We all know Google Analytics is great for analyzing website traffic. But in the age of the smartphone, we want to analyze traffic to our mobile apps, too. Wouldn’t it be great if we could get the same actionable insight we get on our mobile development websites for the apps we design? Well, it turns out, you can!
Google offers an SDK for Google Analytics that provides support for both iOS (iPhone) and Android. As you’d expect from Google, the Android SDK is a little more powerful, but both allow you to get a much better picture of how people are using your app, in the same way you currently do for your website. The major difference is that with Android you can track the sources of where people actually download your app, so you can tie your marketing campaigns to the usage of the app.
Let’s do a quick overview of how it works. I’ll spare you the gory technical details, but Google provides a great walkthrough, including code samples.
How You Can Integrate With Your App
Here at LunaMetrics, just like you, we’re building the next “killer” app. It’s called InstaTweetSquare.
InstaTweetSquare will allow you to apply fancy filters to your tweets when you check-in to a location (investors, feel free to comment below, we’re seeking a $50 billion valuation). But how do we decide whether our users are finding all of the great features? What if they only like applying filters, but not Tweeting? Let’s install the Google Analytics library into our Android app and see what happens.
Once the library is installed, you need to add some code on each app view (just like Google Analytics code on your website) to let GA know which account to log, and also to track that someone was there. In my case, I’ve put tracking code on each tab:
Look familiar? This works the way Virtual Page Views do, where you provide a “page name” and tell Google to track it. So each time someone clicks on one of my tabs of the app, I’ll see that as a page viewed in Google Analytics.
Ok, now we know who is viewing what tab. That’s pretty interesting, as we see that no one seems to care about the Profile tab. Using this data, perhaps we’ll remove that tab and put it in a button. But how do we know that our users are even doing anything on our tabs? Just like for websites, we can configure Events for actions we want to monitor on the page
So I’ll add an event for someone clicking the Filter button, the Tweet button, and any other events we’d like to monitor.
It looks like everyone really understands the Filter select button, but for some reason people are clicking the Check-in button twice for every view of that page. That’s something we may want to send back to the UI team.
GA for smart phones isn’t just limited to views and clicks though. For our app, we decided on a freemium SaaS model, where our users can Tweet if they are a Free user and post to Google+ if they are a Paid user, and just like with our website, we can use Custom Variables to tell which users are which to see how they are using the app and converting.
tracker.setCustomVar(1, "User Type", "Paid", 2);
Finally, the all important goal of our app is in-app purchases. And just like on the web, we can configure E-commerce for Android, so when someone buys our custom filters, it’s logged just like any other E-commerce transaction (sample code is pretty long, but Google has a great example).
All of the examples above are sent to Google almost immediately when the user is online. Something to keep in mind though: apps that can be used offline can still use GA, but the data will only be dispatched once the user is online again. This may cause some of your data to have inaccurate timestamps.
As you can see, pretty much anything you can do with Google Analytics for the web, you can do with GA for mobile. If you have a smart phone app, it’s worth thinking about using Google Analytics’ Mobile SDK to analyze user behavior.
I think you’ll agree that an ever-changing search algorithm is dynamic in its engineers’ consistent efforts towards development, refinement, and ultimately, improvement. The end goal of any algorithm update, however large or small, is certainly not detraction from quality. In fact, it’s quite the opposite. An update is made, we can assume, to improve upon the quality of the results – no matter how insignificant-seeming the percentage of results affected. When I search “all about poodles,” I want to learn all about poodles – not play minesweeper with pop up and banner ads. Mind you, overall improvement does not necessarily translate to individual ranking increases; we know this all too well. With positive change comes almost certain hardship for those that are oppositely negative. Fortune favors the brave – yes. Similarly, though, misfortune handpicks the irresponsibly audacious. Just ask BMW or J.C. Penney – both of which have suffered the unrelenting punitive blows of Google’s “manual action.”
An algorithm update, in some sense, is the addition of an automation process to carry out an action that was previously executable only by handpicking or “manual action.” As you can imagine, penalizing (or rewarding) sites on a case to case basis is both laughably uneconomical and far too permissive of subjective, human analysis. It’s fairly intuitive, then, that the more frequently a particular rule needs applied, the more likely it is that that rule will become an integral part of the algorithm. For instance, when I search to learn more about our fluffy, white friends, the results at the top of the SERPs are largely informative and (more importantly) exactly what I’m looking for. Before Panda (which came with harsh penalties for websites with thin content), I might not have been so lucky. Anyways, that’s for another day. For now, we’ll focus on sentiment in search. Where is it going? Where has it been? And can its analysis be translated effectively and efficiently into the current search algorithm? Let’s have at it!
The Current State of Sentiment in Search
First off, let’s define the “sentiment” of an online vote (be it a link, review, service testimonial, etc.) as the connotation (positive, negative, or neutral) with which said vote is casted. While the link is traditionally recognized as the primary vote metric, developments in social technology and online listing review systems have broadened the user’s ability to convey relative, measurable sentiment within minutes (or even seconds). If you liked Christina’s recent blog post on ‘keyword not provided‘ or tweeted about Jim’s take on flow visualization in GA, you’ve engaged socially in conveying positive sentiment, or casting a positive vote for the respective post. On the other hand, if you found such disfavor in the stale-tasting coffee at the local donut shoppe that you felt obligated to share that negative experience with potential customers online (perhaps through a Google Places listing review), you’ve conveyed negative sentiment, or casted a negative vote for that business.
While we can’t be sure how these signals are weighted in the current algorithm, we can certainly infer that the integration process is well under way. With Google’s release of the +1 button and specific markup for reviews and rich snippets, it’s a reasonable assumption to make that the link is no longer the lone indicator of online sentiment. Notice, though, that the majority of these indicators are geared towards users sharing positive experiences (perhaps with exception to negative reviews). Although many custom blog platforms allow users to cast a negative vote for a given post with a thumbs-down, major social platforms (from which search engines actually collect data) like Facebook have yet to implement such an option. How, then, without clear-cut social signals, do we derive negative sentiment from a given comment or review? And perhaps more importantly, how do we go about deriving negative sentiment from the original vote metric – the link?
Sentiment Analysis – A Work in Progress
To preface this section, I’d like to recommend some light reading – a New York Times article (which Robbin suggested to me) that inspired this post (as it probably has many of the more recent debates on sentiment in search). The article details the much-chagrined success story (and subsequent fall) of an online eye glasses vendor who utilized the power of negative votes (provided by intentionally provoked customers) to leverage his company’s organic search presence. I’d like to spare you another poodle analogy, but honestly, I can’t resist. This should paint a fairly representative picture of the article (for those of you who are saving it for a rainy day).
If a fictitious John from John’s Poodle Emporium trains his dogs to be utterly disobedient to their renters, there’s a good chance that John’s business is going to receive plenty of negative reviews online. With no sentiment analysis, though, a review is a review and a link is a link. Online poodle forums and blogs are abuzz with horror stories about John’s Poodle Emporium (occasionally even linking to his site). Little do they know, they’re fueling the very fire that they seek to put out – sending link juice from relevant websites onto John’s site. John punks his Poodle-loving patrons and moves onto the next group of clients the town over (who haven’t bothered to check out some online reviews). All the while, his rankings are shooting through the roof, providing him with a healthy influx of new customers to mistreat intentionally.
Okay, back to reality. That was bad, but you get the idea. While Google affirms that the the real vendor’s rankings should be attributed to link juice from high authority news outlets (like the New York Times), citing the presence of the rel=”nofollow” link attribute on many of the negative review sites, the causation is there, nonetheless. Be it direct or indirect, in this case, negative sentiment yielded positive results.
How Do We Combat This?
Needless to say, the article prompted almost immediate action from Google. After doing their due diligence, they found that cases similar to that in the New York Times article were not as uncommon as they had originally thought. As we discussed earlier, a high volume of problematic, penalty-deserving websites can often complicate manual action. However, when all of these websites are linked by a common infraction, the likelihood that the penalties can be distributed algorithmically is much higher. In this case, the search engineers at Google were able to implement a quick, algorithm-intensive fix that penalizes online vendors who treat their customers poorly or unfairly. While we can’t be sure that this solution is completely free of sentiment consideration, we can be sure that sentiment analysis is not the foundation of the underlying framework. In fact, Google has admitted that although they have a “world-class sentiment analysis system,” they’ve yet to find a way to effectively implement that system within the current algorithm.
The Way of the Future?
It seems simple, doesn’t it? Just introduce an algorithm update that mandates that all crawls take into account the sentiment of the text surrounding a given link. If the connotation of the “context clues” is primarily positive, treat the link as a positive vote. If negative, weight the link with a negative value. Simple enough, right? Actually . . . not so much. We could pick the simplicity of this solution apart all day, so I’ll spare you the countless refutations in place of one (for which I’ll pose a rhetorical question). Aren’t some of the most important modern issues also the most polarizing issues? And, in our context, should a website pertaining to one of these issues be devalued because the negative sentiment nearly washes the positive? Hardly, in my opinion. A vote, whether positive or negative, is still an indication of care. As long as people care about a given issue or web page (and are willing to pay testament to their sentiments), as things stand, the results that they see will be based on sheer popularity.
With all that we’ve considered, many points remain mute. Incorporating user sentiment in search, whether socially, through review aggregators, or by sentiment analysis, is a tricky little game. Considering the tremendously impactful implications that a major sentiment-related algorithm change could have, it’s a game that needs to be played with the utmost tact and care. That said, I’m rather confident that user reviews, testimonials, social votes, context clues surrounding links, and even the sentiment of anchor text will continue to play larger roles in both organic and local rankings. Undoubtedly, the technology behind these metrics (and consequently, their popularity among users) will continue to develop in the future. This puts further onus on coinciding algorithmic development targeting search sentiment. Again, the end goal is better results for the user – or better information about poodles for curious dog lovers. If, by implementing a functional, discriminatory sentiment analysis system in the search algorithm, we’re able to achieve this, then I’m all for it. Personalized search is the way of the future. Sentiment analysis is just another step in the right direction . . . well, at least on the timeline.
What are your thoughts on sentiment in search? Are all votes created equal, or should positive and negative sentiment play a role in valuing a link? Have you observed any noticeable ranking changes since you’ve enabled social “voting” on your pages? Share your thoughts and experiences!
You may or may not have noticed something fishy in your Google Analytics Keywords report recently. If you haven’t noticed, go into Google Analytics and do the following:
Use the Non-Paid Search Traffic Advanced Segment
Change the Date Range to 10/17 – 10-19
Go to Traffic Sources > Sources> Organic
Observe the top three or four keyowrds
Do you see it? If it’s not at the top, it’s in there somewhere. It’s a keyword called (Not Provided.)
Now, if you were training at an SEO event like I was on the 17th and then was out of the office (and largely offline) on the 18th or if you live under a rock somewhere, you might not have heard Google’s official announcement that they will no longer be providing keyword data for organic search results if the user is signed into their Google account.
It’s not just Google Analytics that will be denied this data. By “enhancing” their default user experience for signed in users, Google will be redirecting signed in users to https://www.google.com, thus encrypting the search results page. In analytics, you’ll still be able to see that these signed in users came from the organic search results, but instead of being able to see the actual keywords that they used, you’ll see all that data aggregated under (Not Provided.)
If you’re an SEO who uses the keywords report to prove the validity and efficacy of your work, you’re screaming and gnashing your teeth by this point. If you’re a causal analytics user, you may be asking the question “why do this?”
Well, obviously, it’s to protect the user: “As search becomes an increasingly customized experience, we recognize the growing importance of protecting the personalized search results we deliver.” (excerpt from Google’s official statement)
In what way does hiding the queries that signed in users use to get to your site infringe upon their privacy since all the data is anonymous anyway? That’s a legitimate question by the way. Feel free to answer it in the comments! I’m curious what you all thing. And why, oh WHY are PAID search keywords not affected by this change.
That’s right. You can still see every single keyword that sent traffic through paid search, whether the user is signed in or not — just not organic search. Are users who click on paid search results less safe than users that click on organic results?
*Breathes Deeply*
Long Lasting Repercussions of Keyword (Not Provided)
Google claims that this change will affect only a small percentage of data, since only those who are signed into their Google account when searching will be “protected.” Well, I’m throwing down the benchmark here and now.
So far, since this change launched, LunaMetrics has seen 1% of our keywords clumped into (Not Provided.) A client with substantially larger organic search volume has already seen almost 2% of their organic keywords represented as Not Provided. We shall see how far-reaching these changes actually are in a few weeks when they’re rolled out completely.
Additionally, Google’s placation that only a small percentage of data will be affected because of the amount of people who search while NOT signed is cold comfort to me when they’re trying so very very hard to push the adoption of Google+ on the masses. If they have their way everyone would always be signed into their Google account when online.
I would love to hear the thoughts and concerns, and views of everyone else! Thanks!
Flow visualization is not a new concept. Take a look at the map above, drawn by Charles Joseph Minard in 1869. That’s a flow map of Napoleon’s march to Russia, showing the French army’s location and direction, where units split off and rejoined, the declining size of the army (as the size of the army gets smaller, so does the line), and also the temperatures during the retreat. Hmmm… if only we could see a similar visualization of “armies” of visitors as they march through our website. (Spoiler alert: that’s exactly what the flow visualization reports do).
Traditional path analysis reports don’t do a good job of providing insights. It’s a visualization problem, and a “user” problem. The “user” problem isn’t so much a problem, it’s just that users are individuals that tend to each do things differently and follow their own unique paths through our websites (and life). Sure, there are some common paths that people take (hopefully this is the case if you’ve diligently designed your site with clear calls to action and obvious path choices). But after the handful of common paths, when you start drilling into the data you just get a lot of unique paths taken by single users.
Flow visualization is a way to understand how visitors flow through your website. It uses intuitive imagery, along with the ability to segment your visitors, to make insightful analysis easier. These reports better help you understand how to optimize your landing pages, navigation, conversion funnels and more. They can help explain the behavior of segments of visitors after they land on a page, and see where there might be commonalities and differences between key segments.
Flow Visualization reports
There are three reports that are included in Flow Visualization:
Visits Flow: provides a graphical representation of your traffic sources, and the paths through your site that your visitors follow.
Goal Flow: provides a graphical representation of the paths your visitors took to successfully complete a conversion and where they dropped off. This flow requires that you have already defined goals. Currently, only URL destination goals are supported. Goal flow improves upon the existing “Funnel Visualization” reports.
Navigation Flow: provides a graphical representation of your start/end nodes, and the paths to or from your site that your visitors follow. When you create a navigation flow, you have the option to identify a single page by URL, or to create a node that represents a group of pages whose URLs match a condition, for example, all pages whose URL contains a particular product identifier like shirts or jackets.
Using Flow Visualization
Sometimes, things are best explained with video. This is one of those times, so sit back, relax, and enjoy this brief tour through this new feature.
I’ve been meaning to write this post for several months, as I’ve repeatedly fielded questions (and complaints) about how to find things “behind the scenes” in the administrative settings of the new Google Analytics interface. Now that the “new” new interface has finally been released, it’s time to highlight the major landmarks. Once you know what to look for, it will make a lot of sense. And managing your accounts and profiles will be faster and easier than ever.
Where Did My Reports Go?
The first thing you may notice about the new interface when you log in to Google Analytics is the big empty orange bar. Where is everything? This is the new “Account Home” – what used to be the overview of all your accounts. There are no numbers here for comparison (sad), just an alphabetized list of accounts and profiles. And where are the reports?
Usually instead of heading for the administrative settings first you’ll want to go straight to a report. So let’s take a quick detour through the up-front navigation and then I’ll take you behind the scenes.
Searching and Clean Profile Switching
To get to a report you have to choose a profile. You could scroll through the list, expanding the plus signs, but… don’t. (Unless it’s a really short list.) The fastest way is to start typing in the Search box either the name of the profile or the account it’s under. Then click on the profile you want and the Visitors Overview report will appear.
You can use the same type-to-search method to switch profiles from any report, only this time you type in the Accounts List under the arrow at the upper left. By the way, if you want to see the name of the profile you’ve currently selected, you have to hover over the web property name in the orange bar (again, sad – wish they’d display the profile name instead).
On the other hand (not sad!) when you switch profiles, GA will remember the way you’ve configured the report – such as changing the date range, the view, or the filter – and show you the same report in the new profile. For me, this clean profile switching is one of the best features of the new interface.
Now we’re ready to go behind the scenes and figure out what’s what in the new administrative settings.
Meet the Web Property – A Group of Profiles
When you click the gear icon at the top right of GA, your first thought might be, “Where the heck am I?” Take a deep breath. We’re at the Web Property level. Think of it as a group of profiles that all have the same Web Property ID number (UA-XXXXX-Y).
That means all the profiles here get their data from web pages with this number in the tracking code. The URLs of those web pages may or may not match the URL of the Web Property – because the tracking code on the page is the only thing that determines where the data ends up.
What you’re looking at now are the settings for a single profile, the one shown in the Profile pulldown list (the same profile whose report you just viewed). The tabs below the profile name are the Assets, Goals, Users, Filters, and Profiles Settings for that profile only.
Above the profile name are tabs for this Web Property level, including the Tracking Code (with this unique Web Property ID number) and the Web Property settings.
So what do you do if you need another tracking code number? You create a new Web Property. And you can do that at the Account level.
Follow the Bread Crumbs to the Account Level
The trick to orienting yourself in the Account and Profile Settings is to follow the bread crumbs at the top of the page. Our tour began at the deepest level, in a single Web Property with a single profile selected.
So to go to the Account level, click on the Account Name in the bread crumbs at the top. Now the tabs say Webproperties, Users, Filters, Data Sources, and Account Settings. Here you can choose the button for + New Web Property if you want to get another snippet of code with a new tracking number.
There are a couple other important features here as well. In the old interface you may have known them as the User Manager and the Filter Manager. If you didn’t know them, allow me to introduce you.
Discovering the User Manager and Filter Manager
There are times when you need to make user or filter changes only in one or two profiles. And the new clean profile switching works great for that here behind the scenes, the same as it did up-front in the reports.
But if you have changes to make in lots of profiles, checking them one at a time is not so great. Or if you simply need information about a particular user (which profiles does he have access to?) or a particular filter (which profiles use that filter?) then checking one at a time is also clearly suboptimal.
Here at the Account level, the Filters tab is the same as the Filter Manager, and the Users tab is the same as the User Manager.
With these tabs, you can apply changes to multiple profiles all at the same time. Or you can just look up information about a particular user or filter. Click the Filters tab and then click any filter to see how this works.
When you select a filter, you’ll see a list of all the profiles currently using that filter. You can easily add or remove profiles, or just make a note of which profiles use this filter.
You’ll see something similar when you select a User under the Users tab (but not for Administrators, since Administrators have access to every profile). Give a User access to multiple profiles or remove access here, without having to visit the Users tab for each profile one at a time. It’s supposed to work the same way, but for now, it doesn’t and you’ll have to set User access one profile at a time.
Last Stop – Account Administration and Back Again
And finally you can even go all the way back up the trail of bread crumbs to the highest level, by clicking All Accounts.
Here under Account Administration you’ll see the accounts you have access to and whether you’re a User or Administrator for each one. The button to create a new account is here, too.
Navigating back down into an account, to a web property, to a profile, feels more intuitive than the upward climb through the bread crumbs. It’s a little more obvious where you’re going. After a few trips up and down, the tabs at each level will become familiar landmarks and you’ll be a pro.
The navigational tools in the downward direction are mostly familiar, too. You can use the page navigation in the lower right, or even “star” frequently used accounts and web properties (alas, not profiles). And type-to-search is available at every level. It’s my favorite way to get where I want to go fast.
What do you like (or dislike) the most in the administrative settings of the new interface? What’s missing or what do you wish Google Analytics would change? Please share in the comments.
Managing a Facebook Page or multiple Facebook Pages can often be a 24/7 commitment, depending on the size of your Page’s audience and their level of engagement with that Page. One way to help lower the amount of time you’re in front of a computer is by posting and interacting with fans from your mobile phone, in this case, the iPhone. The Facebook App for the iPhone was recently updated, making it much easier for a Page administrator to interact with their Facebook audience on the go. To deal with this problem many schedule their Facebook posts when they know they’ll be away from the computer, but there are reasons why you shouldn’t post on Facebook with third party tools.
The latest changes to the app, which coincide with the release of the Facebook app for the iPad, give users a much cleaner layout of the Facebook platform, making it both easy and effective for Page administrators to use. When you first open the Facebook app for the iPhone, the new home screen lays out all your options much more concisely, allowing you to browse your News Feed, check your messages, check-in with Facebook Places, view upcoming events and search through your friends list with greater ease than before.
Facebook Page Management
One of the biggest improvements to the new layout of the Facebook for iPhone app is how your Facebook Pages are displayed. Previously, you had to search through all the Pages you like and admin, and then add them as a favorite. By adding them as a favorite you could quickly access them from the homepage of the app.
Thankfully the new app eliminates this extra step for Page administrators and simply puts all the Pages you administer in a list on the homepage of the app. This cuts down time, making your social media management efforts that much easier. With this change you can now quickly go down the list and choose which Page you wish to update. You can also see numbers to the right of each Page on your list of Pages, indicating notifications for that particular Page. This change helps Page administrators spend less time roaming their Facebook Page on their iPhone for comments from fans and more time responding to fan feedback because it’s now super easy to see that a notification was triggered.
Posting to Your Facebook Page
You can still share a photo on your Page, write a post for your Page and respond to a comment on your Page as you did before with the previous version of the Facebook for iPhone application. However, sharing a photo on your Page has slightly changed when it comes to the variety of customization options. After you land on the Facebook Page you wish to update, you’re given two options once you’ve reached the wall tab. You can either write a post or share a photo in terms of updating the Page. Writing a post simply allows you to add text or links to an update on your Facebook wall, while sharing a photo allows you to share a photo of your choosing. The photo option has become a little more dynamic in terms of allowing you to tag others and write a caption. By clicking on the photo anywhere, then typing in the name of a person, event, group or Page, you’re able to tag them in the photo you’re about to share. The photo you share can come from a photo you’ve just taken or from the photo album on your phone. The ability to add a caption is super easy as well. All you need to do is tap where it says write a caption and begin typing away. From here you can upload your photo to your wall at your leisure.
Other Noteworthy Features
App Notification Settings, Made Easier
You were always able to change the notification settings of your Facebook for iPhone app, but now they are much clearer and easier to view and change.
External Applications Integration
Applications like Foursquare and Instagram already existed as applications within Facebook, but they’ve been made more accessible from the updated Facebook for iPhone app. The new layout seamlessly integrates the applications already given access to your Facebook account and installed on your iPhone. This is an interesting move for Facebook in terms of Foursquare and Instagram because Facebook at one time wished to dominate the location based social media vertical and in the case of Instagram, Facebook attempted to buy the company and incorporated its photo filters into Facebook. In both cases, Facebook failed to overtake the market these social platforms specialize in. Maybe this is Facebook’s salute to these platforms for capitalizing on what they do best?
Privacy Settings Added to App
The new app also addresses the continuing concerns that Facebook users have regarding privacy. Privacy settings were not very clear within the previous version of the app, but now they are much more concise and easier to customize right from your iPhone.
Facebook Places with an Easy to View Friend Map
Facebook Places was Facebook’s big push for the last year or so, but recently they handed the torch off to Foursquare and gave up on controlling the location based social media space. However, this feature shows you where your friends have recently checked in on a nice, Google Maps style map.
There’s no doubt in my mind that the Facebook for iPhone app will be upgraded again in the future. Until then, do you find these latest changes helpful for your social media monitoring efforts? What other changes to the Facebook for iPhone app would you like to see?
It’s well known just how important (and robust) Google’s Quality Score is. It’s made up of multiple factors, including click-through rate, landing page quality, and numerous other relevancy factors, and in turn, it affects keywords’ CPCs, ad rank, and other indirect performance factors. While Click-through rate remains the strongest influencer of quality score, Google recently rolled out updates to its quality score calculation that will make the weight of landing page quality a stronger factor in quality score than it has been in the past.
This update definitely makes sense – the landing page a user arrives on after clicking an ad should be relevant to both the ad itself and the keyword that triggered it, and contain original, relevant content that is transparent and easily navigable. Therefore, it only makes sense that landing page quality should be a stronger indicator of quality score than it was in the past. Once the user clicks, it’s the landing page and overall user experience that needs to drive those conversions for your business.
Don’t Overlook Your Landing Pages
Keeping this update in mind, it’s time to revisit all of those landing pages you have set up in your AdWords account to make sure they’re relevant, transparent, and navigable.
Make sure your ads, keywords, and landing pages contain the same content. The message should be fluid, and the information being relayed in the ad should be relayed on the landing page, which of course, should be related to the keyword itself.
Make sure your visitors know what they’ll get when they click on a link, if they enter information, or if they choose to download something off of your site.
Visitors should be able to learn about your company and your site easily, without having to dig around too much.
Make sure to keep the path to conversion short and quick. Minimize clicks so that visitors can get where they want to go quickly, before dropping off the page.
If you want to keep your costs down as much as possible while holding a strong ad position on the SERP, all of these landing pages factors (and more) are necessary. Simply getting your visitors to your site won’t necessarily do the trick – spend time finding the best page possible on your site. Also, don’t be afraid to test out the creation of new pages for the purpose of maintaining quality landing pages throughout your AdWords campaigns. The effort will be worth it in the end.
While Important, Don’t Expect a Radical Change from the Update
Google is currently rolling out these changes to quality score globally. Initially, they expect variations to take place across campaigns in regard to quality score and ad position, but expect things to stabilize shortly after the changes take effect. While it is extremely important you ensure your landing pages are the best they can be, this update does not mean you should disregard the other factors that go into Google’s quality score. Also, you shouldn’t expect to see catastrophic changes in your ad positioning and quality scores within your account. Landing page quality is one piece of the Quality Score puzzle, and all pieces remain important and essential to your account’s success.
Internal linking is often overlooked during the search engine optimization arms race. Despite this, it is an easy way to help optimize your site. While not every website will see dramatic results from internal linking, others will be shocked to see forgotten about articles gain significant traffic, or see their pages ranking for new keywords.
Internal linking is any link within your website that links to somewhere else on your website. Logically, these links fall into two basic camps: structural and contextual.
Structural links are generally created while designing the website. They include any navigation bars, site maps, footers, and headers. Without well planned structural links, it’s possible to have pages completely unattached to the rest of your website. In this scenario, the only way to access these pages would be to type in their URL. For this reason, structural links are designed to ensure no pages go missing.
Unfortunately, many people see structural links as the be-all-end-all of internal linking. This isn’t true. Your website has a wealth of knowledge and countless opportunities to help boost its own search engine rank through contextual internal linking.
A contextual link is simply a link within the content of your website. By using them properly, you can help pages rank higher for specific key phrases and increase the usability of your website. Studies have shown that website users are more likely to click on contextual links. They cite contextual links as feeling more “natural” than search bars or navigation columns. This makes sense. If as you introduce new products, services or ideas you incorporate contextual links to pages further exploring these facets, the flow from one page to another feels seamless.
The best way to begin a contextual link building campaign is to review your website and determine your goals. Do you have high-quality pages that are rarely viewed? Is an important aspect of your company getting drowned out by other pages and key phrases? Do you want an evenly distributed web of links that keep people on your site longer? These kinds of questions will help shape how you approach your campaign.
The basis of contextual links is using key phrases from your content (otherwise known as anchor text) as your link. These key phrases infer the content of the page it links to. Search engines use this information to help rank pages for key phrases used in the anchor text. As such, anchor text should be keywords with high search volume and should be directly related to the page it links to.
For example, I might write: “Due to the ever changing nature of search engines, there is always demand for search engine optimization consultants.” In this example, the anchor text “search engine optimization consultants” has a high search volume, and it leads back to the LunaMetrics webpage, as LunaMetrics is a SEO consultant company.
Once you understand the simple mechanics of contextual link building, the process of adding links to your website becomes intuitive. Page by page you need to go through your website adding links that will help you reach your goal. If you’re trying to boost the visibility of some overlooked pages, you might link to them from a high-traffic page. If you’d like to keep people clicking through your site, you might add links when new ideas are introduced. For a page of great importance, you may link several pages to it to increase visibility. If a page is ranking poorly for an important keyword, use that keyword as anchor text when linking to that page.
As with everything in life, there can be too much of a good thing. Stuffing your website with links can negatively affect your search engine rank and will certainly annoy any users that visit your site. As a rule of thumb, only add links where they make sense and increase website usability.
To some, this SEO technique seems too good to be true. While it won’t singlehandedly cause your website to rank on the first page, it is an effective tool in your SEO arsenal. The benefits range from small bumps in traffic to pages ranking highly for completely new key phrases. With search engine optimization being a constant arms race, taking advantage of every small step is vital to landing that coveted first page slot.
Have you ever wondered how exactly does information about visits to your website get sent back to Google Analytics? Let me introduce you to my good friend, __utm.gif.
You see, whenever a page of your site loads (as long as you have GA tracking code on the page) a request is made for a small file — the __utm.gif. But don’t be fooled by the size of this file (weighing in at only 35 bytes); it packs a lot of information in the request URI of that little pixel. Here’s an example:
Holy parameters, Batman! Let’s break that down now to see what information is being sent back.
utmwv=5.1.7 – Tracking code version utms=1 – Session number. Number of sessions/visits from this particular browser Session requests. Updates every time a __utm.gif request is made. Stops incrementing at 500 (max number of GIF requests per session). utmn=1894752493 – Unique ID generated for each GIF request to prevent caching of the GIF image utmhn=www.lunametrics.com – Host name, which is a URL-encoded string utmcs=UTF-8 – Language encoding for the browser. Some browsers don’t set this, in which case it is set to “-” utmsr=1280×1024 – Screen resolution utmsc=24-bit – Screen color depth utmul=en-us – Browser language utmje=1 – Indicates if browser is Java enabled. 1 is true. utmfl=10.3 r183 – Flash version utmdt=Tracking QR Codes with Google Analytics – Page title, which is a URL-encoded string utmhid=1681965357 – A random number used to link the GA GIF request with AdSense utmr=http://www.google.com/search?q=tracking+qr+codes&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a – Referral, complete URL utmp=/blog/2011/08/18/tracking-qr-codes-google-anaytics/ – Page request of the current page utmac=UA-296882-1 – Account string, appears on all requests utmcc=__utma=230887938.1463229748.1317737798.1317737798.1317737798.1;
+__utmz=230887938.1317737798.1.1.utmcsr=google|utmccn=(organic)|utmcmd=organic|utmctr=tracking%20qr%20codes; – Cookie values. This request parameter sends all the cookies requested from the page. utmu=DC~ – This is a new parameter that contains some internal state that helps improve ga.js.
Notice the next to last parameter – utmcc. If you look through that you’ll see all of your cookie information, like visitor ID, how many times they’ve been to your site, how they got to your site, what keyword (if any) they used, etc.
Although that GIF request URI is long, it doesn’t use all the parameters available. Here’s an (almost) full list of the GIF request parameters from Google code. And here are additional eCommerce-specific parameters (scroll down to the bottom) that are nicely summarized.
Now it’s your turn
There are a number of free tools that allow you to quickly and easily see what information is being sent in that GIF request (or if it’s even being requested at all). Watch this quick video demonstrating the use of two tools – Firebug and HttpFox (both for Firefox). If you’re a Chrome browser, you may want to try the Google Analytics Tracking Code Debugger. Here’s a list of even more debugging tools.
rate, landing page quality, and numerous other relevancy factors, and in turn, it affects keywords’ CPCs, ad rank, and other indirect performance factors. While Click-through rate remains the strongest influencer of quality score, Google recently rolled out updates to its quality score calculation that will make the weight of landing page quality a stronger factor in quality score than it has been in the past.
they’re relevant, transparent, and navigable.
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