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Announcing Moz Academy!

Posted by Nick_Sayers

We’re stoked to announce Moz Academy!

Have you ever wanted a resource to learn inbound marketing or a place your team can reference marketing best practices? Well, we hope you do a backflip over Moz Academy. If you have a Moz Subscription, check it out now!

Moz Academy

Subscription-based content

At Moz we produce a wealth of free content in the blog, our guides, Q&A, and pretty much everywhere on the site. We want to do something special for Moz subscribers by transforming our free content and reinventing it for Moz Academy. You could probably scour the Moz Blog and other websites to obtain the information in Moz Academy, but we think having it easily digestible and all in one place is a huge win for Moz subscribers. Moz is excited to add the simplicity and power of Moz Academy to the list of Moz subscription benefits.

Why create an inbound marketing school?

Moz is extremely passionate about educating our community. In fact, our entire business started as a blog where people could learn about SEO. Moz Academy gives subscribers the power to be better marketers, which will enable them to use our products in more depth and with greater confidence. We want to provide a hub of marketing knowledge that will create a stronger community where people can teach each other while using the Academy as a frame of reference. One could say that Moz Academy is the Mr. Miyagi of inbound marketing. The key to this project is empowering you to kick even more butt than you already do!

We hope Moz Academy turns into the one-stop-shop for inbound knowledge for Moz subscribers. Everyone on the team is committed to continually refreshing content and adding new lessons. Again, we really want this to be the easiest and most comprehensive place to learn internet marketing on the web.

Furthermore, we’ve designed each lesson with empathy in mind; they will be easily digestible and considerate of your time. That means you can drop in whenever you like and have comfortable breakpoints if you’re brain is exploding with inbound marketing knowledge.

Wait, how do I use Moz Academy?

Moz Academy is easy to use! Check out these six simple steps:

Step 1: Log into your Moz account.

Step 2: Go to moz.com/academy.

Step 3: Look through the lessons.

Step 4: Click a lesson you find interesting.

Step 5: Enjoy a video and/or read the lesson below it!

Step 6: Crane kick.

What lessons do you have right now?

We’re starting with the following lessons:

  • Inbound Marketing
  • SEO
  • Link Building
  • Social Media
  • Content Marketing

We plan to add a lot more! Look for lessons on local SEO, community management, video marketing, email marketing and web analytics. Yup, it’s going to be pretty sweet!

Well, Moz, what’s next for Moz Academy?

The future of Moz Academy really depends on how everyone uses it. In the next few months, we want to create a good foundation for beginners and subsequently build up to intermediate-level content. Eventually, we’d like to have sections for beginners lessons, intermediate lessons, and advanced lessons. Keep your eyes peeled, because we’ll be releasing a lot of new stuff! Some of our longer-term goals for Moz Academy are to have interactive quizzes and some sort of gamification. Yes, we know you’d like to track your progress and unlock achievements. That way you can show off how awesome you are at Moz Academy!

Eventually, we want Moz Academy to look more like Treehouse and Code School’s online learning platforms. We have a long way to go, but are excited about the journey to get there. With your help and feedback, we can make Moz Academy something awesome. Thanks in advance, and enjoy!


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SEO Finds in Your Server Logs, Part 2: Optimizing for Googlebot

Posted by timresnik

This is a follow-up to a post I wrote a few months ago that goes over some of the basics of why server log files are a critical part of your technical SEO toolkit. In this post, I provide more detail around formatting the data in Excel in order to find and analyze Googlebot crawl optimization opportunities.

Before digging into the logs, it’s important to understand the basics of how Googlebot crawls your site. There are three basic factors that Googlebot considers. First is which pages should be crawled. This is determined by factors such as the number of backlinks that point to a page, the internal link structure of the site, the number and strength of the internal links that point to that page, and other internal signals like sitemaps.

Next, Googlebot determines how many pages to crawl. This is commonly referred to as the “crawl budget.” Factors that are most likely considered when allocating crawl budget are domain authority and trust, performance, load time, and clean crawl paths (Googlebot getting stuck in your endless faceted search loop costs them money). For much more detail on crawl budget, check out Ian Lurie’s post on the subject.

Finally, the rate of the crawl — how frequently Googlebot comes back — is determined by how often the site is updated, the domain authority, and the freshness of citations, social mentions, and links.

Now, let’s take a look at how Googlebot is crawling Moz.com (NOTE: the data I am analyzing is from SEOmoz.org prior to our site migration to Moz.com. Several of the potential issues that I point out below are now solved. Wahoo!). The first step is getting the log data into a workable format. I explained in detail how to do this in my last server log post. However, this time make sure to include the parameters with the URLs so we can analyze funky crawl paths. Just make sure the box below is unchecked when importing your log file.

The first thing that we want to look at is where on the site Googlebot is spending its time and dedicating the most resources. Now that you have exported your log file to a .csv file, you’ll need to do a bit of formatting and cleaning of the data.

1. Save the file with an Excel extension, for example .xlsx

2. Remove all the columns except for Page/File, Response Code and User Agent, it should look something like this (formatted as a table which can be done by selecting your data and ^L):

3. Isolate Googlebot from other spiders by creating a new column and writing a formula that searches for “Googlebot� in the cells in the 3rd column.

4. Scrub the Page/File column for the top-level directory so we can later run a pivot table and see which sections Google is crawling the most

5. Since we left the parameter on the URL in order to check crawl paths, we’ll want to remove it here so that data is included in the top level directory analysis that we do in the pivot table. The URL parameter always starts with “?,” so that is what we want to search for in Excel. This is a little tricky because Excel uses the question mark character as a wildcard. In order to indicate to Excel that the question mark is literal, use a preceding tilde, like this: “~?”

6. The data can now be analyzed in a pivot table (data > pivot table). The number associated with the directory is the total number of times Googlebot requested a file in the timeframe of the log, in this case a day.

Is Google allocating crawl budget properly? We can dive deeper into several different pieces of data here:

  • Over 70% of Google’s crawl budget focuses on three sections, while over 50% goes towards /qa/ and /users/. Moz should look at search referral data from Google Analytics to see how much organic search value these sections provide. If it is disproportionately low, crawl management tactics or on-page optimization improvements should be considered.
  • Another potential insight from this data is that /page-strength/, a URL used for posting data for a Moz tool, is being crawled nearly 1,000 times. These crawls are most likely triggered from external links pointing to the results of the Moz tool. The recommendation would be to exclude this directory using robots.txt.
  • On the other end of the spectrum, it is important to understand the directories that are rarely being crawled. Are there sections being under-crawled? Let’s look at a few of Moz’s:

In this example, the directory /webinars pops out as not getting enough Google attention. In fact, only the top directory is being crawled, while the actual Webinar content pages are being skipped.

These are just a few examples of crawl resource issues that can be found in server logs. A few additional issues to look for include:

  • Are spiders crawling pages that are excluded by robots.txt?
  • Are spider crawling pages that should be excluded by robots.txt?
  • Are certain sections consuming too much bandwidth? What is the ratio of the number of pages crawled in a section to the amount of bandwidth required?

As a bonus, I have done a screencast of the above process for formatting and analyzing the Googlebot crawl.

In my next post on analyzing log files, I will explain in more detail how to identify duplicate content and look for trends over time. Feel free to share your thoughts and questions in the comments below!


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The Key to Empowering your Marketing Team – Whiteboard Friday

Posted by randfish

What holds marketing teams back from accomplishing great things? In today’s Whiteboard Friday, Rand tackles the big challenges many internal marketing teams face, and outlines a way to bring structure and empowerment back to your marketers.

Have something to add? Leave your thoughts and questions in the comments below!

The Key to Empowering your Marketing Team – Whiteboard Friday

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

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. Today I’m going to be talking to you a little bit about what holds marketing teams back from being able to accomplish great things inside of companies, and for external marketing teams that are on an agency or consulting basis, but really oftentimes internally.

So this, I’ve got here my six little friends. This one, this guy is kind of awkward. His back is a little out of whack. But that’s okay. He’s just a stick figure. He’s probably feeling just fine.

The challenge for these guys is that they constantly need their work reviewed. They’re kind of in the weeds, in the trenches doing marketing activities, building content, trying to get that content shared and linked to, trying to earn rankings and traffic, trying to buy advertising, trying to influence the website and the marketing materials, make the conversion rate higher, do all these things to promote the marketing funnel improving. Yet they’re constantly changing course, sometimes daily, sometimes even hourly. Boss comes in, it’s sort of like, “No, no, no, don’t do that anymore. Focus on this thing. No, wait, I know I told you to do that, but we don’t need that anymore. We need this other thing.”

They’re not empowered to make decisions, not even about their own work. They really have to get constantly reviewed. Someone comes and gives them feedback on everything they do. I’ve been this marketer myself before. Especially as a consultant, you’re oftentimes in this position. You don’t have that empowerment to make great decisions.

But there’s a way to fix this, and it’s an architecture I want to share with you that’s been really powerful for me and for a number of other companies that have adopted this and that have shared it too. So the idea is basically that what we want to do is we want to take all the things that the company wants to accomplish today, in the future, in the far, far flung future, and we want to connect that all the way down to what the marketing team is actually working on today, right now. But it takes a little bit of work, and it takes a lot of transparency, and it takes some thinking. If you don’t have this architecture yet, you should give it a try. Let me show you what I’m talking about.

A big company vision is a great starting point. I know many small and medium businesses don’t even really have a great big company vision. But if you can imagine one, if you can put one on there, “We want to be Cleveland, Ohio’s best marketing agency, and we define best as our clients are the happiest, we have the most clients, and we have the highest revenues in the city.” Okay, great, now you’ve got a company vision. Moz’s vision, for example, is to help people do better marketing. Tesla’s vision is to transform how the world is transported. NASA has an organizational vision to explore space. So you can get a company vision.

So let’s say it is, “Help people do better marketing.” From that flows things that you’re going to do over the next few years. It could be five years, it could be just two or three years, but the mission that you have. I’m going to go back to Tesla again because I love Tesla’s five-year mission. Tesla’s five-year mission is to “Power the transformation from gas to electric vehicles and to become the world’s leading car company by doing that.” So become the world’s leading company by powering the transformation from gas to electric.

Okay. Then, based on that mission, that thing that you want to accomplish over the next few years, you have a BHAG. A BHAG is Big Hairy Audacious Goal. I know it sounds a little funny, but this acronym is actually quite important, and so are all the letters in there. Big because you want it to be hard to achieve. My favorite thing that people say about a BHAG is,
“It’s out of reach, but not out of sight.” A goal that is out of reach, I can’t see us accomplishing it today. My God, it’s almost hard to imagine that we accomplished it, but not completely out of sight.

So perhaps Tesla would say that their BHAG is to be the world’s number one auto manufacturer in ten years or in five years. That means that they have to build so many cars and sell so many cars that they are the world’s leading car company through number of cars on the road. For Moz, our BHAG is one million people subscribing to our platform. For your Cleveland, Ohio consulting agency, it might be successfully keeping and maintaining 100 paying customers at $5,000 a month or more for a full year, nonstop. Whatever it is, it has to be definable, easily definable, easily measurable, and powerful, something that people can get behind.

I’ll go back to NASA again. That moon mission that they had, in the 1960s NASA had the moon mission and the BHAG for the moon mission was, “Put a man on the surface of the moon and return him safely to the earth.” Super measurable, super definable, incredibly powerful to get behind. If you’re doing marketing for that, you can see that big vision and that big goal very clearly. Then from there, from these two, I’m going to take our mission and our BHAG, and I’m going to define a list of strategic goals, things we need to accomplish in order to get these things done. But they’re going to be things that we do over the next 6 to 12 months, just 6 to 12 months, just the next little while. This is really powerful because those strategic goals should flow down to everything else that the company does.

So if, for example, I say, “Hey, in order to sell more cars, Tesla needs to open Tesla dealerships in 500 cities over the next 12 months, and here’s the list of cities.” Okay, that’s a strategic goal. Now we’ve got to go get that done. We need to figure out people who know how to open stores and people who know about real estate, and we need to have a bunch of investment dollars that we can put it in these things. We need to figure out how long it is before we open a dealership before that actually turns into sales for us. We need to hire all the salespeople. We need to build a process for that. Huge list of things that come from those, but the strategic goal is very simple. “Open stores in 500 cities.”

At Moz, one of our strategic goals is to increase the retention of our Pro subscribers. Build stuff. Make stuff in the product that makes people want to stick around and use Moz longer. Okay, these are strategic goals.

Then, from there, now we really start to get into the nitty-gritty with the marketing goals being tied to these company goals, and this is such a powerful architecture. It just removes all kinds of barriers, because now I can go and I can build a process like this, right here. So I take a goal that the team is trying to accomplish, and I translate that into what my actual marketing task is around it. Then I have the process and the people that I need for that goal. So actually, I’m going to use my checkboxes that I actually made.

I define my goal, I get the process and people I need, I figure out how we define success, what the measurable elements are. Maybe it’s, “Hey, we need to broaden our brand’s reach.” We want to have more people exposed to the Moz brand, and so therefore, we are going to define a goal as half a million people following our Twitter account and 100,000 people following our Google + account, and maybe a million people following us on Facebook and whatever those things are.

Then you have those metrics-based targets. So those could be website visitor statistics. They could be conversions. It could be an ROI number. It could be a cost number. Many times a strategic goal will be to reduce cost to a certain amount, and then you have these goals. “Hey, we need to reduce customer acquisition costs. We need to find channels that don’t cost as much.” Oftentimes, inbound channels don’t cost as much, things like SEO and email marketing, opt-in email marketing, community building, and content and those kinds of things, that’s a great way to reduce customer acquisition costs. It could be a marketing goal, and you figure out who the process and people are behind that. We may need a writer. We’re going to need someone who is a marketing analyst to do all the statistics work. We’re going to figure out how we measure success. That’s going to be measured through number of people acquired through these lower-cost channels. We’re going to have metrics-based targets. We’re going to say we want to acquire 20% of our customers through non-paid channels by the end of 2013.

Great. Now you have something so amazing. You have marketers that can see the big picture. They can see all the way. They know everything that’s connected here, and that means that they know how their work matters. I can’t tell you what a change in attitude you get when you understand how your work matters versus wondering why you’re pushing buttons. It’s just a remarkable change. Now, those same people can navigate project complexity without needing someone over their shoulder, looking all the time at their work, making sure that they’re doing the right thing, reviewing, because they can see that full connection.

You might have someone who reviews the work at the end of the cycle or is in a project planning meeting with them, maybe a manager or a senior leader or something like that, and that’s fine and that’s a good thing. But you don’t need to be in the weeds with your team anymore, and because they’re empowered, they can choose how they work best, figure out what makes them most effective, and then they can execute on projects.

I urge you to give this a try. It won’t take that long, especially if you’ve got some of these bigger things already defined, and it can really move the needle on how your marketing team works.

All right, everyone. Hope you’ve enjoyed this edition of Whiteboard Friday. We’ll see you again next week. Take care.

Video transcription by Speechpad.com


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Google’s "Multi-Week" Algorithm Update

Posted by Dr-Pete

Back on June 21st, Matt Cutts replied to a tweet about payday loan spam with an unusual bit of information (reported on Search Engine Roundtable):

The exact timeline was a bit unclear, but Matt seemed to suggest a prolonged algorithm update covering as many as three weeks. Four days later, we tracked our highest temperature ever on MozCast, followed by more record highs:

Seven days during the “multi-week” timeline showed temperature spikes near or above 90°, with six of those days exceeding the severity of the original Penguin update.

Was It A MozCast Glitch?

Let me perfectly honest – Google rankings are a moving target, and tracking day-to-day flux has proven difficult at best. Any given temperature on any given day is prone to error. However, this was a sustained pattern of very high numbers, and we have no evidence to suggest a glitch in the data.

There were some reports that other tools were not showing similar spikes, but some of these reports were based on apples-to-oranges comparisons. For example, if you look at SERPmetrics flux data and isolate just page 1 of Google (which is what MozCast tracks), you’ll see this:

Sorry, it’s a bit hard to see the dates on the reduced image, but the two spikes equate to roughly June 28th and July 4th, with a smaller bump on June 25th. While they’re not an exact match, these two data sets are certainly telling a similar story.

Was It A Large-scale Test?

This is a much harder question to answer. Our beta 10K data set showed similar patterns across multiple C-blocks of IPs, so we have no reason to believe this was specific to one or a very few data centers.

What if Google made a massive change one day, though, and then reverted it? Theoretically, we would see two days of high MozCast temperatures, but if we looked at the two-day flux (instead of two one-day numbers), the temperature would be very low. While this multi-day flux is theoretically interesting, it can be very hard to interpret in practice. Some rankings naturally change, and Google can roll out multiple small updates in any given week.

If we look at the overall flux between the start and end of recorded spikes (June 25 – July 4), we get a MozCast temperature of 120.3°, not much higher than the one-day temperature on June 27th. The average daily temperature for this period was 92.5°. Now, let’s look at a similar time period (May 28 – June 6) – the average temperature for that period was 66.8°, and the multi-day temperature across the entire period was 114.7°.

Comparing the two time periods, the overall flux for the period of record temperatures was roughly the same as the peak and about 30% higher than the multi-day average, whereas the overall flux for the quieter period was 72% higher than the average. This is an inexact science at best, and we don’t have a good historical sense of multi-day patterns, but my gut feeling is that some of the multi-week update involved changes that Google tested and later rolled back.

What About PMDs & EMDs?

In my post on the June 25th temperature spike, I reported a noticeable single-day drop in partial-match domain (PMD) influence. That post happened very early in the multi-week update, so let’s look at the PMD influence data across a 30-day time period that includes all of the high-temperature days:

While there was a lot of movement during this period, you can see that PMDs recovered some of their initial losses around July 4th. The overall trend is downward, but the June 25th drop doesn’t appear to have been permanent.

It’s interesting to note, even if not directly relevant to this analysis, that the long-term trend for PMD influence in our data is still decidedly downward. Here’s a graph back to the beginning of 2013:

So, how have EMDs fared? They seem to show a similar pattern, but in a much tighter range. Scaled to the same Y-axis as the PMD chart above, we get this:

The EMD data is fairly consistent with Dr. Matt Peters’ early report on our 2013 Ranking Factors study. Keep in mind that we are measuring two different things – the correlations show how well PMDs/EMDs ranked compared to other domains, whereas MozCast tracks how many PMDs/EMDs ranked across the data set. If the number of total PMDs drops, but they rank roughly as well, the correlations will remain stable, but the “PMD Influence” metric will drop. In other words, the correlations measure how well PMDs rank, whereas MozCast measures how many PMDs rank.

Which PMDs Lost Long-term?

There’s one more question we can ask about the drop and subsequent recovery in PMD influence. Did the PMDs that fell out eventually come back, or were they replaced by different PMDs? The metric itself doesn’t tell us, but we can dig deeper and see who lost out long-term.

On the initial drop (between June 25-26), 62 PMDs fell out of our public 1K MozCast query set. New PMDs always enter the mix, so the net drop is smaller, but 62 PMDs that were ranking on June 25th weren’t ranking on June 26th. So, let’s compare that list of 62 to the data on July 5th – after the apparent recovery. On July 5th, 37 of those PMDs (60%) had returned to our data set. This certainly suggests some amount of legitimate recovery.

So, which losing PMDs failed to recover? Here’s the complete list (query keywords in parentheses):

  • californiacarshows.org (car shows)
  • digital-voice-recorder-review.toptenreviews.com (voice recorder)
  • fullyramblomatic-yahtzee.blogspot.com (yahtzee)
  • virginiamommymakeover.com (mommy makeover)
  • www.appliancepartscenter.us (appliance parts)
  • www.appliancepartssuppliers.com (appliance parts)
  • www.campagnolorestaurant.ca (campagnolo)
  • www.campagnolorestaurant.com (campagnolo)
  • www.capitalcarshows.com (car shows)
  • www.chicagoweddingcandybuffet.com (candy buffet)
  • www.dollardrivingschool.com (driving school)
  • www.elitedrivingschool.biz (driving school)
  • www.etanzanite.com (tanzanite)
  • www.firstchoicedrivingschool.net (driving school)
  • www.fitzgeraldsdrivingschool.com (driving school)
  • www.monogrammedgiftshop.com (monogrammed gifts)
  • www.moscatorestaurant.com (moscato)
  • www.newjerseyluxuryrealestate.com (luxury real estate)
  • www.ocsportscards.com (sports cards)
  • www.phoenixbassboats.com (bass boats)
  • www.rvsalesofbroward.com (rv sales)
  • www.sri-onlineauctions.com (online auctions)
  • www.stoltzfusrvs.com (rvs)
  • www.vibramdiscgolf.com (vibram)

It’s not my goal to pass judgment on the quality of these domains, but simply to provide data for further analysis if anyone is interested. You can see that there are a few examples of multiple PMDs falling out of a single query, suggesting some kind of targeted action.

How Did The Big 10 Do?

In MozCast, we track a metric called the “Big 10” (I did my grad work at U. Iowa, so I should probably have thought twice about that name) – it’s just a count of the total percentage of top 10 ranking positions held by the 10 most prominent sites on any given day. Those sites may change day-to-day, but tend to be fairly stable. Looking back to the beginning of 2013, we see a clear upward trend (this graph starts on January 8th, due to a counting issue we had with YouTube results at the beginning of the year):

The “Big 10” gained almost 2-1/2 percentage points in the first half of the year. Some of the gain across the year represents a shuffling of sites in the mix (Twitter falls in and out of the “Big 10”, for example, and the root eBay domain struggled earlier this year), and some of this is a symptom of other changes. As Google gets more aggressive about spam, the sites that already dominate naturally tend to take more spots.

I thought it would be interesting to look at these numbers alongside the year-to-date PMD and EMD numbers, but the “Big 10” doesn’t seem to tell us much about the multi-week update. As a group, they moved only a fairly small amount between June 25th and July 5th (from 14.97% to 15.17%). Whatever Google tested and rolled out over this period, it didn’t dramatically advantage big brands in our data set.

What Happened, Then?

Unfortunately, the patterns just aren’t clear, and digging into individual queries that showed the most movement during the multi-week update didn’t reveal any general insights. The volatility during this time period seems to have been real, and my best guess is that while some changes stuck, others were made and rolled back. Google may have been doing large-scale testing of algorithm tweaks and refining as they went, but at this point the exact nature of those changes is unclear. Between the multi-week update and Google’s announcement of 10-day Panda roll-outs, it appears that we’re going to see more prolonged updates. Whether this is to mitigate the impact of one-day updates or make the update process more opaque is anyone’s guess.


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