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When Facebook rolled out the ability to reply to comments on Facebook, my immediate reaction was … indifferent. Actually, I thought it was more likely it would complicate conversations and give spammers additional ways to pollute comment sections. Read the rest of this entry »

Posted by Dr. Pete

The long-awaited Penguin 2.0 (also called "Penguin 4") rolled out on Wednesday, May 22nd. Rumor has been brewing for a while that the next Penguin update would be big, and include significant algorithm changes, and Matt Cutts has suggested more than once that major changes are in the works. We wanted to give the dust a day to settle, but this post will review data from our MozCast Google weather stations to see if Penguin 2.0 really lives up to the hype.

Short-Term MozCast Data

First things first – the recorded temperature (algorithm "flux") for May 22nd was 80.7°F. For reference, MozCast is tuned to an average temperature of about 70°, but the reality is that that average has slipped into the high 60s over the past few months. Here's a 7-day history, along with a couple of significant events (including Penguin 1.0):

By our numbers, Penguin 2.0 was about on par with the 20th Panda update. Google claimed that Penguin 2.0 impacted about 2.3% of US/English queries, while they clocked Panda #20 at about 2.4% of queries (see my post on how to interpret "X% of queries"). Penguin 1.0 was measured at 3.1% of queries, the highest query impact Google has publicly reported. These three updates seem to line up pretty well between temperature and reported impact, but the reality is that we've seen big differences for other updates, so take that with a grain of salt.

Overall, the picture of Penguin 2.0 in our data confirms an update, but it doesn't seem to be as big as many people expected. Please note that we had a data collection issue on May 20th, so the temperatures for May 20-21 are unreliable. It's possible that Penguin 2.0 rolled out over two days, but we can't confirm that observation.

Temperatures by Category

In addition to the core MozCast data, we have a beta system running 10K keywords distributed across 20 industry categories (based on Google AdWords categories). The average temperature for any given category can vary quite a bit, so I looked at the difference between Penguin 2.0 and the previous 7 days for each category. Here they are, in order by most impacted (1-day/7-day temps in parentheses):

• 33.0% (80°/60°) – Retailers & General Merchandise
• 31.2% (81°/62°) – Real Estate
• 30.8% (90°/69°) – Dining & Nightlife
• 29.1% (89°/69°) – Internet & Telecom
• 26.0% (82°/65°) – Law & Government
• 24.4% (79°/64°) – Finance
• 23.5% (81°/65°) – Occasions & Gifts
• 20.8% (88°/73°) – Beauty & Personal Care
• 17.3% (70°/60°) – Travel & Tourism
• 15.7% (87°/75°) – Vehicles
• 15.5% (84°/73°) – Arts & Entertainment
• 15.4% (72°/62°) – Health
• 15.0% (83°/72°) – Home & Garden
• 14.2% (78°/69°) – Family & Community
• 13.4% (79°/70°) – Apparel
• 13.1% (78°/69°) – Hobbies & Leisure
• 12.0% (74°/66°) – Jobs & Education
• 11.5% (88°/79°) – Sports & Fitness
• 7.8% (75°/70°) – Food & Groceries
• -3.7% (70°/73°) – Computers & Consumer Electronics

Retailers and Real Estate came in at the top, with just over 30% higher than average temperatures. Consumer Electronics rounded out the bottom, with slightly lower than average flux, oddly. Of course, split 20 ways, this represents a relatively small number of data points for each category. It's useful for reference, but I wouldn't read too much into these breakdowns.

"Big 20" Sub-domains

Across the beta 10K data-set, we track the top sub-domains by overall share of SERP real-estate. Essentially, we count how many page-1 positions each sub-domain holds and divide it across the entire data set. These were the Big 20 sub-domains for the day after Penguin 2.0 hit, along with their SERP share and 1-day change:

1. 5.66% (+0.29%) – en.wikipedia.org
2. 2.35% (-0.75%) – www.amazon.com
3. 2.22% (+3.11%) – www.youtube.com
4. 1.49% (+6.05%) – www.facebook.com
5. 1.35% (-8.11%) – www.yelp.com
6. 0.84% (+4.77%) – twitter.com
7. 0.58% (+0.37%) – www.webmd.com
8. 0.58% (+1.87%) – pinterest.com
9. 0.52% (+1.24%) – www.walmart.com
10. 0.49% (+4.54%) – www.tripadvisor.com
11. 0.47% (+0.45%) – www.foodnetwork.com
12. 0.47% (-0.44%) – allrecipes.com
13. 0.44% (+1.98%) – www.ebay.com
14. 0.41% (-0.76%) – www.mayoclinic.com
15. 0.38% (+1.72%) – www.target.com
16. 0.37% (-4.37%) – www.yellowpages.com
17. 0.37% (+0.58%) – popular.ebay.com
18. 0.36% (+2.12%) – www.huffingtonpost.com
19. 0.33% (+3.27%) – www.overstock.com
20. 0.32% (-0.32%) – www.indeed.com

By percentage change, Yelp was the big day-over-day loser, at -8.11%, and Twitter picked up the highest percentage, at +4.77%. In absolute positions, YouTube picked up the most page-1 rankings, and Yelp was still the biggest loser. Overall, the Big 20 occupied 20.00% of the page-1 real estate the day after Penguin 2.0, up from 19.88% the previous day, picking up a modest number of ranking positions.

3rd-Party Analyses

Most reports yesterday showed relatively modest day-over-day changes (solid evidence of an algorithm update, but not a particularly big update). One exception was Dejan SEO's Australian flux tracker, Algoroo, which showed massive day-over-day flux. We believe that at least two other major algorithm updates have rolled out in May in the US, so it's possible that multiple updates were combined and hit other countries simultaneously. This is purely speculative, but no other reports seem to suggest changes on the scale of the Australian data.

The May 9th Update

I'd like to also call out an unconfirmed algorithm update in early May. There was a period of heavy flux for a few days at the beginning of the month, which was backed up by webmaster chatter and other 3rd-party reports. Temperatures on May 9th reached 83.3°F. The MozCast 7-day graph appears below:

The temperature spike on May 5th is unconfirmed, and may have been a test across a small number of data centers (unfortunately, our 10K data for that day was running a separate test and so we can't compare the two data sets). Reports of updates popped up across this time period, but our best guess is May 9th. Interestingly, traffic to MozCast tends to reveal when people suspect an update and are looking for confirmation, and the traffic pattern shows a similar trend:

Traffic data also suggest that May 5th was probably an anomaly. Private data from multiple SEOs shows sites gradually losing traffic over a couple of days in this period. Unfortunately, we have no clear explanation at this time, and I do not believe that this was directly related to Penguin 2.0. Google did roll out a domain crowding update at some point in the past couple of weeks, which may be connected to the early May data, but we don't have solid evidence either way. At this point, though, I strongly believe that the data indicates a significant algorithm update around May 9th.

Were You Hit by Penguin 2.0?

It's important to keep in mind that all of this is aggregate data. Algorithm updates are like unemployment rates. If the unemployment rate is 10%, the reality for any individual is still binary – you either have a job or you don't. You can weather 20% unemployment if you have a job (although you may worry more), and 5% unemployment is little comfort if you're jobless. I don't want to suggest any lack of empathy for those hit by Penguin 2.0 by suggesting that the update was relatively small, but overall the impact seems to be less jarring and jolting than many people feared. If you were hit, please share your story in the comments.

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The promise of social media was once “one-to-one engagement” and “relationship building” … but somehow “building a relationship” in social media has morphed into blasting messages at as many people as possible and hoping someone is attracted.

How the heck did this happen?  Read the rest of this entry »

Posted by SteKenwright

This post was originally in YouMoz, and was promoted to the main blog because it provides great value and interest to our community. The author’s views are entirely his or her own and may not reflect the views of SEOmoz, Inc.

This kind of thing might happen to Rand all the time, but it’s not often that a digital marketing company based in Leeds gets 100,000+ people reading anything it does (at least on its own site). That’s what unexpectedly happened to us on www.branded3.com a few weeks ago – what essentially started as a rant from some guy having a bad day blew up and now has 1,184 votes on Hacker News (and incoming links from some of the biggest sites in the world).

I think it’s likely I’ll never replicate this, and I didn’t intend this either – so I’ll not preach: “this is how you get 100,000 page views.” Everyone else is just as qualified as I am to write a post that’s read all around the world, and that’s exactly what I want to happen. I’d like to tell you what I’m taking away from this, and how I’ll use it when I’m creating content for my clients in the future.

Commonly known as sharking. Google it.

1. [citation needed]…but not always.

Google only wants you to list the links that are most relevant to and most important to your content – Eric Enge likened this to a research paper around a month ago on Search Engine Watch. The difference between your content and a research paper, though, is that your content doesn’t get discredited if there is nobody to link to that backs up the point you’re trying to make.

In a Webmaster Help Video earlier in the year, Google Engineer Matt Cutts said don’t link out to low quality sites – this is pretty much the equivalent of quoting from Wikipedia in an essay. You don’t have to get peer approved before people will read your post, though, so if there’s nobody to link to that’s talking about whatever you are then that could actually be a good thing. If someone else is covering the same subject as you there’s no real reason why you should get all the links, so you should definitely write about things that no one else is covering if you can.

NB: Not having anyone to back up your point doesn’t excuse you from not having a point in the first place.

2. Content needs to solve people’s problems…or highlight them.

I had a problem with Path and as of the time I started writing the post, nobody had solved it, though a few people had tweeted about experiencing similar problems. I tweeted @path at roughly 7am and the first person to reply was someone else who was (very) actively looking for an answer to the same problem. I embedded Design33’s tweet in the post and linked to him; let my cohort know; and instantly a problem shared is a problem…erm, doubled.

Whether your content is solving someone’s problem, or you’re just empathising with them; if you know where to find them…let them know it’s there and get your influencers on board.

3. Find out what people are looking for.

The principles behind content marketing are gaining real traction in the SEO community, and more and more companies are getting on board with long-term content strategies. There’s plenty to say about planning your content out for months in advance, but as Simon points out in this fantastic YouMoz post from last year, it’s not all about Google Keyword Tool anymore. There are some great tools out there to find hot topics (Bottlenose is particularly useful), but the best way to find what your audience is looking for is by using the same tools as they are.

Wil Reynolds is a great advocate of using Google Complete to find content topics (check out Wil’s LinkLove 2013 presentation, around slide 90) – start typing questions, don’t press enter; just note down what people are actually searching for. Search Twitter and find out not only what problems need solving, but who it is that actually has that problem (see point two)! Google Keyword Tool shouldn’t be your first stop when you’re looking for fires to put out, and if it’s monthly search volume you’re looking at, chances are someone faster has created content solving the same issue weeks ago.

4. Find your forum.

…by which I don’t literally mean a forum, since as an industry we’ve pretty much ruined that for everyone – all I’m saying is that you just need to find the right soapbox to spread your message.

In the comment string on our site this guy called me out for posting this on a company blog. At the time I hadn’t really questioned where else I could actually write this up, so Luca made me think. If I had put this on my own blog nobody would have read it…I would have just been complaining without any real platform to build on (might as well have just put it on Facebook or Twitter).

One of our clients is a cloud storage company who obviously have a vested interest in online security, and do write about issues such as this from time to time. They’d never approve something like this for their blog (more in point six) so I would have had to dry it right out…or put it on another site on their behalf.

Hammering this article to fit brand guidelines would have dulled its impact so much, and for a company to write about real life issues like this they really would have had to find a real life case…otherwise they’re just tipping off the media. It would never have worked.

If you’re going to be controversial, find a site that’s fine with that to host your content – that goes for the content you’re putting out on behalf of your clients too. We’ve had plenty of content turned down by webmasters for being too much for their blogs, and you’ve got to respect that. Guest blogging is like the name implies, and you’ve got to make sure you don’t leave a mess in someone else’s house.

5. Write for your audience…

Something everyone is taught in English class from a relatively early age is how to write for an audience. Even if you came into SEO from something else – a computer science degree, MA in marketing; whatever – you still have those classes to fall back on, and they’ll give you a pretty solid foundation in content marketing. In this industry everything comes from experience – if you covered search engine optimisation in your degree I’m sure you found half the things you knew were obsolete by the time you’d graduated…and post-Penguin the other half will get you penalised too.

I found when I moved from in-house to agency side search engine marketing, most of the things I’d been doing for the last year were considered pretty spammy. If you’re writing to put content on websites that nobody reads, like article marketing websites, then you’re not writing for an audience…and that shows in the work you put out.

You don’t have to be a journalist to create great content. If you’re solving problems imagine you’ve got that problem yourself and then just write for you…

6. …don’t write for your client.

If you think you’ve found a hot topic and your client isn’t happy with being associated with it, there’s probably a case for not pushing that. Controversial content gets links, but there’s a certain amount of press that comes with those links.

I don’t have a PR agency, so TechCrunch pointing out that it was probably my fault isn’t a disaster from my point of view. If your client makes a mistake then it might be. In the case of my blog post it wasn’t long before the media-at-large didn’t care anymore (TechCrunch may have even been the start of that) and the chances are pretty good that nobody will remember a guy getting mad at his phone in a few weeks – if a tech company posted a rant about Path it would probably be called a smear campaign.

…and I won’t lie – when the VP of Marketing called me I was more than a little worried.

7. Your content has to be worthy of links to get any…

This is my very first YouMoz post, and there’s a good reason for that – up until now I’ve not really had anything to say that I think might help the community, so I’ve stuck to my blog, Twitter and getting all up in other people’s business when I get the chance.

If you’ve got an opportunity to write for a great site – or to work with a well-known journalist, or whatever – giving them a few hundred words of nothing content will a) not generate much in the way in traffic, b) not generate any leads, and c) make that great site think twice about having you back.

8. …and so does your site.

Which leads me on to number eight: the whole point of placing links as part of a content marketing strategy (or at least it probably should be the main point) is for people to click through to your site. Make sure your users are arriving on a page they want to see.

@stekenwright @phillipsnick @newsyc20 @path I think that branded3.com needs to install a WordPress caching plugin.

— David Lynch (@kemayo) April 30, 2013

When St. Louis-based developer David Lynch submitted the post to Hacker News our entire site went down almost immediately (at 17:25, which our Development team were definitely not happy about). It’s a pretty extreme example, but if your site doesn’t present people with the screen they were expecting to see they’re probably going to leave straight away.

This applies not only in a technical SEO sense (see Aleyda Solis’ wonderful resources on mobile SEO and which versions of a page you should be serving to which people for a start), but also in something as intrinsic as the services you’re providing.

Going back to point four (Find your forum): the company I work for not only has a burgeoning social team, but an entire blog dedicated to social media – the perfect place to host an article about a social network, in my opinion.

Make sure your link is pointing to the kind of page your audience wants to find.

9. Be funny, or insightful. Probably not both.

The links generated by my post contain so much more useful information and insight than my content does. Like I said, I’m not pretending to be a journalist uncovering a story. I just presented a real life experience in a humorous way…because it was pretty funny. How do you explain what you do to your partner’s grandparents? I go with “I work with computers”. Imagine trying to explain a social network to two different pairs of 80 year-olds before 6:30 in the morning? You’ve got to laugh, as the expression goes.

Your multi-national debt management firm probably can’t be funny in its content (very happy for people to prove me wrong here). Companies like this have guidelines to uphold and the chances are they’re much more interested in their brand guidelines than the links you’re working so hard to get for them. Make sure you take tone of voice into account and if your content doesn’t work in their speak, see point six. You’re writing the wrong thing.

Your post definitely needs a Wonka meme.

10. Don’t do it for the links.

Writing my blog post, I had absolutely no intention of getting a single link. In all honestly I didn’t fully expect the guys at Path to see it – I just wanted to vent and if possible, make my colleagues laugh. In a very helpful post on Quick Sprout last October KISSmetrics’ Neil Patel wrote that he never manually built a link – he just kept writing. We’re not KISSmetrics, but our blog has been covering as many of the happenings in the digital marketing world as we can possibly manage for more than half a decade – and mostly we just do it because we want to.

Posting a piece of content on your blog every few weeks or months and expecting it to get picked up isn’t going to happen; and it’s definitely not content marketing – it’s just content. No matter how good your stuff is, don’t be disheartened if you don’t get any traction with a blog post…or a hundred blog posts.

What I do think is important is that you look at every piece of content you write and think about how to make it better this time. You don’t need to over-analyse every post before it goes live – I would guess you’ve got targets and deadlines to make after all – just think about how to improve on what you’ve got so your next article will make outreach easier, or will help more people out; and if your last piece performed well, how are you going to beat it? Even if you know you won’t.

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“Two roads diverged in the social media wood, and I, I took the one less traveled,” said 21.7% of salespeople.

In a recent survey of 511 predominantly B2B sales reps and executives published on A Sales Guy Consulting, approximately 22% of salespeople claimed they didn’t use social media to close deals, while an overwhelming 78.3% said they had used social media to sell. Read the rest of this entry »

Posted by timresnik

Last week, I held a Mozinar outlining a method to extract SERP vertical — called Universal Search by Google — from Google referral strings. Since the Mozinar concluded, the number of people who have reached out with their own theories and ideas has been impressive. I want to post everything that I know here and then leave it up to you folks in the SEOmoz community to start hacking and sharing your insight.

For those of you who did not see the Mozinar, you can access it here (voiceover included). You can also download or view the slides without VO on Slideshare here.

Before getting into the step-by-step process and providing examples of how to use the Google referral string to interpret where in Universal Search your traffic came from, I want to lay out a problem we were having at AudienceWise. In 2011, Matthew Brown and I started an agency to help news publishers with technical SEO and audience development. In our other jobs, specifically Matthew at the New York Times, we struggled with reconciling for the lack of data around Universal Search referrals. As far as our web analytics platforms were concerned, a visit from web search, a News OneBox link, and an image result were all treated exactly the same: as organic search traffic.

Then came Google Secure Search, and referral data got even more opaque. In addition to not knowing which Universal vertical the referral came from, now in about 10% of cases we didn’t even know the keyword that referred the traffic. The question that kept going through our collective ginger minds was: how can we help our clients with content strategy if we know nothing about WHY they are receiving said search traffic? Unfortunately, Secure Search has vastly expanded and now accounts for a large percentage of all Google referral traffic. As way of an example, here is the latest percentage of keyword = (not provided) for SEOmoz:

Matthew and I knew the only way to reclaim *some* of this lost data was to start looking at other sources. Luckily, Matt speaks Spanish (sort of) and came across this blog. The author posited that the 'ved' parameter in the Google referral string held some magic in determining the vertical that result appeared in. After doing some quick searches, and looking at the “href” values for the results, it seemed like he was onto something. We immediately set up Google Analytics profile filters to extract this parameter on a client that receives 300,000 search referrals from Google per day. After a couple of hours, we were loaded with enough data to start confirming some of the authors theories and coming up with a few of our own. I will layout what we found, provide a step-by-step tutorial to setup Google Analytics filters, and provide a few examples of how to use the data.

First, let’s talk about where you can find this parameter.

Simply, the Google referral string is the “href” value assigned to each URL in a set of search results. When a user clicks on the above, she is being redirected through a google URL prior to reaching her final destination; Radiohead.com, in this case. Google most likely does this for internal data aggregation reasons — we’re not suppose to know where our traffic comes from, but they sure make use of it — probably for aggregating data around SERPs.

There are two parameters that I will focus on here: ‘cd’ and ‘ved.’ The ‘cd’ parameter has been written about before and tells us the position of the search result in the set. As far as I can tell, the ‘ved’ parameter is divided into three parts and tells us which Universal vertical the result is part of, the position within that vertical (relative position), and the position within the search result (absolute position). I will focus on just the Universal aspect for this post and will follow up with relative vs. absolute position in a follow-up.

Let’s have a look at a few examples.

When QFj is in the ‘ved’ parameter that the result is a standard web search result, such as:

One of the attendees of the Mozinar made this astute observation about a special variation for the web search 'ved':

When QqQIw (that’s a capital “i” not a lowercase “L”) it is a Universal result that resides within the Google News OneBox. When QpwI is present that means the result was the thumbnail image within the News OneBox.

You get the idea. Here are some other values of ‘ved.’ I suspect that there are many more and am curious to see what the community here can find and SHARE here within:

Setting up Google Analytics filters

You should have a good understanding now of potential power of this information. Did I mention that it is still available even if the keyword is “(not provided)”? We could potentially interpret the keyword by comparing ‘ved.’ Anyone up for the challenge? I go through one example below. While ‘ved’ appears to persist through Secure Search only about 50% of the search referrals within GA have this data. If anyone can shine light on this, I’m sure the rest of the community would shower you with thumbs ups!

Step 1: Set up a Google Analytics Profile filter

Go to the account’s administrative dashboard and select “New Profile.” I would recommend against setting this filter up on an existing profile as that it will overwrite some data that you otherwise want. I called mine ‘Universal Search.’

Next, you will need to set up two advanced filters; one to extract ‘ved’ and ‘cd’ from the Google referral string, and the other to display the data within Google Analytics.

Universal Extract

Here’s the text of the regex that I used

Field A  (\?|&)(ved)=([^&]*)

Field B (\?|&)(cd)=([^&]*)

Universal Display

There’s many different ways to do this. I’ve decided to overwrite the campaign dimension of source since that’s where I am checking my organic search referrals.

Filters work while the data is streaming in and will not be reflected retroactively. That’s fine; you just have to wait for a day or so (or an hour or so for bigger sites) to start digging in. Here’s what it should look like:

Step 2: Set up Advanced Segments

I prefer to do this level of analysis in Excel, but Advanced Segments can be created to make it all look pretty in GA. I will walk you through the setup of one, which will inform you how to do the rest.

You will want to name your Advanced Segment something that will clue you in to which vertical you are analyzing. In this case, I have called out that it is a standard ‘blue link’ result from a News OneBox. From there, all you need to do is search on ‘Source’ for anything containing the ‘ved’ you are trying to isolate. In this case, we are looking for ‘QqQIw.’

Here’s an example of what you will see:

Wow! There is an actionable result right in front of me. It’s probably time to do some image optimization. Google apparently respects the site as a news authority, but not one that creates good images.

Another useful ‘ved’ to investigate is Sitelinks. Sitelinks are a subset of results triggered by a branded search. Google algorithmically determines which links to include, but webmasters have the ability to demote links in Webmaster Tools. The 'ved’ parameter can come in handy to measure performance of Sitelink pages and action can be taken. In order to figure out the Sitelink that sent the search referral, look at the ‘cd’ value that was passed with the referral string. We accounted for this in the filters and it is in your data here:

Here’s what the ‘cd’ values mean in relation to Sitelink results:

There are myriad of use cases for bubbling up SEO action items. Here are a few, and please add more in the comments:

• Calculating ROI and resource allocation for different SEO efforts: News, image, branded, and semantic markup. As marketers, we are only as valuable as what we can quantify. A challenge with SEO is demonstrating value. This does not solve the problem, but exposes a few more variables to work with.
• Optimizing branded search Sitelinks: As I outlined above, there is value in knowing which branded links send you traffic. This is also one area where you can mitigate the loss of keyword data due to Secure Search. When you see that a keyword is (not provided) AND ved = xxxxQjB, you can interpolate that keyword = YOUR BRAND.
• Image optimization for Google News: The top link in the Google News OneBox is most often a different source than the image thumbnail. If ved = xxxxQqQIw ÷ ved = xxxxQpwI, or the ratio of links to images, is way off-kilter it suggests there is an image optimization issue. Publishers can then use this data to measure optimization efforts against a pre-established baseline.
• Optimizing video thumbnails: Images of video that are alongside a link are always from the same source as the link. Marketers can use a similar ratio as above to analyze click-through rates and on-page analysis when ved = xxxxQuAIw.
• Analyzing efficacy of semantic markup: As the occurrences of SERPS that include clickable rich-snippets and knowledge graph elements increase, being able to parse and understand the referrals using ‘ved’ is clear. I have only started looking at results that have rich-snippets, but the initial data suggests that ‘ved’ may even indicate what type event, of rich snippet was clicked. Here are a few examples: (This is one area that could use a lot more research from the community!)

Events Markup: ved = xxxBE0MGM

Music Markup: ved = xxxQ6hEw

• SERP landscape analysis: If you can scrape a Google SERP, you can tell which ‘ved’ elements are on the page and know which verticals are in each. The ‘href’ lives within Java Script so the simplest way to retrieve it is by using a headless browser such PhantomJS.

That about wraps it up for my first — of hopefully many — posts on ‘ved.’ In the months to come, Moz will be collecting Google referral string data on a great number of SERPs for various keywords. We plan to unleash our data hound to sniff out the most useful elements. In the meantime, I would like to use this post as a place for the hacking to begin and the sharing of your thoughts in the comments.

Dig in!

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