How to Rid Your Website of Six Common Google Analytics Headaches

Posted by amandaecking

I’ve been in and out of Google Analytics (GA) for the past five or so years agency-side. I’ve seen three different code libraries, dozens of new different features and reports roll out, IP addresses stop being reported, and keywords not-so-subtly phased out of the free platform.

Analytics has been a focus of mine for the past year or so—mainly, making sure clients get their data right. Right now, our new focus is closed loop tracking, but that’s a topic for another day. If you’re using Google Analytics, and only Google Analytics for the majority of your website stats, or it’s your primary vehicle for analysis, you need to make sure it’s accurate.

Not having data pulling in or reporting properly is like building a house on a shaky foundation: It doesn’t end well. Usually there are tears.

For some reason, a lot of people, including many of my clients, assume everything is tracking properly in Google Analytics… because Google. But it’s not Google who sets up your analytics. People do that. And people are prone to make mistakes.

I’m going to go through six scenarios where issues are commonly encountered with Google Analytics.

I’ll outline the remedy for each issue, and in the process, show you how to move forward with a diagnosis or resolution.

1. Self-referrals

This is probably one of the areas we’re all familiar with. If you’re seeing a lot of traffic from your own domain, there’s likely a problem somewhere—or you need to extend the default session length in Google Analytics. (For example, if you have a lot of long videos or music clips and don’t use event tracking; a website like TEDx or SoundCloud would be a good equivalent.)

Typically one of the first things I’ll do to help diagnose the problem is include an advanced filter to show the full referrer string. You do this by creating a filter, as shown below:

Filter Type: Custom filter > Advanced
Field A: Hostname
Extract A: (.*)
Field B: Request URI
Extract B: (.*)
Output To: Request URI
Constructor: $A1$B1

You’ll then start seeing the subdomains pulling in. Experience has shown me that if you have a separate subdomain hosted in another location (say, if you work with a separate company and they host and run your mobile site or your shopping cart), it gets treated by Google Analytics as a separate domain. Thus, you ‘ll need to implement cross domain tracking. This way, you can narrow down whether or not it’s one particular subdomain that’s creating the self-referrals.

In this example below, we can see all the revenue is being reported to the booking engine (which ended up being cross domain issues) and their own site is the fourth largest traffic source:

I’ll also a good idea to check the browser and device reports to start narrowing down whether the issue is specific to a particular element. If it’s not, keep digging. Look at pages pulling the self-referrals and go through the code with a fine-tooth comb, drilling down as much as you can.

2. Unusually low bounce rate

If you have a crazy-low bounce rate, it could be too good to be true. Unfortunately. An unusually low bounce rate could (and probably does) mean that at least on some pages of your website have the same Google Analytics tracking code installed twice.

Take a look at your source code, or use Google Tag Assistant (though it does have known bugs) to see if you’ve got GA tracking code installed twice.

While I tell clients having Google Analytics installed on the same page can lead to double the pageviews, I’ve not actually encountered that—I usually just say it to scare them into removing the duplicate implementation more quickly. Don’t tell on me.

3. Iframes anywhere

I’ve heard directly from Google engineers and Google Analytics evangelists that Google Analytics does not play well with iframes, and that it will never will play nice with this dinosaur technology.

If you track the iframe, you inflate your pageviews, plus you still aren’t tracking everything with 100% clarity.

If you don’t track across iframes, you lose the source/medium attribution and everything becomes a self-referral.

Damned if you do; damned if you don’t.

My advice: Stop using iframes. They’re Netscape-era technology anyway, with rainbow marquees and Comic Sans on top. Interestingly, and unfortunately, a number of booking engines (for hotels) and third-party carts (for ecommerce) still use iframes.

If you have any clients in those verticals, or if you’re in the vertical yourself, check with your provider to see if they use iframes. Or you can check for yourself, by right-clicking as close as you can to the actual booking element:

iframe-booking.png

There is no neat and tidy way to address iframes with Google Analytics, and usually iframes are not the only complicated element of setup you’ll encounter. I spent eight months dealing with a website on a subfolder, which used iframes and had a cross domain booking system, and the best visibility I was able to get was about 80% on a good day.

Typically, I’d approach diagnosing iframes (if, for some reason, I had absolutely no access to viewing a website or talking to the techs) similarly to diagnosing self-referrals, as self-referrals are one of the biggest symptoms of iframe use.

4. Massive traffic jumps

Massive jumps in traffic don’t typically just happen. (Unless, maybe, you’re Geraldine.) There’s always an explanation—a new campaign launched, you just turned on paid ads for the first time, you’re using content amplification platforms, you’re getting a ton of referrals from that recent press in The New York Times. And if you think it just happened, it’s probably a technical glitch.

I’ve seen everything from inflated pageviews result from including tracking on iframes and unnecessary implementation of virtual pageviews, to not realizing the tracking code was installed on other microsites for the same property. Oops.

Usually I’ve seen this happen when the tracking code was somewhere it shouldn’t be, so if you’re investigating a situation of this nature, first confirm the Google Analytics code is only in the places it needs to be.Tools like Google Tag Assistant and Screaming Frog can be your BFFs in helping you figure this out.

Also, I suggest bribing the IT department with sugar (or booze) to see if they’ve changed anything lately.

5. Cross-domain tracking

I wish cross-domain tracking with Google Analytics out of the box didn’t require any additional setup. But it does.

If you don’t have it set up properly, things break down quickly, and can be quite difficult to untangle.

The older the GA library you’re using, the harder it is. The easiest setup, by far, is Google Tag Manager with Universal Analytics. Hard-coded universal analytics is a bit more difficult because you have to implement autoLink manually and decorate forms, if you’re using them (and you probably are). Beyond that, rather than try and deal with it, I say update your Google Analytics code. Then we can talk.

Where I’ve seen the most murkiness with tracking is when parts of cross domain tracking are implemented, but not all. For some reason, if allowLinker isn’t included, or you forget to decorate all the forms, the cookies aren’t passed between domains.

The absolute first place I would start with this would be confirming the cookies are all passing properly at all the right points, forms, links, and smoke signals. I’ll usually use a combination of the Real Time report in Google Analytics, Google Tag Assistant, and GA debug to start testing this. Any debug tool you use will mean you’re playing in the console, so get friendly with it.

6. Internal use of UTM strings

I’ve saved the best for last. Internal use of campaign tagging. We may think, oh, I use Google to tag my campaigns externally, and we’ve got this new promotion on site which we’re using a banner ad for. That’s a campaign. Why don’t I tag it with a UTM string?

Step away from the keyboard now. Please.

When you tag internal links with UTM strings, you override the original source/medium. So that visitor who came in through your paid ad and then who clicks on the campaign banner has now been manually tagged. You lose the ability to track that they came through on the ad the moment they click on the tagged internal link. Their source and medium is now your internal campaign, not that paid ad you’re spending gobs of money on and have to justify to your manager. See the problem?

I’ve seen at least three pretty spectacular instances of this in the past year, and a number of smaller instances of it. Annie Cushing also talks about the evils of internal UTM tags and the odd prevalence of it. (Oh, and if you haven’t explored her blog, and the amazing spreadsheets she shares, please do.)

One clothing company I worked with tagged all of their homepage offers with UTM strings, which resulted in the loss of visibility for one-third of their audience: One million visits over the course of a year, and $2.1 million in lost revenue.

Let me say that again. One million visits, and $2.1 million. That couldn’t be attributed to an external source/campaign/spend.

Another client I audited included campaign tagging on nearly every navigational element on their website. It still gives me nightmares.

If you want to see if you have any internal UTM strings, head straight to the Campaigns report in Acquisition in Google Analytics, and look for anything like “home” or “navigation” or any language you may use internally to refer to your website structure.

And if you want to see how users are moving through your website, go to the Flow reports. Or if you really, really, really want to know how many people click on that sidebar link, use event tracking. But please, for the love of all things holy (and to keep us analytics lovers from throwing our computers across the room), stop using UTM tagging on your internal links.

Now breathe and smile

Odds are, your Google Analytics setup is fine. If you are seeing any of these issues, though, you have somewhere to start in diagnosing and addressing the data.

We’ve looked at six of the most common points of friction I’ve encountered with Google Analytics and how to start investigating them: self-referrals, bounce rate, iframes, traffic jumps, cross domain tracking and internal campaign tagging.

What common data integrity issues have you encountered with Google Analytics? What are your favorite tools to investigate?

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Eliminate Duplicate Content in Faceted Navigation with Ajax/JSON/JQuery

Posted by EricEnge

One of the classic problems in SEO is that while complex navigation schemes may be useful to users, they create problems for search engines. Many publishers rely on tags such as rel=canonical, or the parameters settings in Webmaster Tools to try and solve these types of issues. However, each of the potential solutions has limitations. In today’s post, I am going to outline how you can use JavaScript solutions to more completely eliminate the problem altogether.

Note that I am not going to provide code examples in this post, but I am going to outline how it works on a conceptual level. If you are interested in learning more about Ajax/JSON/jQuery here are some resources you can check out:

  1. Ajax Tutorial
  2. Learning Ajax/jQuery

Defining the problem with faceted navigation

Having a page of products and then allowing users to sort those products the way they want (sorted from highest to lowest price), or to use a filter to pick a subset of the products (only those over $60) makes good sense for users. We typically refer to these types of navigation options as “faceted navigation.”

However, faceted navigation can cause problems for search engines because they don’t want to crawl and index all of your different sort orders or all your different filtered versions of your pages. They would end up with many different variants of your pages that are not significantly different from a search engine user experience perspective.

Solutions such as rel=canonical tags and parameters settings in Webmaster Tools have some limitations. For example, rel=canonical tags are considered “hints” by the search engines, and they may not choose to accept them, and even if they are accepted, they do not necessarily keep the search engines from continuing to crawl those pages.

A better solution might be to use JSON and jQuery to implement your faceted navigation so that a new page is not created when a user picks a filter or a sort order. Let’s take a look at how it works.

Using JSON and jQuery to filter on the client side

The main benefit of the implementation discussed below is that a new URL is not created when a user is on a page of yours and applies a filter or sort order. When you use JSON and jQuery, the entire process happens on the client device without involving your web server at all.

When a user initially requests one of the product pages on your web site, the interaction looks like this:

using json on faceted navigation

This transfers the page to the browser the user used to request the page. Now when a user picks a sort order (or filter) on that page, here is what happens:

jquery and faceted navigation diagram

When the user picks one of those options, a jQuery request is made to the JSON data object. Translation: the entire interaction happens within the client’s browser and the sort or filter is applied there. Simply put, the smarts to handle that sort or filter resides entirely within the code on the client device that was transferred with the initial request for the page.

As a result, there is no new page created and no new URL for Google or Bing to crawl. Any concerns about crawl budget or inefficient use of PageRank are completely eliminated. This is great stuff! However, there remain limitations in this implementation.

Specifically, if your list of products spans multiple pages on your site, the sorting and filtering will only be applied to the data set already transferred to the user’s browser with the initial request. In short, you may only be sorting the first page of products, and not across the entire set of products. It’s possible to have the initial JSON data object contain the full set of pages, but this may not be a good idea if the page size ends up being large. In that event, we will need to do a bit more.

What Ajax does for you

Now we are going to dig in slightly deeper and outline how Ajax will allow us to handle sorting, filtering, AND pagination. Warning: There is some tech talk in this section, but I will try to follow each technical explanation with a layman’s explanation about what’s happening.

The conceptual Ajax implementation looks like this:

ajax and faceted navigation diagram

In this structure, we are using an Ajax layer to manage the communications with the web server. Imagine that we have a set of 10 pages, the user has gotten the first page of those 10 on their device and then requests a change to the sort order. The Ajax requests a fresh set of data from the web server for your site, similar to a normal HTML transaction, except that it runs asynchronously in a separate thread.

If you don’t know what that means, the benefit is that the rest of the page can load completely while the process to capture the data that the Ajax will display is running in parallel. This will be things like your main menu, your footer links to related products, and other page elements. This can improve the perceived performance of the page.

When a user selects a different sort order, the code registers an event handler for a given object (e.g. HTML Element or other DOM objects) and then executes an action. The browser will perform the action in a different thread to trigger the event in the main thread when appropriate. This happens without needing to execute a full page refresh, only the content controlled by the Ajax refreshes.

To translate this for the non-technical reader, it just means that we can update the sort order of the page, without needing to redraw the entire page, or change the URL, even in the case of a paginated sequence of pages. This is a benefit because it can be faster than reloading the entire page, and it should make it clear to search engines that you are not trying to get some new page into their index.

Effectively, it does this within the existing Document Object Model (DOM), which you can think of as the basic structure of the documents and a spec for the way the document is accessed and manipulated.

How will Google handle this type of implementation?

For those of you who read Adam Audette’s excellent recent post on the tests his team performed on how Google reads Javascript, you may be wondering if Google will still load all these page variants on the same URL anyway, and if they will not like it.

I had the same question, so I reached out to Google’s Gary Illyes to get an answer. Here is the dialog that transpired:

Eric Enge: I’d like to ask you about using JSON and jQuery to render different sort orders and filters within the same URL. I.e. the user selects a sort order or a filter, and the content is reordered and redrawn on the page on the client site. Hence no new URL would be created. It’s effectively a way of canonicalizing the content, since each variant is a strict subset.

Then there is a second level consideration with this approach, which involves doing the same thing with pagination. I.e. you have 10 pages of products, and users still have sorting and filtering options. In order to support sorting and filtering across the entire 10 page set, you use an Ajax solution, so all of that still renders on one URL.

So, if you are on page 1, and a user executes a sort, they get that all back in that one page. However, to do this right, going to page 2 would also render on the same URL. Effectively, you are taking the 10 page set and rendering it all within one URL. This allows sorting, filtering, and pagination without needing to use canonical, noindex, prev/next, or robots.txt.

If this was not problematic for Google, the only downside is that it makes the pagination not visible to Google. Does that make sense, or is it a bad idea?

Gary Illyes
: If you have one URL only, and people have to click on stuff to see different sort orders or filters for the exact same content under that URL, then typically we would only see the default content.

If you don’t have pagination information, that’s not a problem, except we might not see the content on the other pages that are not contained in the HTML within the initial page load. The meaning of rel-prev/next is to funnel the signals from child pages (page 2, 3, 4, etc.) to the group of pages as a collection, or to the view-all page if you have one. If you simply choose to render those paginated versions on a single URL, that will have the same impact from a signals point of view, meaning that all signals will go to a single entity, rather than distributed to several URLs.

Summary

Keep in mind, the reason why Google implemented tags like rel=canonical, NoIndex, rel=prev/next, and others is to reduce their crawling burden and overall page bloat and to help focus signals to incoming pages in the best way possible. The use of Ajax/JSON/jQuery as outlined above does this simply and elegantly.

On most e-commerce sites, there are many different “facets” of how a user might want to sort and filter a list of products. With the Ajax-style implementation, this can be done without creating new pages. The end users get the control they are looking for, the search engines don’t have to deal with excess pages they don’t want to see, and signals in to the site (such as links) are focused on the main pages where they should be.

The one downside is that Google may not see all the content when it is paginated. A site that has lots of very similar products in a paginated list does not have to worry too much about Google seeing all the additional content, so this isn’t much of a concern if your incremental pages contain more of what’s on the first page. Sites that have content that is materially different on the additional pages, however, might not want to use this approach.

These solutions do require Javascript coding expertise but are not really that complex. If you have the ability to consider a path like this, you can free yourself from trying to understand the various tags, their limitations, and whether or not they truly accomplish what you are looking for.

Credit: Thanks for Clark Lefavour for providing a review of the above for technical correctness.

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Reblogged 3 years ago from tracking.feedpress.it

​Inbound Lead Generation: eCommerce Marketing’s Missing Link

Posted by Everett

If eCommerce businesses hope to remain competitive with Amazon, eBay, big box brands, and other online retail juggernauts, they’ll need to learn how to conduct content marketing, lead generation, and contact nurturing as part of a comprehensive inbound marketing strategy.

First, I will discuss some of the ways most online retailers are approaching email from the bottom of the funnel upward, and why this needs to be turned around. Then we can explore how to go about doing this within the framework of “Inbound Marketing” for eCommerce businesses. Lastly, popular marketing automation and email marketing solutions are discussed in the context of inbound marketing for eCommerce.

Key differences between eCommerce and lead generation approaches to email

Different list growth strategies

Email acquisition sources differ greatly between lead gen. sites and online stores. The biggest driver of email acquisition for most eCommerce businesses are their shoppers, especially when the business doesn’t collect an email address for their contact database until the shopper provides it during the check-out process—possibly, not until the very end.

With most B2B/B2C lead gen. websites, the entire purpose of every landing page is to get visitors to submit a contact form or pick up the phone. Often, the price tag for their products or services is much higher than those of an eCommerce site or involves recurring payments. In other words, what they’re selling is more difficult to sell. People take longer to make those purchasing decisions. For this reason, leads—in the form of contact names and email addresses—are typically acquired and nurtured without having first become a customer.

Contacts vs. leads

Whether it is a B2B or B2C website, lead gen. contacts (called leads) are thought of as potential customers (clients, subscribers, patients) who need to be nurtured to the point of becoming “sales qualified,” meaning they’ll eventually get a sales call or email that attempts to convert them into a customer.

On the other hand, eCommerce contacts are often thought of primarily as existing customers to whom the marketing team can blast coupons and other offers by email.

Retail sites typically don’t capture leads at the top or middle of the funnel. Only once a shopper has checked out do they get added to the list. Historically, the buying cycle has been short enough that eCommerce sites could move many first-time visitors directly to customers in a single visit.
But this has changed.

Unless your brand is very strong—possibly a luxury brand or one with an offline retail presence—it is probably getting more difficult (i.e. expensive) to acquire new customers. At the same time, attrition rates are rising. Conversion optimization helps by converting more bottom of the funnel visitors. SEO helps drive more traffic into the site, but mostly for middle-of-funnel (category page) and bottom-of-funnel (product page) visitors who may not also be price/feature comparison shopping, or are unable to convert right away because of device or time limitations.

Even savvy retailers publishing content for shoppers higher up in the funnel, such as buyer guides and reviews, aren’t getting an email address and are missing a lot of opportunities because of it.

attract-convert-grow-funnel-inflow-2.jpg

Here’s a thought. If your eCommerce site has a 10 percent conversion rate, you’re doing pretty good by most standards. But what happened to the other 90 percent of those visitors? Will you have the opportunity to connect with them again? Even if you bump that up a few percentage points with retargeting, a lot of potential revenue has seeped out of your funnel without a trace.

I don’t mean to bash the eCommerce marketing community with generalizations. Most lead gen. sites aren’t doing anything spectacular either, and a lot of opportunity is missed all around.

There are many eCommerce brands doing great things marketing-wise. I’m a big fan of
Crutchfield for their educational resources targeting early-funnel traffic, and Neman Tools, Saddleback Leather and Feltraiger for the stories they tell. Amazon is hard to beat when it comes to scalability, product suggestions and user-generated reviews.

Sadly, most eCommerce sites (including many of the major household brands) still approach marketing in this way…

The ol’ bait n’ switch: promising value and delivering spam

Established eCommerce brands have gigantic mailing lists (compared with lead gen. counterparts), to whom they typically send out at least one email each week with “offers” like free shipping, $ off, buy-one-get-one, or % off their next purchase. The lists are minimally segmented, if at all. For example, there might be lists for repeat customers, best customers, unresponsive contacts, recent purchasers, shoppers with abandoned carts, purchases by category, etc.

The missing points of segmentation include which campaign resulted in the initial contact (sometimes referred to as a cohort) and—most importantly—the persona and buying cycle stage that best applies to each contact.

Online retailers often send frequent “blasts” to their entire list or to a few of the large segments mentioned above. Lack of segmentation means contacts aren’t receiving emails based on their interests, problems, or buying cycle stage, but instead, are receiving what they perceive as “generic” emails.

The result of these missing segments and the lack of overarching strategy looks something like this:

My, What a Big LIST You Have!

iStock_000017047747Medium.jpg

TIME reported in 2012 on stats from Responsys that the average online retailer sent out between five and six emails the week after Thanksgiving. Around the same time, the Wall Street Journal reported that the top 100 online retailers sent an average of 177 emails apiece to each of their contacts in 2011. Averaged out, that’s somewhere between three and four emails each week that the contact is receiving from these retailers.

The better to SPAM you with!

iStock_000016088853Medium.jpg

A 2014 whitepaper from SimpleRelevance titled
Email Fail: An In-Depth Evaluation of Top 20 Internet Retailer’s Email Personalization Capabilities (
PDF) found that, while 70 percent of marketing executives believed personalization was of “utmost importance” to their business…

“Only 17 percent of marketing leaders are going beyond basic transactional data to deliver personalized messages to consumers.”

Speaking of email overload, the same report found that some major online retailers sent ten or more emails per week!

simplerelevance-email-report-frequency.png

The result?

All too often, the eCommerce business will carry around big, dead lists of contacts who don’t even bother reading their emails anymore. They end up scrambling toward other channels to “drive more demand,” but because the real problems were never addressed, this ends up increasing new customer acquisition costs.

The cycle looks something like this:

  1. Spend a fortune driving in unqualified traffic from top-of-the-funnel channels
  2. Ignore the majority of those visitors who aren’t ready to purchase
  3. Capture email addresses only for the few visitors who made a purchase
  4. Spam the hell out of those people until they unsubscribe
  5. Spend a bunch more money trying to fill the top of the funnel with even more traffic

It’s like trying to fill your funnel with a bucket full of holes, some of them patched with band-aids.

The real problems

  1. Lack of a cohesive strategy across marketing channels
  2. Lack of a cohesive content strategy throughout all stages of the buying cycle
  3. Lack of persona, buying cycle stage, and cohort-based list segmentation to nurture contacts
  4. Lack of tracking across customer touchpoints and devices
  5. Lack of gated content that provides enough value to early-funnel visitors to get them to provide their email address

So, what’s the answer?

Inbound marketing allows online retailers to stop competing with Amazon and other “price focused” competitors with leaky funnels, and to instead focus on:

  1. Persona-based content marketing campaigns designed to acquire email addresses from high-quality leads (potential customers) by offering them the right content for each stage in their buyer’s journey
  2. A robust marketing automation system that makes true personalization scalable
  3. Automated contact nurturing emails triggered by certain events, such as viewing specific content, abandoning their shopping cart, adding items to their wish list or performing micro-conversions like downloading a look book
  4. Intelligent SMM campaigns that match visitors and customers with social accounts by email addresses, interests and demographics—as well as social monitoring
  5. Hyper-segmented email contact lists to support the marketing automation described above, as well as to provide highly-customized email and shopping experiences
  6. Cross-channel, closed loop reporting to provide a complete “omnichannel” view of online marketing efforts and how they assist offline conversions, if applicable

Each of these areas will be covered in more detail below. First, let’s take a quick step back and define what it is we’re talking about here.

Inbound marketing: a primer

A lot of people think “inbound marketing” is just a way some SEO agencies are re-cloaking themselves to avoid negative associations with search engine optimization. Others think it’s synonymous with “internet marketing.” I think it goes more like this:

Inbound marketing is to Internet marketing as SEO is to inbound marketing: One piece of a larger whole.

There are many ways to define inbound marketing. A cursory review of definitions from several trusted sources reveals some fundamental similarities :

Rand Fishkin

randfishkin.jpeg

“Inbound Marketing is the practice of earning traffic and attention for your business on the web rather than buying it or interrupting people to get it. Inbound channels include organic search, social media, community-building content, opt-in email, word of mouth, and many others. Inbound marketing is particularly powerful because it appeals to what people are looking for and what they want, rather than trying to get between them and what they’re trying to do with advertising. Inbound’s also powerful due to the flywheel-effect it creates. The more you invest in Inbound and the more success you have, the less effort required to earn additional benefit.”


Mike King

mikeking.jpeg

“Inbound Marketing is a collection of marketing activities that leverage remarkable content to penetrate earned media channels such as Organic Search, Social Media, Email, News and the Blogosphere with the goal of engaging prospects when they are specifically interested in what the brand has to offer.”

This quote is from 2012, and is still just as accurate today. It’s from an
Inbound.org comment thread where you can also see many other takes on it from the likes of Ian Lurie, Jonathon Colman, and Larry Kim.


Inflow

inflow-logo.jpeg

“Inbound Marketing is a multi-channel, buyer-centric approach to online marketing that involves attracting, engaging, nurturing and converting potential customers from wherever they are in the buying cycle.”

From Inflow’s
Inbound Services page.


Wikipedia

wikipedia.jpeg

“Inbound marketing refers to marketing activities that bring visitors in, rather than marketers having to go out to get prospects’ attention. Inbound marketing earns the attention of customers, makes the company easy to be found, and draws customers to the website by producing interesting content.”

From
Inbound Marketing – Wikipedia.


Larry-Kim.jpeg

Larry Kim

“Inbound marketing” refers to marketing activities that bring leads and customers in when they’re ready, rather than you having to go out and wave your arms to try to get people’s attention.”

Via
Marketing Land in 2013. You can also read more of Larry Kim’s interpretation, along with many others, on Inbound.org.


Hubspot

“Instead of the old outbound marketing methods of buying ads, buying email lists, and praying for leads, inbound marketing focuses on creating quality content that pulls people toward your company and product, where they naturally want to be.”

Via
Hubspot, a marketing automation platform for inbound marketing.

When everyone has their own definition of something, it helps to think about what they have in common, as opposed to how they differ. In the case of inbound, this includes concepts such as:

  • Pull (inbound) vs. push (interruption) marketing
  • “Earning” media coverage, search engine rankings, visitors and customers with outstanding content
  • Marketing across channels
  • Meeting potential customers where they are in their buyer’s journey

Running your first eCommerce inbound marketing campaign

Audience personas—priority no. 1

The magic happens when retailers begin to hyper-segment their list based on buyer personas and other relevant information (i.e. what they’ve downloaded, what they’ve purchased, if they abandoned their cart…). This all starts with audience research to develop personas. If you need more information on persona development, try these resources:

Once personas are developed, retailers should choose one on which to focus. A complete campaign strategy should be developed around this persona, with the aim of providing the “right value” to them at the “right time” in their buyer’s journey.

Ready to get started?

We’ve developed a quick-start guide in the form of a checklist for eCommerce marketers who want to get started with inbound marketing, which you can access below.

inbound ecommerce checklist

Hands-on experience running one campaign will teach you more about inbound marketing than a dozen articles. My advice: Just do one. You will make mistakes. Learn from them and get better each time.

Example inbound marketing campaign

Below is an example of how a hypothetical inbound marketing campaign might play out, assuming you have completed all of the steps in the checklist above. Imagine you handle marketing for an online retailer of high-end sporting goods.

AT Hiker Tommy campaign: From awareness to purchase

When segmenting visitors and customers for a “high-end sporting goods / camping retailer” based on the East Coast, you identified a segment of “Trail Hikers.” These are people with disposable income who care about high-quality gear, and will pay top dollar if they know it is tested and reliable. The top trail on their list of destinations is the
Appalachian Trail (AT).

Top of the Funnel: SEO & Strategic Content Marketing

at-tommy.jpg

Tommy’s first action is to do “top of the funnel” research from search engines (one reason why SEO is still so important to a complete inbound marketing strategy).

A search for “Hiking the Appalachian Trail” turns up your article titled “What NOT to Pack When Hiking the Appalachian Trail,” which lists common items that are bulky/heavy, and highlights slimmer, lighter alternatives from your online catalog.

It also highlights the difference between cheap gear and the kind that won’t let you down on your 2,181 mile journey through the wilderness of Appalachia, something you learned was important to Tommy when developing his persona. This allows you to get the company’s value proposition of “tested, high-end, quality gear only” in front of readers very early in their buyer’s journey—important if you want to differentiate your site from all of the retailers racing Amazon to the bottom of their profit margins.

So far you have yet to make “contact” with AT Hiker Tommy. The key to “acquiring” a contact before the potential customer is ready to make a purchase is to provide something of value to that specific type of person (i.e. their persona) at that specific point in time (i.e. their buying cycle stage).

In this case, we need to provide value to AT Hiker Tommy while he is getting started on his research about hiking the Appalachian Trail. He has an idea of what gear not to bring, as well as some lighter, higher-end options sold on your site. At this point, however, he is not ready to buy anything without researching the trail more. This is where retailers lose most of their potential customers. But not you. Not this time…

Middle of the funnel: Content offers, personalization, social & email nurturing

at-hiker-ebook.png

On the “What NOT to Pack When Hiking the Appalachian Trail” article (and probably several others), you have placed a call-to-action (CTA) in the form of a button that offers something like:

Download our Free 122-page Guide to Hiking the Appalachian Trail

This takes Tommy to a landing page showcasing some of the quotes from the book, and highlighting things like:

“We interviewed over 50 ‘thru-hikers’ who completed the AT and have curated and organized the best first-hand tips, along with our own significant research to develop a free eBook that should answer most of your questions about the trail.”

By entering their email address potential customers agree to allow you to send them the free PDF downloadable guide to hiking the AT, and other relevant information about hiking.

An automated email is sent with a link to the downloadable PDF guide, and several other useful content links, such as “The AT Hiker’s Guide to Gear for the Appalachian Trail”—content designed to move Tommy further toward the purchase of hiking gear.

If Tommy still has not made a purchase within the next two weeks, another automated email is sent asking for feedback about the PDF guide (providing the link again), and to again provide the link to the “AT Hiker’s Guide to Gear…” along with a compelling offer just for him, perhaps “Get 20% off your first hiking gear purchase, and a free wall map of the AT!”

Having Tommy’s email address also allows you to hyper-target him on social channels, while also leveraging his initial visit to initiate retargeting efforts.

Bottom of the funnel: Email nurturing & strategic, segmented offers

Eventually Tommy makes a purchase, and he may or may not receive further emails related to this campaign, such as post-purchase emails for reviews, up-sells and cross-sells.

Upon checkout, Tommy checked the box to opt-in to weekly promotional emails. He is now on multiple lists. Your marketing automation system will automatically update Tommy’s status from “Contact” or lead, to “Customer” and potentially remove or deactivate him from the marketing automation system database. This is accomplished either by default integration features, or with the help of integration tools like
Zapier and IFTTT.

You have now nurtured Tommy from his initial research on Google all the way to his first purchase without ever having sent a spammy newsletter email full of irrelevant coupons and other offers. However, now that he is a loyal customer, Tommy finds value in these bottom-of-funnel email offers.

And this is just the start

Every inbound marketing campaign will have its own mix of appropriate channels. This post has focused mostly on email because acquiring the initial permission to contact the person is what fuels most of the other features offered by marketing automation systems, including:

  • Personalization of offers and other content on the site.
  • Knowing exactly which visitors are interacting on social media
  • Knowing where visitors and social followers are in the buying cycle and which persona best represents them, among other things.
  • Smart forms that don’t require visitors to put in the same information twice and allow you to build out more detailed profiles of them over time.
  • Blogging platforms that tie into email and marketing automation systems
  • Analytics data that isn’t blocked by Google and is tied directly to real people.
  • Closed-loop reporting that integrates with call-tracking and Google’s Data Import tool
  • Up-sell, cross-sell, and abandoned cart reclamation features
Three more things…
  1. If you can figure out a way to get Tommy to “log in” when he comes to your site, the personalization possibilities are nearly limitless.
  2. The persona above is based on a real customer segment. I named it after my friend Tommy Bailey, who actually did write the eBook
    Guide to Hiking the Appalachian Trail, featured in the image above.
  3. This Moz post is part of an inbound marketing campaign targeting eCommerce marketers, a segment Inflow identified while building out our own personas. Our hope, and the whole point of inbound marketing, is that it provides value to you.

Current state of the inbound marketing industry

Inbound has, for the the most part, been applied to businesses in which the website objective is to generate leads for a sales team to follow-up with and close the deal. An examination of various marketing automation platforms—a key component of scalable inbound marketing programs—highlights this issue.

Popular marketing automation systems

Most of the major marketing automation systems can be be used very effectively as the backbone of an inbound marketing program for eCommerce businesses. However, only one of them (Silverpop) has made significant efforts to court the eCommerce market with content and out-of-box features. The next closest thing is Hubspot, so let’s start with those two:

Silverpop – an IBMⓇ Company

silver-pop.jpeg

Unlike the other platforms below, right out of the box Silverpop allows marketers to tap into very specific behaviors, including the items purchased or left in the cart.

You can easily segment based on metrics like the Recency, Frequency and Monetary Value (RFM) of purchases:

silverpop triggered campaigns

You can automate personalized shopping cart abandonment recovery emails:

silverpop cart abandonment recovery

You can integrate with many leading brands offering complementary services, including: couponing, CRM, analytics, email deliverability enhancement, social and most major eCommerce platforms.

What you can’t do with Silverpop is blog, find pricing info on their website, get a free trial on their website or have a modern-looking user experience. Sounds like an IBMⓇ company, doesn’t it?

HubSpot

Out of all the marketing automation platforms on this list, HubSpot is the most capable of handling “inbound marketing” campaigns from start to finish. This should come as no surprise, given the phrase is credited to
Brian Halligan, HubSpot’s co-founder and CEO.

While they don’t specifically cater to eCommerce marketing needs with the same gusto they give to lead gen. marketing, HubSpot does have
an eCommerce landing page and a demo landing page for eCommerce leads, which suggests that their own personas include eCommerce marketers. Additionally, there is some good content on their blog written specifically for eCommerce.

HubSpot has allowed some key partners to develop plug-ins that integrate with leading eCommerce platforms. This approach works well with curation, and is not dissimilar to how Google handles Android or Apple handles their approved apps.

magento and hubspot

The
Magento Connector for HubSpot, which costs $80 per month, was developed by EYEMAGiNE, a creative design firm for eCommerce websites. A similar HubSpot-approved third-party integration is on the way for Bigcommerce.

Another eCommerce integration for Hubspot is a Shopify plug-in called
HubShoply, which was developed by Groove Commerce and costs $100 per month.

You can also use HubSpot’s native integration capabilities with
Zapier to sync data between HubSpot and most major eCommerce SaaS vendors, including the ones above, as well as WooCommerce, Shopify, PayPal, Infusionsoft and more. However, the same could be said of some of the other marketing automation platforms, and using these third-party solutions can sometimes feel like fitting a square peg into a round hole.

HubSpot can and does handle inbound marketing for eCommerce websites. All of the features are there, or easy enough to integrate. But let’s put some pressure on them to up their eCommerce game even more. The least they can do is put an eCommerce link in the footer:

hubspot menus

Despite the lack of clear navigation to their eCommerce content, HubSpot seems to be paying more attention to the needs of eCommerce businesses than the rest of the platforms below.

Marketo

Nothing about Marketo’s in-house marketing strategy suggests “Ecommerce Director Bob” might be one of their personas. The description for each of
their marketing automation packages (from Spark to Enterprise) mentions that it is “for B2B” websites.

marketo screenshot

Driving Sales could apply to a retail business so I clicked on the link. Nope. Clearly, this is for lead generation.

marketo marketing automation

Passing “purchase-ready leads” over to your “sales reps” is a good example of the type of language used throughout the site.

Make no mistake, Marketo is a top-notch marketing automation platform. Powerful and clean, it’s a shame they don’t launch a full-scale eCommerce version of their core product. In the meantime, there’s the
Magento Integration for Marketo Plug-in developed by an agency out of Australia called Hoosh Marketing.

magento marketo integration

I’ve never used this integration, but it’s part of Marketo’s
LaunchPoint directory, which I imagine is vetted, and Hoosh seems like a reputable agency.

Their
pricing page is blurred and gated, which is annoying, but perhaps they’ll come on here and tell everyone how much they charge.

marketo pricing page

As with all others except Silverpop, the Marketo navigation provides no easy paths to landing pages that would appeal to “Ecommerce Director Bob.”

Pardot

This option is a
SalesForce product, so—though I’ve never had the opportunity to use it—I can imagine Pardot is heavy on B2B/Sales and very light on B2C marketing for retail sites.

The hero image on their homepage says as much.

pardot tagline

pardot marketing automationAgain, no mention of eCommerce or retail, but clear navigation to lead gen and sales.

Eloqua / OMC

eloqua-logo.jpeg

Eloqua, now part of the Oracle Marketing Cloud (OMC), has a landing page
for the retail industry, on which they proclaim:

“Retail marketers know that the path to lifelong loyalty and increased revenue goes through building and growing deep client relationships.”

Since when did retail marketers start calling customers clients?

eloqua integration

The Integration tab on OMC’s “…Retail.html” page helpfully informs eCommerce marketers that their sales teams can continue using CRM systems like SalesForce and Microsoft Dynamics but doesn’t mention anything about eCommerce platforms and other SaaS solutions for eCommerce businesses.

Others

There are many other players in this arena. Though I haven’t used them yet, three I would love to try out are
SharpSpring, Hatchbuck and Act-On. But none of them appear to be any better suited to handle the concerns of eCommerce websites.

Where there’s a gap, there’s opportunity

The purpose of the section above wasn’t to highlight deficiencies in the tools themselves, but to illustrate a gap in who they are being marketed to and developed for.

So far, most of your eCommerce competitors probably aren’t using tools like these because they are not marketed to by the platforms, and don’t know how to apply the technology to online retail in a way that would justify the expense.

The thing is, a tool is just a tool

The
key concepts behind inbound marketing apply just as much to online retail as they do to lead generation.

In order to “do inbound marketing,” a marketing automation system isn’t even strictly necessary (in theory). They just help make the activities scalable for most businesses.

They also bring a lot of different marketing activities under one roof, which saves time and allows data to be moved and utilized between channels and systems. For example, what a customer is doing on social could influence the emails they receive, or content they see on your site. Here are some potential uses for most of the platforms above:

Automated marketing uses

  • Personalized abandoned cart emails
  • Post-purchase nurturing/reorder marketing
  • Welcome campaigns for the newsletter (other free offer) signups
  • Winback campaigns
  • Lead-nurturing email campaigns for cohorts and persona-based segments

Content marketing uses

  • Optimized, strategic blogging platforms, and frameworks
  • Landing pages for pre-transactional/educational offers or contests
  • Social media reporting, monitoring, and publishing
  • Personalization of content and user experience

Reporting uses

  • Revenue reporting (by segment or marketing action)
  • Attribution reporting (by campaign or content)

Assuming you don’t have the budget for a marketing automation system, but already have a good email marketing platform, you can still get started with inbound marketing. Eventually, however, you may want to graduate to a dedicated marketing automation solution to reap the full benefits.

Email marketing platforms

Most of the marketing automation systems claim to replace your email marketing platform, while many email marketing platforms claim to be marketing automation systems. Neither statement is completely accurate.

Marketing automation systems, especially those created specifically for the type of “inbound” campaigns described above, provide a powerful suite of tools all in one place. On the other hand, dedicated email platforms tend to offer “email marketing” features that are better, and more robust, than those offered by marketing automation systems. Some of them are also considerably cheaper—such as
MailChimp—but those are often light on even the email-specific features for eCommerce.

A different type of campaign

Email “blasts” in the form of B.O.G.O., $10 off or free shipping offers can still be very successful in generating incremental revenue boosts — especially for existing customers and seasonal campaigns.

The conversion rate on a 20% off coupon sent to existing customers, for instance, would likely pulverize the conversion rate of an email going out to middle-of-funnel contacts with a link to content (at least with how CR is currently being calculated by email platforms).

Inbound marketing campaigns can also offer quick wins, but they tend to focus mostly on non-customers after the first segmentation campaign (a campaign for the purpose of segmenting your list, such as an incentivised survey). This means lower initial conversion rates, but long-term success with the growth of new customers.

Here’s a good bet if works with your budget: Rely on a marketing automation system for inbound marketing to drive new customer acquisition from initial visit to first purchase, while using a good email marketing platform to run your “promotional email” campaigns to existing customers.

If you have to choose one or the other, I’d go with a robust marketing automation system.

Some of the most popular email platforms used by eCommerce businesses, with a focus on how they handle various Inbound Marketing activities, include:

Bronto

bronto.jpeg

This platform builds in features like abandoned cart recovery, advanced email list segmentation and automated email workflows that nurture contacts over time.

They also offer a host of eCommerce-related
features that you just don’t get with marketing automation systems like Hubspot and Marketo. This includes easy integration with a variety of eCommerce platforms like ATG, Demandware, Magento, Miva Merchant, Mozu and MarketLive, not to mention apps for coupons, product recommendations, social shopping and more. Integration with enterprise eCommerce platforms is one reason why Bronto is seen over and over again when browsing the Internet Retailer Top 500 reports.

On the other hand, Bronto—like the rest of these email platforms—doesn’t have many of the features that assist with content marketing outside of emails. As an “inbound” marketing automation system, it is incomplete because it focuses almost solely on one channel: email.

Vertical Response

verticalresponse.jpeg

Another juggernaut in eCommerce email marketing platforms, Vertical Response, has even fewer inbound-related features than Bronto, though it is a good email platform with a free version that includes up to 1,000 contacts and 4,000 emails per month (i.e. 4 emails to a full list of 1,000).

Oracle Marketing Cloud (OMC)

Responsys (the email platform), like Eloqua (the marketing automation system) was gobbled up by Oracle and is now part of their “Marketing Cloud.”

It has been my experience that when a big technology firm like IBM or Oracle buys a great product, it isn’t “great” for the users. Time will tell.

Listrak

listrak.jpeg

Out of the established email platforms for eCommerce, Listrak may do the best job at positioning themselves as a full inbound marketing platform.

Listrak’s value proposition is that they’re an “Omnichannel” solution. Everything is all in one “Single, Integrated Digital Marketing Platform for Retailers.” The homepage image promises solutions for Email, Mobile, Social, Web and In-Store channels.

I haven’t had the opportunity to work with Listrak yet, but would love to hear feedback in the comments on whether they could handle the kind of persona-based content marketing and automated email nurturing campaigns described in the example campaign above.

Key takeaways

Congratulations for making this far! Here are a few things I hope you’ll take away from this post:

  • There is a lot of opportunity right now for eCommerce sites to take advantage of marketing automation systems and robust email marketing platforms as the infrastructure to run comprehensive inbound marketing campaigns.
  • There is a lot of opportunity right now for marketing automation systems to develop content and build in eCommerce-specific features to lure eCommerce marketers.
  • Inbound marketing isn’t email marketing, although email is an important piece to inbound because it allows you to begin forming lasting relationships with potential customers much earlier in the buying cycle.
  • To see the full benefits of inbound marketing, you should focus on getting the right content to the right person at the right time in their shopping journey. This necessarily involves several different channels, including search, social and email. One of the many benefits of marketing automation systems is their ability to track your efforts here across marketing channels, devices and touch-points.

Tools, resources, and further reading

There is a lot of great content on the topic of Inbound marketing, some of which has greatly informed my own understanding and approach. Here are a few resources you may find useful as well.

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!

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Spam Score: Moz’s New Metric to Measure Penalization Risk

Posted by randfish

Today, I’m very excited to announce that Moz’s Spam Score, an R&D project we’ve worked on for nearly a year, is finally going live. In this post, you can learn more about how we’re calculating spam score, what it means, and how you can potentially use it in your SEO work.

How does Spam Score work?

Over the last year, our data science team, led by 
Dr. Matt Peters, examined a great number of potential factors that predicted that a site might be penalized or banned by Google. We found strong correlations with 17 unique factors we call “spam flags,” and turned them into a score.

Almost every subdomain in 
Mozscape (our web index) now has a Spam Score attached to it, and this score is viewable inside Open Site Explorer (and soon, the MozBar and other tools). The score is simple; it just records the quantity of spam flags the subdomain triggers. Our correlations showed that no particular flag was more likely than others to mean a domain was penalized/banned in Google, but firing many flags had a very strong correlation (you can see the math below).

Spam Score currently operates only on the subdomain level—we don’t have it for pages or root domains. It’s been my experience and the experience of many other SEOs in the field that a great deal of link spam is tied to the subdomain-level. There are plenty of exceptions—manipulative links can and do live on plenty of high-quality sites—but as we’ve tested, we found that subdomain-level Spam Score was the best solution we could create at web scale. It does a solid job with the most obvious, nastiest spam, and a decent job highlighting risk in other areas, too.

How to access Spam Score

Right now, you can find Spam Score inside 
Open Site Explorer, both in the top metrics (just below domain/page authority) and in its own tab labeled “Spam Analysis.” Spam Score is only available for Pro subscribers right now, though in the future, we may make the score in the metrics section available to everyone (if you’re not a subscriber, you can check it out with a free trial). 

The current Spam Analysis page includes a list of subdomains or pages linking to your site. You can toggle the target to look at all links to a given subdomain on your site, given pages, or the entire root domain. You can further toggle source tier to look at the Spam Score for incoming linking pages or subdomains (but in the case of pages, we’re still showing the Spam Score for the subdomain on which that page is hosted).

You can click on any Spam Score row and see the details about which flags were triggered. We’ll bring you to a page like this:

Back on the original Spam Analysis page, at the very bottom of the rows, you’ll find an option to export a disavow file, which is compatible with Google Webmaster Tools. You can choose to filter the file to contain only those sites with a given spam flag count or higher:

Disavow exports usually take less than 3 hours to finish. We can send you an email when it’s ready, too.

WARNING: Please do not export this file and simply upload it to Google! You can really, really hurt your site’s ranking and there may be no way to recover. Instead, carefully sort through the links therein and make sure you really do want to disavow what’s in there. You can easily remove/edit the file to take out links you feel are not spam. When Moz’s Cyrus Shepard disavowed every link to his own site, it took more than a year for his rankings to return!

We’ve actually made the file not-wholly-ready for upload to Google in order to be sure folks aren’t too cavalier with this particular step. You’ll need to open it up and make some edits (specifically to lines at the top of the file) in order to ready it for Webmaster Tools

In the near future, we hope to have Spam Score in the Mozbar as well, which might look like this: 

Sweet, right? 🙂

Potential use cases for Spam Analysis

This list probably isn’t exhaustive, but these are a few of the ways we’ve been playing around with the data:

  1. Checking for spammy links to your own site: Almost every site has at least a few bad links pointing to it, but it’s been hard to know how much or how many potentially harmful links you might have until now. Run a quick spam analysis and see if there’s enough there to cause concern.
  2. Evaluating potential links: This is a big one where we think Spam Score can be helpful. It’s not going to catch every potentially bad link, and you should certainly still use your brain for evaluation too, but as you’re scanning a list of link opportunities or surfing to various sites, having the ability to see if they fire a lot of flags is a great warning sign.
  3. Link cleanup: Link cleanup projects can be messy, involved, precarious, and massively tedious. Spam Score might not catch everything, but sorting links by it can be hugely helpful in identifying potentially nasty stuff, and filtering out the more probably clean links.
  4. Disavow Files: Again, because Spam Score won’t perfectly catch everything, you will likely need to do some additional work here (especially if the site you’re working on has done some link buying on more generally trustworthy domains), but it can save you a heap of time evaluating and listing the worst and most obvious junk.

Over time, we’re also excited about using Spam Score to help improve the PA and DA calculations (it’s not currently in there), as well as adding it to other tools and data sources. We’d love your feedback and insight about where you’d most want to see Spam Score get involved.

Details about Spam Score’s calculation

This section comes courtesy of Moz’s head of data science, Dr. Matt Peters, who created the metric and deserves (at least in my humble opinion) a big round of applause. – Rand

Definition of “spam”

Before diving into the details of the individual spam flags and their calculation, it’s important to first describe our data gathering process and “spam” definition.

For our purposes, we followed Google’s definition of spam and gathered labels for a large number of sites as follows.

  • First, we randomly selected a large number of subdomains from the Mozscape index stratified by mozRank.
  • Then we crawled the subdomains and threw out any that didn’t return a “200 OK” (redirects, errors, etc).
  • Finally, we collected the top 10 de-personalized, geo-agnostic Google-US search results using the full subdomain name as the keyword and checked whether any of those results matched the original keyword. If they did not, we called the subdomain “spam,” otherwise we called it “ham.”

We performed the most recent data collection in November 2014 (after the Penguin 3.0 update) for about 500,000 subdomains.

Relationship between number of flags and spam

The overall Spam Score is currently an aggregate of 17 different “flags.” You can think of each flag a potential “warning sign” that signals that a site may be spammy. The overall likelihood of spam increases as a site accumulates more and more flags, so that the total number of flags is a strong predictor of spam. Accordingly, the flags are designed to be used together—no single flag, or even a few flags, is cause for concern (and indeed most sites will trigger at least a few flags).

The following table shows the relationship between the number of flags and percent of sites with those flags that we found Google had penalized or banned:

ABOVE: The overall probability of spam vs. the number of spam flags. Data collected in Nov. 2014 for approximately 500K subdomains. The table also highlights the three overall danger levels: low/green (< 10%) moderate/yellow (10-50%) and high/red (>50%)

The overall spam percent averaged across a large number of sites increases in lock step with the number of flags; however there are outliers in every category. For example, there are a small number of sites with very few flags that are tagged as spam by Google and conversely a small number of sites with many flags that are not spam.

Spam flag details

The individual spam flags capture a wide range of spam signals link profiles, anchor text, on page signals and properties of the domain name. At a high level the process to determine the spam flags for each subdomain is:

  • Collect link metrics from Mozscape (mozRank, mozTrust, number of linking domains, etc).
  • Collect anchor text metrics from Mozscape (top anchor text phrases sorted by number of links)
  • Collect the top five pages by Page Authority on the subdomain from Mozscape
  • Crawl the top five pages plus the home page and process to extract on page signals
  • Provide the output for Mozscape to include in the next index release cycle

Since the spam flags are incorporated into in the Mozscape index, fresh data is released with each new index. Right now, we crawl and process the spam flags for each subdomains every two – three months although this may change in the future.

Link flags

The following table lists the link and anchor text related flags with the the odds ratio for each flag. For each flag, we can compute two percents: the percent of sites with that flag that are penalized by Google and the percent of sites with that flag that were not penalized. The odds ratio is the ratio of these percents and gives the increase in likelihood that a site is spam if it has the flag. For example, the first row says that a site with this flag is 12.4 times more likely to be spam than one without the flag.

ABOVE: Description and odds ratio of link and anchor text related spam flags. In addition to a description, it lists the odds ratio for each flag which gives the overall increase in spam likelihood if the flag is present).

Working down the table, the flags are:

  • Low mozTrust to mozRank ratio: Sites with low mozTrust compared to mozRank are likely to be spam.
  • Large site with few links: Large sites with many pages tend to also have many links and large sites without a corresponding large number of links are likely to be spam.
  • Site link diversity is low: If a large percentage of links to a site are from a few domains it is likely to be spam.
  • Ratio of followed to nofollowed subdomains/domains (two separate flags): Sites with a large number of followed links relative to nofollowed are likely to be spam.
  • Small proportion of branded links (anchor text): Organically occurring links tend to contain a disproportionate amount of banded keywords. If a site does not have a lot of branded anchor text, it’s a signal the links are not organic.

On-page flags

Similar to the link flags, the following table lists the on page and domain name related flags:

ABOVE: Description and odds ratio of on page and domain name related spam flags. In addition to a description, it lists the odds ratio for each flag which gives the overall increase in spam likelihood if the flag is present).

  • Thin content: If a site has a relatively small ratio of content to navigation chrome it’s likely to be spam.
  • Site mark-up is abnormally small: Non-spam sites tend to invest in rich user experiences with CSS, Javascript and extensive mark-up. Accordingly, a large ratio of text to mark-up is a spam signal.
  • Large number of external links: A site with a large number of external links may look spammy.
  • Low number of internal links: Real sites tend to link heavily to themselves via internal navigation and a relative lack of internal links is a spam signal.
  • Anchor text-heavy page: Sites with a lot of anchor text are more likely to be spam then those with more content and less links.
  • External links in navigation: Spam sites may hide external links in the sidebar or footer.
  • No contact info: Real sites prominently display their social and other contact information.
  • Low number of pages found: A site with only one or a few pages is more likely to be spam than one with many pages.
  • TLD correlated with spam domains: Certain TLDs are more spammy than others (e.g. pw).
  • Domain name length: A long subdomain name like “bycheapviagra.freeshipping.onlinepharmacy.com” may indicate keyword stuffing.
  • Domain name contains numerals: domain names with numerals may be automatically generated and therefore spam.

If you’d like some more details on the technical aspects of the spam score, check out the 
video of Matt’s 2012 MozCon talk about Algorithmic Spam Detection or the slides (many of the details have evolved, but the overall ideas are the same):

We’d love your feedback

As with all metrics, Spam Score won’t be perfect. We’d love to hear your feedback and ideas for improving the score as well as what you’d like to see from it’s in-product application in the future. Feel free to leave comments on this post, or to email Matt (matt at moz dot com) and me (rand at moz dot com) privately with any suggestions.

Good luck cleaning up and preventing link spam!



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