Darryl, the man behind dotmailer’s Custom Technical Solutions team

Why did you decide to come to dotmailer?

I first got to know dotmailer when the company was just a bunch of young enthusiastic web developers called Ellipsis Media back in 1999. I was introduced by one of my suppliers and we decided to bring them on board to build a recruitment website for one of our clients. That client was Amnesty International and the job role was Secretary General. Not bad for a Croydon company whose biggest client before that was Scobles the plumber’s merchants. So, I was probably dotmailer’s first ever corporate client! After that, I used dotmailer at each company I worked for and then one day they approached a colleague and me and asked us if we wanted to work for them. That was 2013.  We grabbed the opportunity with both hands and haven’t looked back since.

Tell us a bit about your role

I’m the Global Head of Technical Solutions which actually gives me responsibility for 2 teams. First, Custom Technical Solutions (CTS), who build bespoke applications and tools for customers that allow them to integrate more closely with dotmailer and make life easier. Second, Technical Pre-sales, which spans our 3 territories (EMEA, US and APAC) and works with prospective and existing clients to figure out the best solution and fit within dotmailer.

What accomplishments are you most proud of from your dotmailer time so far?

I would say so far it has to be helping to turn the CTS team from just 2 people into a group of 7 highly skilled and dedicated men and women who have become an intrinsic and valued part of the dotmailer organization. Also I really enjoy being part of the Senior Technical Management team. Here we have the ability to influence the direction and structure of the platform on a daily basis.

Meet Darryl Clark – the cheese and peanut butter sandwich lover

Can you speak a bit about your background and that of your team? What experience and expertise is required to join this team?

My background is quite diverse from a stint in the Army, through design college, web development, business analysis to heading up my current teams. I would say the most valuable skill that I have is being highly analytical. I love nothing more than listening to a client’s requirements and digging deep to work out how we can answer these if not exceed them.

As a team, we love nothing more than brainstorming our ideas. Every member has a valid input and we listen. Everyone has the opportunity to influence what we do and our motto is “there is no such thing as a stupid question.”

To work in my teams you have to be analytical but open minded to the fact that other people may have a better answer than you. Embrace other people’s input and use it to give our clients the best possible solution. We are hugely detail conscious, but have to be acutely aware that we need to tailor what we say to our audience so being able to talk to anyone at any level is hugely valuable.

How much of the dotmailer platform is easily customizable and when does it cross over into something that requires your team’s expertise? How much time is spent on these custom solutions one-time or ongoing?

I’ll let you in on a little secret here. We don’t actually do anything that our customers can’t do with dotmailer given the right knowledge and resources. This is because we build all of our solutions using the dotmailer public API. The API has hundreds of methods in both SOAP and REST versions, which allows you to do a huge amount with the dotmailer platform. We do have a vast amount of experience and knowledge in the team so we may well be able to build a solution quicker than our customers. We are more than happy to help them and their development teams build a solution using us on a consultancy basis to lessen the steepness of the learning curve.

Our aim when building a solution for a customer is that it runs silently in the background and does what it should without any fuss.

What are your plans for the Custom Tech Solutions team going forward?

The great thing about Custom Technical Solutions is you never know what is around the corner as our customers have very diverse needs. What we are concentrating on at the moment is refining our processes to ensure that they are as streamlined as possible and allow us to give as much information to the customer as we can. We are also always looking at the technology and coding approaches that we use to make sure that we build the most innovative and robust solutions.

We are also looking at our external marketing and sharing our knowledge through blogs so keep an eye on the website for our insights.

What are the most common questions that you get when speaking to a prospective customer?

Most questions seem to revolve around reassurance such as “Have you done this before?”, “How safe is my data?”, “What about security?”, “Can you talk to my developers?”, “Do I need to do anything?”.  In most instances, we are the ones asking the questions as we need to find out information as soon as possible so that we can analyse it to ensure that we have the right detail to provide the right solution.

Can you tell us about the dotmailer differentiators you highlight when speaking to prospective customers that seem to really resonate?

We talk a lot about working with best of breed so for example a customer can use our Channel Extensions in automation programs to fire out an SMS to a contact using their existing provider. We don’t force customers down one route, we like to let them decide for themselves.

Also, I really like to emphasize the fact that there is always more than one way to do something within the dotmailer platform. This means we can usually find a way to do something that works for a client within the platform. If not, then we call in CTS to work out if there is a way that we can build something that will — whether this is automating uploads for a small client or mass sending from thousands of child accounts for an enterprise level one.

What do you see as the future of marketing automation technology?  Will one size ever fit all? Or more customization going forward?

The 64 million dollar question. One size will never fit all. Companies and their systems are too organic for that. There isn’t one car that suits every driver or one racquet that suits every sport. Working with a top drawer partner network and building our system to be as open as possible from an integration perspective means that our customers can make dotmailer mold to their business and not the other way round…and adding to that the fact that we are building lots of features in the platform that will blow your socks off.

Tell us a bit about yourself – favorite sports team, favorite food, guilty pleasure, favorite band, favorite vacation spot?

I’m a dyed in the wool Gooner (aka Arsenal Football Club fan) thanks to my Grandfather leading me down the right path as a child. If you are still reading this after that bombshell, then food-wise I pretty much like everything apart from coriander which as far as I’m concerned is the Devils own spawn. I don’t really have a favorite band, but am partial to a bit of Level 42 and Kings of Leon and you will also find me listening to 90s drum and bass and proper old school hip hop. My favorite holiday destination is any decent villa that I can relax in and spend time with my family and I went to Paris recently and loved that. Guilty pleasure – well that probably has to be confessing to liking Coldplay or the fact that my favorite sandwich is peanut butter, cheese and salad cream. Go on try it, you’ll love it.

Want to meet more of the dotmailer team? Say hi to Darren Hockley, Global Head of Support, and Dan Morris, EVP for North America.

Reblogged 3 years ago from blog.dotmailer.com

The Magento Xcelerate program: A positive sum game

As an open source ecommerce platform, Magento is flexible and accessible for developers to work with and as a result, an active community of developers emerged on online forums and at offline meetups all over the world. Many of these were happily plugging away independently of Magento until the split from eBay in early 2015.

Free from the reins of eBay, Magento has decisively been reaching out to, promoting and rewarding the individuals, agencies and technology providers that make up its ecosystem. Last February they announced the Magento Masters Program, empowering the top platform advocates, frequent forum contributors and the innovative solution implementers. Then at April‘s Magento Imagine conference (the largest yet) the theme emerged as ‘We are Magento”, in celebration of the community.

The new Xcelerate Technology Partner Program focuses not on individuals but on business partnerships formed with the technology companies that offer tools for Magento merchants to implement.

 Sharing ideas, opportunities and successes:

This is the Xcelerate Program tagline, which acts as a sort of mission statement to get the technology partners involved moving with regards to continuously considering Magento in their own technology roadmap and jointly communicating successes and learnings from working on implementations with merchants.

“In turn, the program offers members the tools to get moving, through events, resources and contacts. Our goal is to enable you to be an integral part of the Magento ecosystem” Jon Carmody, Head of Technology Partners

The program in practice:

The new program is accompanied by the new Marketplace from which the extensions can be purchased and downloaded. The program splits the extensions into 3 partnership levels:

Registered Partners – these are technology extensions that the new Magento Marketplace team test for code quality. Extensions must now pass this initial level to be eligible for the Marketplace. With each merchant having on average 15 extensions for their site, this is a win for merchants when it comes to extension trustworthiness.

Select Partners – extensions can enter this second tier if the technology falls into one of the strategic categories identified by Magento and if they pass an in-depth technical review. These will be marked as being ‘Select’ in the Marketplace.

Premier Partners – this level is by invitation only, chosen as providing crucial technology to Magento merchants (such as payments, marketing, tax software). The Magento team’s Extension Quality Program looks at coding structure, performance, scalability, security and compatibility but influence in the Community is also a consideration. dotmailer is proud to be the first Premier Technology Partner in the marketing space for Magento.

All in all, the latest move from Magento in illuminating its ecosystem should be positive for all; the merchants who can now choose from a vetted list of extensions and know when to expect tight integration, the technology partners building extensions now with clearer merchant needs/extension gaps in mind and guidance from Magento, and of course the solution implementers recommending the best extension for the merchant now knowing it will be maintained.

Reblogged 3 years ago from blog.dotmailer.com

Why Effective, Modern SEO Requires Technical, Creative, and Strategic Thinking – Whiteboard Friday

Posted by randfish

There’s no doubt that quite a bit has changed about SEO, and that the field is far more integrated with other aspects of online marketing than it once was. In today’s Whiteboard Friday, Rand pushes back against the idea that effective modern SEO doesn’t require any technical expertise, outlining a fantastic list of technical elements that today’s SEOs need to know about in order to be truly effective.

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

Video transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week I’m going to do something unusual. I don’t usually point out these inconsistencies or sort of take issue with other folks’ content on the web, because I generally find that that’s not all that valuable and useful. But I’m going to make an exception here.

There is an article by Jayson DeMers, who I think might actually be here in Seattle — maybe he and I can hang out at some point — called “Why Modern SEO Requires Almost No Technical Expertise.” It was an article that got a shocking amount of traction and attention. On Facebook, it has thousands of shares. On LinkedIn, it did really well. On Twitter, it got a bunch of attention.

Some folks in the SEO world have already pointed out some issues around this. But because of the increasing popularity of this article, and because I think there’s, like, this hopefulness from worlds outside of kind of the hardcore SEO world that are looking to this piece and going, “Look, this is great. We don’t have to be technical. We don’t have to worry about technical things in order to do SEO.”

Look, I completely get the appeal of that. I did want to point out some of the reasons why this is not so accurate. At the same time, I don’t want to rain on Jayson, because I think that it’s very possible he’s writing an article for Entrepreneur, maybe he has sort of a commitment to them. Maybe he had no idea that this article was going to spark so much attention and investment. He does make some good points. I think it’s just really the title and then some of the messages inside there that I take strong issue with, and so I wanted to bring those up.

First off, some of the good points he did bring up.

One, he wisely says, “You don’t need to know how to code or to write and read algorithms in order to do SEO.” I totally agree with that. If today you’re looking at SEO and you’re thinking, “Well, am I going to get more into this subject? Am I going to try investing in SEO? But I don’t even know HTML and CSS yet.”

Those are good skills to have, and they will help you in SEO, but you don’t need them. Jayson’s totally right. You don’t have to have them, and you can learn and pick up some of these things, and do searches, watch some Whiteboard Fridays, check out some guides, and pick up a lot of that stuff later on as you need it in your career. SEO doesn’t have that hard requirement.

And secondly, he makes an intelligent point that we’ve made many times here at Moz, which is that, broadly speaking, a better user experience is well correlated with better rankings.

You make a great website that delivers great user experience, that provides the answers to searchers’ questions and gives them extraordinarily good content, way better than what’s out there already in the search results, generally speaking you’re going to see happy searchers, and that’s going to lead to higher rankings.

But not entirely. There are a lot of other elements that go in here. So I’ll bring up some frustrating points around the piece as well.

First off, there’s no acknowledgment — and I find this a little disturbing — that the ability to read and write code, or even HTML and CSS, which I think are the basic place to start, is helpful or can take your SEO efforts to the next level. I think both of those things are true.

So being able to look at a web page, view source on it, or pull up Firebug in Firefox or something and diagnose what’s going on and then go, “Oh, that’s why Google is not able to see this content. That’s why we’re not ranking for this keyword or term, or why even when I enter this exact sentence in quotes into Google, which is on our page, this is why it’s not bringing it up. It’s because it’s loading it after the page from a remote file that Google can’t access.” These are technical things, and being able to see how that code is built, how it’s structured, and what’s going on there, very, very helpful.

Some coding knowledge also can take your SEO efforts even further. I mean, so many times, SEOs are stymied by the conversations that we have with our programmers and our developers and the technical staff on our teams. When we can have those conversations intelligently, because at least we understand the principles of how an if-then statement works, or what software engineering best practices are being used, or they can upload something into a GitHub repository, and we can take a look at it there, that kind of stuff is really helpful.

Secondly, I don’t like that the article overly reduces all of this information that we have about what we’ve learned about Google. So he mentions two sources. One is things that Google tells us, and others are SEO experiments. I think both of those are true. Although I’d add that there’s sort of a sixth sense of knowledge that we gain over time from looking at many, many search results and kind of having this feel for why things rank, and what might be wrong with a site, and getting really good at that using tools and data as well. There are people who can look at Open Site Explorer and then go, “Aha, I bet this is going to happen.” They can look, and 90% of the time they’re right.

So he boils this down to, one, write quality content, and two, reduce your bounce rate. Neither of those things are wrong. You should write quality content, although I’d argue there are lots of other forms of quality content that aren’t necessarily written — video, images and graphics, podcasts, lots of other stuff.

And secondly, that just doing those two things is not always enough. So you can see, like many, many folks look and go, “I have quality content. It has a low bounce rate. How come I don’t rank better?” Well, your competitors, they’re also going to have quality content with a low bounce rate. That’s not a very high bar.

Also, frustratingly, this really gets in my craw. I don’t think “write quality content” means anything. You tell me. When you hear that, to me that is a totally non-actionable, non-useful phrase that’s a piece of advice that is so generic as to be discardable. So I really wish that there was more substance behind that.

The article also makes, in my opinion, the totally inaccurate claim that modern SEO really is reduced to “the happier your users are when they visit your site, the higher you’re going to rank.”

Wow. Okay. Again, I think broadly these things are correlated. User happiness and rank is broadly correlated, but it’s not a one to one. This is not like a, “Oh, well, that’s a 1.0 correlation.”

I would guess that the correlation is probably closer to like the page authority range. I bet it’s like 0.35 or something correlation. If you were to actually measure this broadly across the web and say like, “Hey, were you happier with result one, two, three, four, or five,” the ordering would not be perfect at all. It probably wouldn’t even be close.

There’s a ton of reasons why sometimes someone who ranks on Page 2 or Page 3 or doesn’t rank at all for a query is doing a better piece of content than the person who does rank well or ranks on Page 1, Position 1.

Then the article suggests five and sort of a half steps to successful modern SEO, which I think is a really incomplete list. So Jayson gives us;

  • Good on-site experience
  • Writing good content
  • Getting others to acknowledge you as an authority
  • Rising in social popularity
  • Earning local relevance
  • Dealing with modern CMS systems (which he notes most modern CMS systems are SEO-friendly)

The thing is there’s nothing actually wrong with any of these. They’re all, generally speaking, correct, either directly or indirectly related to SEO. The one about local relevance, I have some issue with, because he doesn’t note that there’s a separate algorithm for sort of how local SEO is done and how Google ranks local sites in maps and in their local search results. Also not noted is that rising in social popularity won’t necessarily directly help your SEO, although it can have indirect and positive benefits.

I feel like this list is super incomplete. Okay, I brainstormed just off the top of my head in the 10 minutes before we filmed this video a list. The list was so long that, as you can see, I filled up the whole whiteboard and then didn’t have any more room. I’m not going to bother to erase and go try and be absolutely complete.

But there’s a huge, huge number of things that are important, critically important for technical SEO. If you don’t know how to do these things, you are sunk in many cases. You can’t be an effective SEO analyst, or consultant, or in-house team member, because you simply can’t diagnose the potential problems, rectify those potential problems, identify strategies that your competitors are using, be able to diagnose a traffic gain or loss. You have to have these skills in order to do that.

I’ll run through these quickly, but really the idea is just that this list is so huge and so long that I think it’s very, very, very wrong to say technical SEO is behind us. I almost feel like the opposite is true.

We have to be able to understand things like;

  • Content rendering and indexability
  • Crawl structure, internal links, JavaScript, Ajax. If something’s post-loading after the page and Google’s not able to index it, or there are links that are accessible via JavaScript or Ajax, maybe Google can’t necessarily see those or isn’t crawling them as effectively, or is crawling them, but isn’t assigning them as much link weight as they might be assigning other stuff, and you’ve made it tough to link to them externally, and so they can’t crawl it.
  • Disabling crawling and/or indexing of thin or incomplete or non-search-targeted content. We have a bunch of search results pages. Should we use rel=prev/next? Should we robots.txt those out? Should we disallow from crawling with meta robots? Should we rel=canonical them to other pages? Should we exclude them via the protocols inside Google Webmaster Tools, which is now Google Search Console?
  • Managing redirects, domain migrations, content updates. A new piece of content comes out, replacing an old piece of content, what do we do with that old piece of content? What’s the best practice? It varies by different things. We have a whole Whiteboard Friday about the different things that you could do with that. What about a big redirect or a domain migration? You buy another company and you’re redirecting their site to your site. You have to understand things about subdomain structures versus subfolders, which, again, we’ve done another Whiteboard Friday about that.
  • Proper error codes, downtime procedures, and not found pages. If your 404 pages turn out to all be 200 pages, well, now you’ve made a big error there, and Google could be crawling tons of 404 pages that they think are real pages, because you’ve made it a status code 200, or you’ve used a 404 code when you should have used a 410, which is a permanently removed, to be able to get it completely out of the indexes, as opposed to having Google revisit it and keep it in the index.

Downtime procedures. So there’s specifically a… I can’t even remember. It’s a 5xx code that you can use. Maybe it was a 503 or something that you can use that’s like, “Revisit later. We’re having some downtime right now.” Google urges you to use that specific code rather than using a 404, which tells them, “This page is now an error.”

Disney had that problem a while ago, if you guys remember, where they 404ed all their pages during an hour of downtime, and then their homepage, when you searched for Disney World, was, like, “Not found.” Oh, jeez, Disney World, not so good.

  • International and multi-language targeting issues. I won’t go into that. But you have to know the protocols there. Duplicate content, syndication, scrapers. How do we handle all that? Somebody else wants to take our content, put it on their site, what should we do? Someone’s scraping our content. What can we do? We have duplicate content on our own site. What should we do?
  • Diagnosing traffic drops via analytics and metrics. Being able to look at a rankings report, being able to look at analytics connecting those up and trying to see: Why did we go up or down? Did we have less pages being indexed, more pages being indexed, more pages getting traffic less, more keywords less?
  • Understanding advanced search parameters. Today, just today, I was checking out the related parameter in Google, which is fascinating for most sites. Well, for Moz, weirdly, related:oursite.com shows nothing. But for virtually every other sit, well, most other sites on the web, it does show some really interesting data, and you can see how Google is connecting up, essentially, intentions and topics from different sites and pages, which can be fascinating, could expose opportunities for links, could expose understanding of how they view your site versus your competition or who they think your competition is.

Then there are tons of parameters, like in URL and in anchor, and da, da, da, da. In anchor doesn’t work anymore, never mind about that one.

I have to go faster, because we’re just going to run out of these. Like, come on. Interpreting and leveraging data in Google Search Console. If you don’t know how to use that, Google could be telling you, you have all sorts of errors, and you don’t know what they are.

  • Leveraging topic modeling and extraction. Using all these cool tools that are coming out for better keyword research and better on-page targeting. I talked about a couple of those at MozCon, like MonkeyLearn. There’s the new Moz Context API, which will be coming out soon, around that. There’s the Alchemy API, which a lot of folks really like and use.
  • Identifying and extracting opportunities based on site crawls. You run a Screaming Frog crawl on your site and you’re going, “Oh, here’s all these problems and issues.” If you don’t have these technical skills, you can’t diagnose that. You can’t figure out what’s wrong. You can’t figure out what needs fixing, what needs addressing.
  • Using rich snippet format to stand out in the SERPs. This is just getting a better click-through rate, which can seriously help your site and obviously your traffic.
  • Applying Google-supported protocols like rel=canonical, meta description, rel=prev/next, hreflang, robots.txt, meta robots, x robots, NOODP, XML sitemaps, rel=nofollow. The list goes on and on and on. If you’re not technical, you don’t know what those are, you think you just need to write good content and lower your bounce rate, it’s not going to work.
  • Using APIs from services like AdWords or MozScape, or hrefs from Majestic, or SEM refs from SearchScape or Alchemy API. Those APIs can have powerful things that they can do for your site. There are some powerful problems they could help you solve if you know how to use them. It’s actually not that hard to write something, even inside a Google Doc or Excel, to pull from an API and get some data in there. There’s a bunch of good tutorials out there. Richard Baxter has one, Annie Cushing has one, I think Distilled has some. So really cool stuff there.
  • Diagnosing page load speed issues, which goes right to what Jayson was talking about. You need that fast-loading page. Well, if you don’t have any technical skills, you can’t figure out why your page might not be loading quickly.
  • Diagnosing mobile friendliness issues
  • Advising app developers on the new protocols around App deep linking, so that you can get the content from your mobile apps into the web search results on mobile devices. Awesome. Super powerful. Potentially crazy powerful, as mobile search is becoming bigger than desktop.

Okay, I’m going to take a deep breath and relax. I don’t know Jayson’s intention, and in fact, if he were in this room, he’d be like, “No, I totally agree with all those things. I wrote the article in a rush. I had no idea it was going to be big. I was just trying to make the broader points around you don’t have to be a coder in order to do SEO.” That’s completely fine.

So I’m not going to try and rain criticism down on him. But I think if you’re reading that article, or you’re seeing it in your feed, or your clients are, or your boss is, or other folks are in your world, maybe you can point them to this Whiteboard Friday and let them know, no, that’s not quite right. There’s a ton of technical SEO that is required in 2015 and will be for years to come, I think, that SEOs have to have in order to be effective at their jobs.

All right, everyone. Look forward to some great comments, and we’ll see you again next time for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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Reblogged 4 years ago from tracking.feedpress.it

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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Reblogged 4 years ago from tracking.feedpress.it

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

​The 3 Most Common SEO Problems on Listings Sites

Posted by Dom-Woodman

Listings sites have a very specific set of search problems that you don’t run into everywhere else. In the day I’m one of Distilled’s analysts, but by night I run a job listings site, teflSearch. So, for my first Moz Blog post I thought I’d cover the three search problems with listings sites that I spent far too long agonising about.

Quick clarification time: What is a listings site (i.e. will this post be useful for you)?

The classic listings site is Craigslist, but plenty of other sites act like listing sites:

  • Job sites like Monster
  • E-commerce sites like Amazon
  • Matching sites like Spareroom

1. Generating quality landing pages

The landing pages on listings sites are incredibly important. These pages are usually the primary drivers of converting traffic, and they’re usually generated automatically (or are occasionally custom category pages) .

For example, if I search “Jobs in Manchester“, you can see nearly every result is an automatically generated landing page or category page.

There are three common ways to generate these pages (occasionally a combination of more than one is used):

  • Faceted pages: These are generated by facets—groups of preset filters that let you filter the current search results. They usually sit on the left-hand side of the page.
  • Category pages: These pages are listings which have already had a filter applied and can’t be changed. They’re usually custom pages.
  • Free-text search pages: These pages are generated by a free-text search box.

Those definitions are still bit general; let’s clear them up with some examples:

Amazon uses a combination of categories and facets. If you click on browse by department you can see all the category pages. Then on each category page you can see a faceted search. Amazon is so large that it needs both.

Indeed generates its landing pages through free text search, for example if we search for “IT jobs in manchester” it will generate: IT jobs in manchester.

teflSearch generates landing pages using just facets. The jobs in China landing page is simply a facet of the main search page.

Each method has its own search problems when used for generating landing pages, so lets tackle them one by one.


Aside

Facets and free text search will typically generate pages with parameters e.g. a search for “dogs” would produce:

www.mysite.com?search=dogs

But to make the URL user friendly sites will often alter the URLs to display them as folders

www.mysite.com/results/dogs/

These are still just ordinary free text search and facets, the URLs are just user friendly. (They’re a lot easier to work with in robots.txt too!)


Free search (& category) problems

If you’ve decided the base of your search will be a free text search, then we’ll have two major goals:

  • Goal 1: Helping search engines find your landing pages
  • Goal 2: Giving them link equity.

Solution

Search engines won’t use search boxes and so the solution to both problems is to provide links to the valuable landing pages so search engines can find them.

There are plenty of ways to do this, but two of the most common are:

  • Category links alongside a search

    Photobucket uses a free text search to generate pages, but if we look at example search for photos of dogs, we can see the categories which define the landing pages along the right-hand side. (This is also an example of URL friendly searches!)

  • Putting the main landing pages in a top-level menu

    Indeed also uses free text to generate landing pages, and they have a browse jobs section which contains the URL structure to allow search engines to find all the valuable landing pages.

Breadcrumbs are also often used in addition to the two above and in both the examples above, you’ll find breadcrumbs that reinforce that hierarchy.

Category (& facet) problems

Categories, because they tend to be custom pages, don’t actually have many search disadvantages. Instead it’s the other attributes that make them more or less desirable. You can create them for the purposes you want and so you typically won’t have too many problems.

However, if you also use a faceted search in each category (like Amazon) to generate additional landing pages, then you’ll run into all the problems described in the next section.

At first facets seem great, an easy way to generate multiple strong relevant landing pages without doing much at all. The problems appear because people don’t put limits on facets.

Lets take the job page on teflSearch. We can see it has 18 facets each with many options. Some of these options will generate useful landing pages:

The China facet in countries will generate “Jobs in China” that’s a useful landing page.

On the other hand, the “Conditional Bonus” facet will generate “Jobs with a conditional bonus,” and that’s not so great.

We can also see that the options within a single facet aren’t always useful. As of writing, I have a single job available in Serbia. That’s not a useful search result, and the poor user engagement combined with the tiny amount of content will be a strong signal to Google that it’s thin content. Depending on the scale of your site it’s very easy to generate a mass of poor-quality landing pages.

Facets generate other problems too. The primary one being they can create a huge amount of duplicate content and pages for search engines to get lost in. This is caused by two things: The first is the sheer number of possibilities they generate, and the second is because selecting facets in different orders creates identical pages with different URLs.

We end up with four goals for our facet-generated landing pages:

  • Goal 1: Make sure our searchable landing pages are actually worth landing on, and that we’re not handing a mass of low-value pages to the search engines.
  • Goal 2: Make sure we don’t generate multiple copies of our automatically generated landing pages.
  • Goal 3: Make sure search engines don’t get caught in the metaphorical plastic six-pack rings of our facets.
  • Goal 4: Make sure our landing pages have strong internal linking.

The first goal needs to be set internally; you’re always going to be the best judge of the number of results that need to present on a page in order for it to be useful to a user. I’d argue you can rarely ever go below three, but it depends both on your business and on how much content fluctuates on your site, as the useful landing pages might also change over time.

We can solve the next three problems as group. There are several possible solutions depending on what skills and resources you have access to; here are two possible solutions:

Category/facet solution 1: Blocking the majority of facets and providing external links
  • Easiest method
  • Good if your valuable category pages rarely change and you don’t have too many of them.
  • Can be problematic if your valuable facet pages change a lot

Nofollow all your facet links, and noindex and block category pages which aren’t valuable or are deeper than x facet/folder levels into your search using robots.txt.

You set x by looking at where your useful facet pages exist that have search volume. So, for example, if you have three facets for televisions: manufacturer, size, and resolution, and even combinations of all three have multiple results and search volume, then you could set you index everything up to three levels.

On the other hand, if people are searching for three levels (e.g. “Samsung 42″ Full HD TV”) but you only have one or two results for three-level facets, then you’d be better off indexing two levels and letting the product pages themselves pick up long-tail traffic for the third level.

If you have valuable facet pages that exist deeper than 1 facet or folder into your search, then this creates some duplicate content problems dealt with in the aside “Indexing more than 1 level of facets” below.)

The immediate problem with this set-up, however, is that in one stroke we’ve removed most of the internal links to our category pages, and by no-following all the facet links, search engines won’t be able to find your valuable category pages.

In order re-create the linking, you can add a top level drop down menu to your site containing the most valuable category pages, add category links elsewhere on the page, or create a separate part of the site with links to the valuable category pages.

The top level drop down menu you can see on teflSearch (it’s the search jobs menu), the other two examples are demonstrated in Photobucket and Indeed respectively in the previous section.

The big advantage for this method is how quick it is to implement, it doesn’t require any fiddly internal logic and adding an extra menu option is usually minimal effort.

Category/facet solution 2: Creating internal logic to work with the facets

  • Requires new internal logic
  • Works for large numbers of category pages with value that can change rapidly

There are four parts to the second solution:

  1. Select valuable facet categories and allow those links to be followed. No-follow the rest.
  2. No-index all pages that return a number of items below the threshold for a useful landing page
  3. No-follow all facets on pages with a search depth greater than x.
  4. Block all facet pages deeper than x level in robots.txt

As with the last solution, x is set by looking at where your useful facet pages exist that have search volume (full explanation in the first solution), and if you’re indexing more than one level you’ll need to check out the aside below to see how to deal with the duplicate content it generates.


Aside: Indexing more than one level of facets

If you want more than one level of facets to be indexable, then this will create certain problems.

Suppose you have a facet for size:

  • Televisions: Size: 46″, 44″, 42″

And want to add a brand facet:

  • Televisions: Brand: Samsung, Panasonic, Sony

This will create duplicate content because the search engines will be able to follow your facets in both orders, generating:

  • Television – 46″ – Samsung
  • Television – Samsung – 46″

You’ll have to either rel canonical your duplicate pages with another rule or set up your facets so they create a single unique URL.

You also need to be aware that each followable facet you add will multiply with each other followable facet and it’s very easy to generate a mass of pages for search engines to get stuck in. Depending on your setup you might need to block more paths in robots.txt or set-up more logic to prevent them being followed.

Letting search engines index more than one level of facets adds a lot of possible problems; make sure you’re keeping track of them.


2. User-generated content cannibalization

This is a common problem for listings sites (assuming they allow user generated content). If you’re reading this as an e-commerce site who only lists their own products, you can skip this one.

As we covered in the first area, category pages on listings sites are usually the landing pages aiming for the valuable search terms, but as your users start generating pages they can often create titles and content that cannibalise your landing pages.

Suppose you’re a job site with a category page for PHP Jobs in Greater Manchester. If a recruiter then creates a job advert for PHP Jobs in Greater Manchester for the 4 positions they currently have, you’ve got a duplicate content problem.

This is less of a problem when your site is large and your categories mature, it will be obvious to any search engine which are your high value category pages, but at the start where you’re lacking authority and individual listings might contain more relevant content than your own search pages this can be a problem.

Solution 1: Create structured titles

Set the <title> differently than the on-page title. Depending on variables you have available to you can set the title tag programmatically without changing the page title using other information given by the user.

For example, on our imaginary job site, suppose the recruiter also provided the following information in other fields:

  • The no. of positions: 4
  • The primary area: PHP Developer
  • The name of the recruiting company: ABC Recruitment
  • Location: Manchester

We could set the <title> pattern to be: *No of positions* *The primary area* with *recruiter name* in *Location* which would give us:

4 PHP Developers with ABC Recruitment in Manchester

Setting a <title> tag allows you to target long-tail traffic by constructing detailed descriptive titles. In our above example, imagine the recruiter had specified “Castlefield, Manchester” as the location.

All of a sudden, you’ve got a perfect opportunity to pick up long-tail traffic for people searching in Castlefield in Manchester.

On the downside, you lose the ability to pick up long-tail traffic where your users have chosen keywords you wouldn’t have used.

For example, suppose Manchester has a jobs program called “Green Highway.” A job advert title containing “Green Highway” might pick up valuable long-tail traffic. Being able to discover this, however, and find a way to fit it into a dynamic title is very hard.

Solution 2: Use regex to noindex the offending pages

Perform a regex (or string contains) search on your listings titles and no-index the ones which cannabalise your main category pages.

If it’s not possible to construct titles with variables or your users provide a lot of additional long-tail traffic with their own titles, then is a great option. On the downside, you miss out on possible structured long-tail traffic that you might’ve been able to aim for.

Solution 3: De-index all your listings

It may seem rash, but if you’re a large site with a huge number of very similar or low-content listings, you might want to consider this, but there is no common standard. Some sites like Indeed choose to no-index all their job adverts, whereas some other sites like Craigslist index all their individual listings because they’ll drive long tail traffic.

Don’t de-index them all lightly!

3. Constantly expiring content

Our third and final problem is that user-generated content doesn’t last forever. Particularly on listings sites, it’s constantly expiring and changing.

For most use cases I’d recommend 301’ing expired content to a relevant category page, with a message triggered by the redirect notifying the user of why they’ve been redirected. It typically comes out as the best combination of search and UX.

For more information or advice on how to deal with the edge cases, there’s a previous Moz blog post on how to deal with expired content which I think does an excellent job of covering this area.

Summary

In summary, if you’re working with listings sites, all three of the following need to be kept in mind:

  • How are the landing pages generated? If they’re generated using free text or facets have the potential problems been solved?
  • Is user generated content cannibalising the main landing pages?
  • How has constantly expiring content been dealt with?

Good luck listing, and if you’ve had any other tricky problems or solutions you’ve come across working on listings sites lets chat about them in the comments below!

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