning that apps with more installs are likely to rank higher in Google Play. Android apps with more installs also tended to have less volatile app store rankings, with a correlation of -16.5%.

Unfortunately, these numbers are slightly skewed as Google Play only provides install counts in broad ranges (e.g., 500k–)1M). For each app, I took the low end of the range, meaning we can likely expect the correlation to be a little stronger since the low end was further away from the midpoint for apps with more installs.

Summary

To make a long post ever so slightly shorter, here are the nuts and bolts unearthed in these five mad science studies in app store optimization:

  1. Across the top charts, Apple App Store rankings are 4.45x more volatile than those of Google Play
  2. Rankings become increasingly volatile the lower an app is ranked. This is particularly true across the Apple App Store’s top charts.
  3. In both stores, higher ranked apps tend to have an app store ratings count that far exceeds that of the average app.
  4. Ratings appear to matter more to the Google Play algorithm, especially as the Apple App Store top charts experience a much wider ratings distribution than that of Google Play’s top charts.
  5. The higher an app is rated, the less volatile its rankings are.
  6. The 100 highest ranked apps in either store are updated much more frequently than the average app, and apps with older current versions are correlated with lower ratings.
  7. An app’s update frequency is negatively correlated with Google Play’s ranking volatility but positively correlated with ranking volatility in the App Store. This likely due to how Apple weighs an app’s most recent ratings and reviews.
  8. The highest ranked Google Play apps receive, on average, 15.8x more ratings than the highest ranked App Store apps.
  9. In both stores, apps that fall under the 401–500 ranks receive, on average, 10–20% of the rating volume seen by apps in the top 100.
  10. Rating volume and, by extension, installs or MAUs, is perhaps the best indicator of ranks, with a 29–40% correlation between the two.

Revisiting our first (albeit oversimplified) guess at the app stores’ ranking algorithm gives us this loosely defined function:

Ranking = fn(Rating, Rating Count, Installs, Trends)

I’d now re-write the function into a formula by weighing each of these four factors, where a, b, c, & d are unknown multipliers, or weights:

Ranking = (Rating * a) + (Rating Count * b) + (Installs * c) + (Trends * d)

These five studies on ASO shed a little more light on these multipliers, showing Rating Count to have the strongest correlation with rank, followed closely by Installs, in either app store.

It’s with the other two factors—rating and trends—that the two stores show the greatest discrepancy. I’d hazard a guess to say that the App Store prioritizes growth trends over ratings, given the importance it places on an app’s current version and the wide distribution of ratings across the top charts. Google Play, on the other hand, seems to favor ratings, with an unwritten rule that apps just about have to have at least four stars to make the top 100 ranks.

Thus, we conclude our mad science with this final glimpse into what it takes to make the top charts in either store:

Weight of factors in the Apple App Store ranking algorithm

Rating Count > Installs > Trends > Rating

Weight of factors in the Google Play ranking algorithm

Rating Count > Installs > Rating > Trends


Again, we’re oversimplifying for the sake of keeping this post to a mere 3,000 words, but additional factors including keyword density and in-app engagement statistics continue to be strong indicators of ranks. They simply lie outside the scope of these studies.

I hope you found this deep-dive both helpful and interesting. Moving forward, I also hope to see ASOs conducting the same experiments that have brought SEO to the center stage, and encourage you to enhance or refute these findings with your own ASO mad science experiments.

Please share your thoughts in the comments below, and let’s deconstruct the ranking formula together, one experiment at a time.

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Reblogged 4 years ago from tracking.feedpress.it

Give It Up for Our MozCon 2015 Community Speakers

Posted by EricaMcGillivray

Super thrilled that we’re able to announce this year’s community speakers for MozCon, July 13-15th in Seattle!

Wow. Each year I feel that I say the pool keeps getting more and more talented, but it’s the truth! We had more quality pitches this year than in the past, and quantity-wise, there were 241, around 100 more entries than years previously. Let me tell you, many of the review committee members filled our email thread with amazement at this.

And even though we had an unprecedented six slots, the choices seemed even tougher!

241 pitches
Let that number sink in for a little while.

Because we get numerous questions about what makes a great pitch, I wanted to share both information about the speakers and their great pitches—with some details removed for spoilers. (We’re still working with each speaker to polish and finalize their topic.) I’ve also included my or Matt Roney‘s own notes on each one from when we read them without knowing who the authors were.

Please congratulate our MozCon 2015 community speakers!

Adrian Vender

Adrian is the Director of Analytics at IMI and a general enthusiast of coding and digital marketing. He’s also a life-long drummer and lover of music. Follow him at @adrianvender.

Adrian’s pitch:

Content Tracking with Google Tag Manager

While marketers have matured in the use of web analytics tools, our ability to measure how users interact with our sites’ content needs improvement. Users are interacting with dynamic content that just aren’t captured in a pageview. While there are JavaScript tricks to help track these details, working with IT to place new code is usually the major hurdle that stops us.

Finally, Google Tag Manager is that bridge to advanced content analysis. GTM may appear technical, but it can easily be used by any digital marketer to track almost any action on a site. My goal is to make ALL attendees users of GTM.

My talk will cover the following GTM concepts:

[Adrian lists 8 highly-actionable tactics he’ll cover.]

I’ll share a client example of tracking content interaction in GA. I’ll also share a link to a GTM container file that can help people pre-load the above tag templates into their own GTM.

Matt’s notes: Could be good. I know a lot of people have questions about Tag Manager, and the ubiquity of GA should help it be pretty well-received.


Chris DayleyChris Dayley

Chris is a digital marketing expert and owner of Dayley Conversion. His company provides full-service A/B testing for businesses, including design, development, and test execution. Follow him at @chrisdayley.

Chris’ pitch:

I would like to present a super actionable 15 minute presentation focused on the first two major steps businesses should take to start A/B testing:

1. Radical Redesign Testing

2. Iterative Testing (Test EVERYTHING)

I am one of the few CROs out there that recommends businesses to start with a radical redesign test. My reasoning for doing so is that most businesses have done absolutely no testing on their current website, so the current landing page/website really isn’t a “best practice” design yet.

I will show several case studies where clients saw more than a 50% lift in conversion rates just from this first step of radical redesign testing, and will offer several tips for how to create a radical redesign test. Some of the tips include:

[Chris lists three direct and interesting tips he’ll share.]

Next I suggest moving into the iterative phase.

I will show several case studies of how to move through iterative testing so you eventually test every element on your page.

Erica’s notes: Direct, interesting, and with promise of multiple case studies.


Duane BrownDuane Brown

Duane is a digital marketer with 10 years’ experience having lived and worked in five cities across three continents. He’s currently at Unbounce. When not working, you can find Duane traveling to some far-flung location around the world to eat food and soak up the culture. Follow him at @DuaneBrown.

Duane’s pitch:

What Is Delightful Remarketing & How You Can Do It Too

A lot of people find remarketing creepy and weird. They don’t get why they are seeing those ads around the internet…. let alone how to make them stop showing.

This talk will focus on the different between remarketing & creating delightful remarketing that can help grow the revenue & profit at a company and not piss customers off. 50% of US marketers don’t use remarketing according to eMarketer (2013).

– [Duane’s direct how-to for e-commerce customers.] Over 60% of customers abandon a shopping cart each year: http://baymard.com/lists/cart-abandonment-rate (3 minute)

– Cover a SaaS company using retargeting to [Duane’s actionable item]. This remarketing helps show your products sticky features while showing off your benefits (3 minute)

– The Dos: [Duane’s actionable tip], a variety of creative & a dedicated landing page creates delightful remarketing that grows revenue (3 minute)

– Wrap up and review main points. (2 minutes)

Matt’s notes: Well-detailed, an area in which there’s a lot of room for improvement.


Gianluca FiorelliGianluca Fiorelli

Moz Associate, official blogger for StateofDigital.com and known international SEO and inbound strategist, Gianluca works in the digital marketing industry, but he still believes that he just know that he knows nothing. Follow him at @gfiorelli1.

Gianluca’s pitch:

Unusual Sources for Keyword and Topical Research

A big percentage of SEOs equal Keyword and Topical Research to using Keyword Planner and Google Suggest.

However, using only them, we cannot achieve a real deep knowledge of the interests, psychology and language of our target.

In this talk, I will present unusual sources and unnoticed features of very well-known tools, and offer a final example based on a true story.

Arguments touched in the speech (not necessarily in this order):

[Gianluca lists seven how-tos and one unique case study.]

Erica’s notes: Theme of Google not giving good keyword info. Lots of unique actionable points and resources. Will work in 15 minute time limit.


Ruth Burr ReedyRuth Burr Reedy

Ruth is the head of on-site SEO for BigWing Interactive, a full-service digital marketing agency in Oklahoma City, OK. At BigWing, she manages a team doing on-site, technical, and local SEO. Ruth has been working in SEO since 2006. Follow her at @ruthburr.

Ruth’s pitch:

Get Hired to Do SEO

This talk will go way beyond “just build your own website” and talk about specific ways SEOs can build evidence of their skills across the web, including:

[Ruth lists 7 how-tos with actionable examples.]

All in a funny, actionable, beautiful, easy-to-understand get-hired masterpiece.

Erica’s notes: Great takeaways. Wanted to do a session about building your resume as a marketer for a while.


Stephanie WallaceStephanie Wallace

Stephanie is director of SEO at Nebo, a digital agency in Atlanta. She helps clients navigate the ever-changing world of SEO by understanding their audience and helping them create a digital experience that both the user and Google appreciates. Follow her at @SWallaceSEO.

Stephanie’s pitch:

Everyone knows PPC and SEO complement one another – increased visibility in search results help increase perceived authority and drive more clickthroughs to your site overall. But are you actively leveraging the wealth of PPC data available to build on your existing SEO strategy? The key to effectively using this information lies in understanding how to test SEO tactics and how to apply the results to your on-page strategies. This session will delve into actionable strategies for using PPC campaign insights to influence on-page SEO and content strategies. Key takeaways include:

[Stephanie lists four how-tos.]

Erica’s notes: Nice and actionable. Like this a lot.


As mentioned, we had 241 entries, and many of them were stage quality. Notable runners up included AJ Wilcox, Ed Reese, and Daylan Pearce, and a big pat on the back to all those who tossed their hat in.

Also, a huge thank you to my fellow selection committee members for 2015: Charlene Inoncillo, Cyrus Shepard, Danie Launders, Jen Lopez, Matt Roney, Rand Fishkin, Renea Nielsen, and Trevor Klein.

Buy your ticket now

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Reblogged 4 years ago from tracking.feedpress.it

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

Are On-Topic Links Important? – Whiteboard Friday

Posted by randfish

How much does the context of a link really matter? In today’s Whiteboard Friday, Rand looks at on- and off-topic links to uncover what packs the greatest SEO punch and shares what you should be looking for when building a high-quality link.

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

On-Topic Links Whiteboard

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re going to chat a little bit about on-topic and off-topic links. One of the questions and one of the topics that you see discussed all the time in the SEO world is: Do on-topic links matter more than off-topic links? By on topic, people generally mean they come from sites and pages that are on the same or very similar subject matter to the site or page that I’m trying to get the link to.

It sort of makes intuitive sense to us that Google would care somewhat about this, that they would say, “Oh, well, here’s our friend over here,” we’ll call him Steve. No we’re going to call him Carl, because Carl is a great name.

Carl, of course, has CarlsCloset.net, CarlsCloset.net being a home organization site. Carl is going out, and he’s doing some link building, which he should, and so he’s got some link targets in mind. He looks at places like RealSimple.com, the magazine site, Sunset Magazine, UnderwaterHoagies.com, Carl being a great fan of all things underwater and sandwich related. So as he’s looking at these sites, he’s thinking to himself, well, from an SEO perspective, is it necessary the case that Real Simple, which has a lot of content on home organization and on cleaning up clutter and those kinds of things, is that going to help Carl’s Closet site rank better than, say, a link from UnderwaterHoagies.com?

The answer is a little tough here. It could be the case that UnderwaterHoagies.com has a feature article all about how submariners can keep their home in order, even as they brunch under the sea. But maybe the link from RealSimple.com is coming from a less on-topic article and page. So this starts to get really messy. Is it the site that matters, or is it the page that matters? Is it the context that matters? Is it the link itself and where that’s embedded in the site? What is the real understanding that Google has between relationships of on-topic and off-topic? That’s where you get a lot of convoluted information.

I have seen and we have probably all heard a ton of anecdotal evidence on both sides. There are SEOs who will argue passionately from their experience that what they’ve seen is that on-topic links are hugely more beneficial than off-topic ones. You’ll see the complete opposite from some other folks. In fact, most of my personal experiences, when I was doing more directed link building for clients way back in my SEO consulting days and even more recently as I’ve helped startups and advised folks, has been that off-topic links, UnderwaterHoagies.com linking to Carl’s Closet, that still seems to provide quite a bit of benefit, and it’s very had to gauge whether it’s as much, less than, more than any of these other ones. So I think, on the anecdotal side, we’re in a tough spot.

What we can say is that probably there’s some additional value from on-topic sites, on-topic pages, or on-topic link connections, that Google has some idea of context. We’ve seen them make huge strides with algorithms like Hummingbird, certainly with their keyword matching and topic modeling algorithms. It seems very unlikely that there would be nothing in Google’s algorithm that looks at the context or relationship of content between linking pages and linking websites.

However, in the real world, things are almost never equal. It’s not like they’re going to get exactly the same anchor text from the same importance of a page that has the same number of external links, that the content is exactly the same on all three of these websites pointing over to Carl’s Closet. In the real world, Carl is going to struggle much harder to get some of these links than others. So I think that the questions we need to ask ourselves, as folks who are doing directed marketing and trying to earn links, is: Will the link actually help people? Is that link going to be clicked?

If you’re on a page on Real Simple that you think very few people ever reach, you think very few people will ever click that link because it just doesn’t appear to provide much value, versus you’re in an article all about home organization on Underwater Hoagies, and it was featured on their home page, and you’re pretty sure that a lot of the submariners who are eating their subs under the sea are very interested in this topic and they’re going to click on that link, well you know what? That’s a link that helps people. That probably means search engines are going to treat it with some reverence as well.

Does the link make sense in context? This is a good one to ask yourself when you are doing any kind of link building that’s directed that could potentially be manipulative. If the link makes sense in context, it tends to be the case that it’s going to be more useful. So if Carl contributes the article to UnderwaterHoagies.com, and the link makes sense in context, and it will help people, I think it’s appropriate to put it there. If that’s not the case, it could look a little manipulative. It could certainly be perceived as self-serving.

Then, can you actually acquire the link? It’s wonderful when you go out and you make a list of, hey, here’s the most important and relevant sites in our sector and niche, and this is how we’re going to build topical authority. But if you can’t get those links, hey that’s tough potatoes, man. It’s no better than putting a list of links and just sorting them by, God knows, a horrible metric like PageRank or Alexa rank or something like that.

I would instead ask yourself if it’s realistic for you to be able to get those links and pursue those as well as pursuing or looking at the metrics, and the importance, and the topical relevance.

Let’s think about this from a broad perspective. Search engines are caring about what? They’re caring about matching the content relevance to the searcher’s query. They care about raw link popularity. That’s sort of like the old-school algorithms of PageRank and number of links and that kind of thing. They do care about topical authority and brand authority. We talked about on Whiteboard Friday previously around some topical authorities and how Google determines the authority and the subject matter of a site’s authority. They care about domain authority, the raw importance of a domain on the web, and they care about things like engagement, user and usage data, and given how much they can follow all of us around the web these days, they probably know pretty well whether people are clicking on these articles using these pages or not.

Then anchor text. Not every link that you might build or acquire or earn is going to provide all of these in one single package. Each of them are going to be contributing pieces of those puzzles. When it comes to the on-topic/off-topic link debate, I’m much more about caring about the answers to these kinds of questions — Can I acquire the link? Is it useful to people? Will they actually use it? Does the link make sense in context? — than I am about is it on-topic or off-topic? I’m not sure that I would ever urge you to prioritize based on that.

That said, I’m certainly looking forward to your feedback this week and hearing about your experiences with on-topic and off-topic links, and hopefully we’ll see you again next week for another edition of Whiteboard Friday. Take care.

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