Panda Analysis Using Google Analytics Segments – How To Isolate Desktop, Mobile, and Tablet Traffic From Google

Segments in Google Analytics to Isolate Traffic

In previous posts about Panda analysis, I’ve mentioned the importance of understanding the content that users are visiting from Google organic. Since Google is measuring user engagement, hunting down those top landing pages can often reveal serious content quality problems.

In addition, I’ve written about understanding the devices being used to access your site from the search results. For example, what’s the breakdown of users by desktop, mobile, and tablets from Google organic? If 50% of your visits are from smartphones, then you absolutely need to analyze your site through that lens. If not, you can miss important problems that users are experiencing while visiting your website. And if left unfixed, those problems can lead to a boatload of horrible engagement signals being sent to Google. And that can lead to serious Panda problems.

Panda Help Via Segments in Google Analytics
So, if you want to analyze your content by desktop, mobile, and tablet users through a Panda lens, what’s the best way to achieve that? Well, there’s an incredibly powerful feature in Google Analytics that I find many webmasters simply don’t use. It’s called segmentation and enables you slice and dice your traffic based on a number of dimensions or metrics.

Segments are non-destructive, meaning that you can apply them to your data and not affect the source of the data. Yes, that means you can’t screw up your reporting. :) In addition, you can apply new segments to previous traffic (they are backwards compatible). So you can build a new segment today and apply it to traffic from six months ago, or longer.

For our purposes today, I’m going to walk you through how to quickly build three new segments. The segments will isolate Google organic traffic from desktop users, mobile users, and tablet users. Then I’ll explain how to use the new segments while analyzing Panda hits.

 

How To Create Segments in Google Analytics
When you fire up Google Analytics, the “All Sessions” segment is automatically applied to your reporting. So yes, you’ve already been using segments without even knowing it. If you click the “All Sessions” segment, you’ll see a list of additional segments you can choose.

Google Analytics All Sessions Segment

You might be surprised to see a number of segments have been built for you already. They are located in the “System” category (accessed via the left side links). For example, “Direct Traffic”, “AdWords”, “Organic Traffic”, and more.

Google Analytics System Segments

 

We are going to build custom segments by copying three system segments and then adding more dimensions. We’ll start by creating a custom segment for mobile traffic from Google organic.

1. Access the system segments by clicking “All Sessions” and then clicking the link labeled “System” (located on the left side of the UI).

 

Google Analytics System Segments

 

2. Scroll down and find the “Mobile Traffic” segment. To the far right, click the “Actions” dropdown. Then choose “Copy” from the list.

 

Copying a System Segment in Google Analytics

 

3. The segment already has “Device Category”, “exactly matches”, and “mobile” as the condition. We are going to add one more condition to the list, which is Google organic traffic. Click the “And” button on the far right. Then choose “Acquisition” and the “Source/Medium” from the dimensions list. Then choose “exactly matches” and select “google/organic” from the list. Note, autocomplete will list the top sources of traffic once you place your cursor in the text box.

 

Creating a Segment by Adding Conditions

 

4. Name your segment “Mobile Google Organic” by using the text box labeled “Segment Name” at the top of the window. It’s easy to miss.

 

Name a Custom Segment in Google Analytics

 

5. Then click “Save” at the bottom of the create segment window.

 

Save a Custom Segment in Google Analytics

 

Congratulations! You just created a custom segment.

 

Create The Tablet Traffic Segment
Now repeat the process listed above to create a custom segment for tablet traffic from Google organic.  You will begin with the system segment for “Tablet Traffic” and then copy it. Then you will add a condition for Google organic as the source and medium.

 

Desktop Traffic (Not a default system segment.)
I held off on explaining the “Desktop Traffic” segment, since there’s an additional step in creating one. For whatever reason, there’s not a system segment for isolating desktop traffic. So, you need to create this segment differently. Don’t worry, it’s still easy to do.

We’ll start with the “Mobile Traffic” segment in the “System” list, copy it, and then refine the condition.

1. Click “All Sessions” and the find “Mobile Traffic” in the “System” list. Click “Actions” to the far right and then click “Copy”.

 

Copying a System Segment in Google Analytics

 

2. The current condition is set for “Device Category” exactly matching “mobile”. We’ll simply change mobile to “desktop”. Delete “mobile” and start typing “desktop”. Then just select the word “desktop” as it shows up.

Creating a Desktop Segment in Google Analytics

 

3. Since we want Desktop traffic from Google Organic, we need to add another condition. You can do this by clicking “And” to the far right, selecting “Acquisition”, and then “Source/Medium” from the dropdown. Then select “exactly matches” and enter “Google/Organic” in the text box. Remember, autocomplete will list the top sources of traffic as you start to type.

 

Creating a Google Organic Desktop Segment in Google Analytics

 

4. Name your segment “Desktop Google Organic” and then click “Save” at the bottom of the segment window to save your new custom segment.

 

Quickly Check Your Segments
OK, at this point you should have three new segments for Google organic traffic from desktop, mobile, and tablets. To ensure you have these segments available, click “All Sessions” at the top of your reporting, and click the “Custom” link on the left. Scroll down and make sure you have all three new segments. Remember, you named them “Desktop Google Organic”, “Mobile Google Organic”, and “Tablet Google Organic”.

If you have them, then you’re good to go. If you don’t, read through the instructions again and create all three segments.

 

Run Panda Reports by Segment
In the past, I’ve explained the importance of running a Panda report in Google Analytics for identifying problematic content. A Panda report isolates landing pages from Google organic that have dropped substantially after a Panda hit. Well, now that you have segments for desktop, mobile, and tablet traffic from Google organic, you can run Panda reports by segment.

For example, click “All Sessions” at the top of your reporting and select “Mobile Google Organic” from the “All” or “Custom” categories. Then visit your “Landing Pages” report under “Behavior” and “Site Content” in the left side menu in GA. Since you have a specific segment active in Google Analytics, the reporting you see will be directly tied to that segment (and filter out any other traffic).

Creating a Google Panda Report Using Custom Segments

 

Then follow the directions in my previous post to run and export the Panda report. You’ll end up with an Excel spreadsheet highlighting top landing pages from mobile devices that dropped significantly after the Panda hit. Then you can dig deeper to better understand the content quality (or engagement) problems impacting those pages.

Combine with Adjusted Bounce Rate (ABR)
User engagement matters for Panda. I’ve documented that point many times in my previous posts about Panda analysis, remediation, and recovery. The more poor engagement signals you send Google, the more bamboo you are building up. And it’s only a matter of time before Panda comes knocking.

So, when analyzing user engagement, many people jump to the almighty Bounce Rate metric to see what’s going on. But here’s the problem. Standard Bounce Rate is flawed. Someone could spend five minutes reading a webpage on your site, leave, and it’s considered a bounce. But that’s not how Google sees it. That would be considered a “long click” to Google and would be absolutely fine.

And this is where Adjusted Bounce Rate shines. If you aren’t familiar with ABR, then read my post about it (including how to implement it). Basically, Adjusted Bounce Rate takes time on page into account and can give you a much stronger view of actual bounce rate. Once you implement ABR, you can check bounce rates for each of the segments you created earlier (and by landing page). Then you can find high ABR pages by segment (desktop, mobile, and tablet traffic).

Combining Adjusted Bounce Rate with Custom Segments

 

Check Devices By Segment (Smartphones and Tablets)
In addition to running a Panda report, you can also check the top devices being used by people searching Google and visiting your website. Then you can analyze that data to see if there are specific problems per device. And if it’s a device that’s heavily used by people visiting your site from Google organic, then you could uncover serious problems that might lie undetected by typical audits.

GA’s mobile reporting is great, but the default reporting is not by traffic source. But using your new segments, you could identify top devices by mobile and tablet traffic from Google organic. And that’s exactly what you need to see when analyzing Panda hits.

Analyzing Devices with Custom Segments in Google Analytics

For example, imagine you saw very high bounce rates (or adjusted bounce rates) for ipad users visiting from Google organic. Or maybe your mobile segment reveals very low engagement from Galaxy S5 users. You could then test your site via those specific devices to uncover rendering problems, usability problems, etc.

 

Summary – Isolate SEO Problems Via Google Analytics Segments
After reading this post, I hope you are ready to jump into Google Analytics to create segments for desktop, mobile, and tablet traffic from Google organic. Once you do, you can analyze all of your reporting through the lens of each segment. And that can enable you to identify potential problems impacting your site from a Panda standpoint. I recommend setting up those segments today and digging into your reporting. You might just find some amazing nuggets of information. Good luck.

GG

 

How To Check If Google Analytics Is Firing On Android Devices Using Remote Debugging With Chrome [Tutorial]

How To Debug Google Analytics on Mobile Devices

We all know that having a strong analytics setup is important. Marketing without measurement is a risky proposition for sure. But in a multi-device world, it’s not as easy to make sure your setup is accurately tracking what you need – or tracking at all. And if your analytics code isn’t firing properly across smartphones, tablets, and desktop computers, your data will be messy, incomplete, and inaccurate. And there’s nothing that drives a marketer crazier than flawed data.

A few weeks ago, Annie Cushing tweeted a quick question to her followers asking how everyone was testing their Google Analytics setup via mobile devices. This is something many digital marketers grapple with, especially when you are trying to track down problems. For example, I do a lot of algorithm update work and often dig into the analytics setup for a site to ensure we are seeing the full drop in traffic, conversion, revenue, etc.

My knee-jerk response was to check real-time reporting in Google Analytics while accessing specific pages to ensure those visits were being tracked, in addition to events. That could work, but it’s not as granular or isolated as you would want. I also mentioned to Annie that using a chrome extension like User Agent Switcher could help. That wouldn’t document the firing of analytics code, but would let you see the source code when accessing a webpage via a specific type of smartphone or tablet. But again, you couldn’t see the actual firing of the code or the events being tracked. And that’s obviously an important aspect to debugging analytics problems.

A Solution – Remote Debugging on Android with Chrome
So I did what I typically do when I run into a tricky situation. I find a solution! And for Android devices, I found a solid one. Many of you might be familiar with Chrome Developer Tools (on your desktop computer). It holds some outstanding functionality for debugging websites and web applications. But although it’s extremely helpful for debugging desktop webpages, it didn’t really address the problem at hand (out of the box), since we want to debug mobile devices.

So I started to research the issue and that’s when I came across a nifty technique which would allow you to connect your Android device to your desktop computer and then debug the Chrome tabs running on your mobile device from your desktop computer. And since I could use Chrome Developer Tools to debug the tabs on my desktop computer, I could check to see if Google Analytics was indeed firing when accessing webpages via my Android device. Awesome.

So, I spent some time testing this out and it does work. Sure, I had to jump through some hoops to get it to run properly, but it finally did work. Below I’ll cover what you’ll need to test this out for yourself and how to overcome some of the problems I encountered. Let’s get started.

 

What You’ll Need
In order to debug GA code running on your mobile device, you’ll need the proper setup both on your desktop computer and on your Android device. In its simplest form, you’ll need:

  • Chrome installed on your desktop (version 32 or later).
  • Android 4.0 or later.
  • A USB Cable to connect your device to your computer.
  • Android SDK {this will not be required for some of you, but others might need to install it. More on that situation below}.

If you run into the problems I ran into, you’ll need the Android SDK installed. I already had it installed since I’ve been testing various Android functionality and code, so it wasn’t a big deal. But you might need to install it on your own. I wouldn’t run to do that just yet, though. If the straight setup works for you, then run with it. If not, then you might need to install the Android SDK.

If you are confident you have the necessary setup listed above, then you can move to the tutorial listed below. I’ll walk you through how to debug Chrome tabs running on your mobile device via Chrome on your desktop computer. And yes, we’ll be isolating Google Analytics code firing on our Android devices to ensure you are tracking what you need.


How To Debug Google Analytics on Your Android Device – Step-By-Step Instructions

  1. Enable USB Debugging on Your Android Device
    Access your settings on your Android device and click Developer Options. On my device, that was located in the more “More” grouping of my settings and under System Manager. If you don’t see Developer Options, then you need to enable it.You can do that by accessing Settings, tapping About Phone or About Device and tapping Build Number seven times. Yes, that sounds extremely cryptic, but that’s what you need to do. Once you do, Developer Options will show up in under System Manager in your phone’s settings.

    Enable USB Debugging on Android Device

    Then you can check the box to enable USB Debugging on your device. You will need to do this in order to debug Google Analytics in Chrome on your device.

  2. Enable USB Discovery in Chrome (on your desktop)
    Next, type chrome:inspect in a new tab in Chrome on your desktop. Ensure “Discover USB devices” is checked on this screen.

    Enable USB Discovery in Chrome Desktop
  3. Connect Your Phone To Your Computer via USB
  4. Allow USB Debugging
    When you connect your phone to your computer, you should see a dialog box on your phone that asks you if you want to allow USB debugging. Click OK. Note, if you don’t see this dialog box, debugging your mobile device from Chrome on your desktop will not work. I provide instructions for getting around this problem later in the tutorial. If you are experiencing this problem, hop down to that section now.

    Allow USB Debugging on Android Device
  5. Fire up Chrome On Your Mobile Device
    Start Chrome on your Android device and access a webpage (any webpage you want to debug).
  6. Inspect With Chrome on your Desktop
    Once you open a webpage in Chrome on your mobile device, access Chrome on your desktop and visit chrome:inspect. Once you do, you should see your device listed and the various tabs that are open in Chrome on your Android device.

    Inspect Chrome Tabs on Desktop Computer
  7. Click Inspect To Debug The Mobile Tab
    When you click “inspect”, you can use Chrome Developer Tools on your desktop to debug the mobile web view. You can use all of the functionality in Chrome Developer Tools to debug the webpage open on your mobile device.
  8. Click the Network Tab in Chrome Developer Tools
    By accessing the Network Tab, you can view all network activity based on the webpage you have loaded in Chrome on your mobile device. That includes any resources that are requested by the webpage. Then reload the webpage on your mobile device to ensure you are seeing all resources.
  9. First Check for GA.js
    When you load a webpage on your mobile device, many resources will be listed in the network tab. But you should look for ga.js to see if the Google Analytics snippet is being loaded.Tip: You can use the search box and enter “ga.js” to filter all resources by that string. It’s an easy way to isolate what you are looking for.

    Check for ga.js in Network Tab in Developer Tools
  10. Next Check for utm.gif
    After checking for ga.js, you should look for the tracking pixel that’s sent to GA named utm.gif. If that is listed in the network panel, then your mobile webpage is tracking properly (at least basic tracking). Again, you can use the search box to filter by utm.gif.

    Check for utm.gif in Network Tab in Developer Tools
  11. Bonus: Advanced Tracking
    If you are firing events from mobile webpages, then you can see them listed here as well. For example, you can see an event being fired when a user stays on the page for more than 30 seconds below. So for this situation, we know that pageviews are accurately being tracked and the time on page event is being tracked via mobile. Nice.

    Check event tracking in Chrome for Android

 

A Note About Troubleshooting
I mentioned earlier that if you don’t see the “Allow USB Debugging” dialog on your mobile device when you connect your phone to your computer, then this setup won’t work for you. It didn’t initially work for me. After doing some digging around, I found the legacy workflow for remote debugging on Android.

By following the steps listed below, I finally got the prompt to show up on my mobile device. Then I was able to debug open Chrome tabs on my Android device.

 

  1. Install the Android SDK (if you don’t already have it installed)
    You can learn more about the SDK here and download the necessary files.
  2. Kill the ADB Server
    Use a command prompt to access the “platform-tools” folder in the SDK directory and then issue the following command: adb kill-server. Note, you should use the cd command to change directory to the folder containing adb. That’s the platform-tools folder in your Android SDK directory.

    Kill ADB Server
  3. Revoke USB Debugging on Your Android Device
    Disconnect your phone from your computer. Then go back to Developer Options on your Android phone and tap Revoke USB debugging authorization.

    Revoke USB Debugging
  4. Start the ADB Server
    Now you must restart the adb server. Use a command prompt, access the platform-tools folder again, and enter the following command: adb start-server.

    Start ADB Server
  5. Reconnect Your Device To Your Computer
    Once you reconnect your device, you should see the “Allow USB Debugging” dialog box. Click “OK” and you should be good to go. This will enable you to debug Chrome tabs running on your mobile device via Chrome running on your desktop.
  6. Open Chrome on Your Android Device
    Go ahead and open a webpage that you want to debug in Chrome on your Android phone. Once it’s loaded in Chrome in Android, you can follow the instructions listed earlier for using the network panel to debug the GA setup.

 

Summary – Know When Google Analytics is Firing on Mobile Devices
So there you have it. There is a way to debug the actual firing of GA code on your Android devices and it works well. Sure, you may need to go the extra mile, use the legacy workflow, and install the Android SDK, but you should be able to get it working. And once you do, you’ll never have to guess if GA is really working on Android devices. You’ll know if it is by debugging your Chrome tabs on Android via Chrome running on your desktop. Good luck.

GG

 

 

How To Remarket 70+ Ways Using Segments and Conditions in Google Analytics

Remarketing in Google Analytics Using Conditions and Segments

I know what you’re thinking. Can you really remarket more than 70 different ways using segments in Google Analytics?  Yes, you can!  Actually, when you combine the methods I’ll cover today, there are many more types of Remarketing lists you can build!  So the total number is much greater than 70.

My post today is meant to introduce you to segments in Google Analytics (GA), explain how you can use them to remarket to people who already visited your site, and provide important Remarketing tips along the way.  I hope once you read this post, you’re ready to kick off some Remarketing campaigns to drive more sales, leads, phone calls, etc.

What Are Segments in Google Analytics?
Many digital marketers know about Remarketing already.  That’s where you can reach people that already visited your website via advertising as they browse the web.  For example, if John visited Roku’s website, browsed various products, and left, then Roku could use Remarketing to advertise to John as he browses the Google Display Network (GDN).  The Google Display Network is a massive network of sites that run Google advertising, and includes Google-owned properties like YouTube, Google Maps, Gmail, etc.  According to Google, the GDN reaches 90% of internet users worldwide.

Remarketing via The Google Display Network (GDN)

By the way, if you’ve ever visited a website and then saw ads from that website as you browsed the web, then you’ve been remarketed to.  As you can guess, this can be an incredibly powerful way to drive more sales, leads, etc.  It can also be extremely frustrating and/or shocking to users.  So be careful when crafting your Remarketing strategy!

When Remarketing first rolled out, you could only set up Remarketing lists in the AdWords interface.  That was ok, but didn’t provide a massive amount of flexibility.  That’s when Google enabled marketers to set up Remarketing lists via Google Analytics.  That opened up an incredible amount of opportunity to slice and dice visitors to create advanced-level Remarketing lists.  For example, you could create Remarketing lists based on users who visited a certain section of your website, or lists based on users completing a certain conversion goal, etc.  Needless to say, tying Google Analytics to Remarketing was an awesome addition.

Now, I started using Google Analytics Remarketing functionality immediately to help clients build advanced Remarketing lists, but I had a feeling that Google was going to make it even more powerful.  And they did.

Along Came Segments… Remarketing Options Galore
You might already be familiar with segments in Google Analytics, which was originally named “Advanced Segmentation”.  In July of 2013, Google released a new version in Google Analytics and simply called it “Segments”.  But don’t get fooled by the simpler name.  Segments enable marketers to slice and dice their users and traffic to view reporting at a granular level.  For example, I often set up a number of segments for clients, based on their specific goals. Doing so enables me to quickly view granular reporting by removing a lot of the noise residing in standard reports.

Using Segments to Create Remarketing Lists in Google Analytics

But starting in January of 2014, Google rolled out an update that enabled marketers to use those segments to create Remarketing lists.  Yes, now marketers had an incredible number of options available when creating Remarketing lists.  In addition, you could easily import segments you are already using! This means you could leverage the hard work you’ve already put in when creating segments in Google Analytics.

Although I thought I had a lot of flexibility in creating Remarketing lists leading up to that point, the ability to use segments opened the targeting flood gates.  I remember checking out the list of options when segments for Remarketing first launched, and I was blown away.

For example, using segments you could create Remarketing lists based on:

  • Demographics like age, gender, language, location, and more.
  • Technology options like operating system, browser, device category, mobile device model or branding, and more.
  • Behavior like the number of sessions per user, days since last session, transactions, and session duration.
  • “Date of First Session” where you could create lists based on the initial session date or a range (sessions that started between two dates).
  • Traffic Sources based on campaign, medium, source, or keyword.
  • Ecommerce options like transaction id, revenue, days to transaction, product purchased, or product category.
  • And you can combine any of these options to create even more advanced Remarketing lists.

 

Now, the options listed above are based on the major categories of segments in Google Analytics.  But you can also set Remarketing lists based on conditions.  Using conditions, you could leverage many of the dimensions or metrics available in Google Analytics to build advanced Remarketing lists.  Actually, there are so many options via “conditions” that I can’t even list them all here in this post.

For example, there are eight major categories of dimensions and metrics you could choose from, including Acquisition, Advertising, Behavior, Custom Variables, Ecommerce, Time, Users, and Other.  And each category has a number of dimensions or metrics you can select to help craft your Remarketing lists.

Using Conditions to Create Remarketing Lists in Google Analytics

Note, it can definitely be overwhelming to review the list of options when you first check this out.  Don’t worry, I provide some tips for getting started later in this post.  For now, just understand that you can use segments and conditions in Google Analytics to craft Remarketing lists based on a number of factors (or a combination of factors).  Basically, you have the power to remarket however you like.  And that’s awesome.

Examples of What You Can Do
Enough with the introduction.  Let’s get specific.  I’m sure you are wondering how segments in Google Analytics can be used in the real-world.  I’ll provide a few examples below of Remarketing lists you can build to get back in front of people who already visited your website.  Note, the lists you build should be based on your specific business and website.  I’m just covering a few options below so you can see the power of using segments to build Remarketing lists.

Example 1: Remarket to users who came from a specific referral path (page).
Imagine you knew that certain referring webpages drove a lot of high-quality traffic on a regular basis.  Based on the quality of traffic coming through those referring pages, you decide that you would love to remarket to those users as they browse the web (since you have a strong feel for the type of user they are based on the content at hand).

Using segments, you could create a Remarketing list based on the original referral path (i.e. the referring pages).  And once that list reaches 100 members, then you can start getting targeted ads in front of those users and driving them to your preferred landing page (whether that’s current content, campaign landing pages, etc.)

Using Referring Path to Create Remarketing Lists

And if you find several referring pages that target similar categories of content, then you could use Boolean operators to combine those pages from across different websites.  For example, {referring path A} AND {referring path B}.  For example, if three referring pages are all about Category A, then you could combine them to create a Remarketing list.  You can also use regular expressions to match certain criteria.  Yes, the sky’s the limit.

Using Boolean Operators to Create Advanced Remarketing Lists

Example 2: Reach a certain demographic that has visited your website.
Let’s say you just launched a new product targeting 18-25 year olds and wanted to remarket to users who already visited your website that fit into this category.  You know they showed some interest in your company and products already (since they already visited your site), so you want to reach them via display advertising as they browse the web.

Using segments, you could create a Remarketing list based on age using the Demographics category.  Simply click the checkbox next to the age category you want to target.

Creating Remarketing Lists Based on Demographics

Or to get even more targeted, you could combine age with gender to test various messaging or visuals in your ads.  Going even further, you could add location as another selection to target users based on age, gender, and geographic location (down to the city level if you wanted).

Combining Demographics to Create Advanced Remarketing Lists

Example 3: Target users of specific campaigns, ad groups, or keywords.
Let’s say you are already using AdWords to drive targeted users to your website.  Using segments in Google Analytics, you could build a Remarketing list based on specific campaigns, ad groups, or keywords.  For example, if you have an ad group targeting a specific category or product, then you could create a list containing the users that already searched Google and clicked through your ads related to that category.  It’s a great way to get back in front of a targeted audience.

Creating Remarketing Lists Based on Previous Campaigns

And by combining the targeting listed above with ecommerce conditions like the number of transactions or amount of revenue generated, you could create advanced Remarketing lists targeting very specific types of users.

Creating Remarketing Lists Based on Revenue

Example 4: Pages or Page Titles
If you have been building a lot of new content and want to reach those visitors as they browse the web, then you could create a Remarketing list based Pages or Page Titles.  For example, let’s say you have 25 blog posts about a certain category of content.  They rank very well, have built up a nice amount of referral traffic, etc.  You could build a Remarketing list by select a grouping of pages via urls or via page titles. Then you could reach those users as they browse the web and drive them to a targeted landing pages, knowing they were interested in a certain post (or group of posts) about a certain subject.

Creating Remarketing Lists Based on Page Titles

And you can combine those pages with conversion goals to add users to a list that completed some type of important action on the site.  For example, users that signed up for your email newsletter, users that triggered an event, downloaded a study, etc.

Creating Remarketing Lists Based on Page Titles and Conversion

Remarketing Tips

Based on the examples listed above, I hope you see the power in using segments and conditions to craft Remarketing lists.  But as I said earlier, it can quickly become overwhelming (especially for marketers new to Remarketing).  Below, I’ve listed several important tips to keep in mind while crafting your campaigns.

  1. Remarketing Lists Require 100 Members
    A list requires at least 100 members before you can start showing ads to users.  Keep this in mind when building lists to ensure you can reach that number.  If not, you will never get back in front of those users.
  2. Start Simple, Then Increase in Complexity
    Based on the 100 member requirement, start with simpler Remarketing lists and increase your targeting as you get more comfortable with Remarketing.  Don’t start with the most granular targeting possible, only to have a list of 3 people.
  3. Refine Your Tracking Snippet
    Google requires that you refine your Google Analytics tracking code in order take advantage of Remarketing.  Review the documentation to ensure you have the proper technical setup.
  4. Craft a Strategy First, and Your Lists Should Support Your Strategy
    Don’t create lists for the sake of creating lists. Always start by mapping out a strong Remarketing strategy before jumping into list creation. Your strategy should dictate your Remarketing lists, and not the other way around.  Spend time up front mapping out who you want to target, and why.  And once you have a solid plan mapped out, you can easily build your lists via Google Analytics segments and conditions.
  5. Use Display Advertising In Addition to Text Ads
    Remarketing enables you to use both image ads and text ads.  Definitely use both when crafting your campaigns.  There are a number of sizes and formats you can use.  I recommend hiring a designer to build your ads unless you have in-house staff that is capable of designing high-quality ads.  Use image ads where possible to grab the user’s attention and provide text ads as a backup when a site doesn’t support image ads.  You don’t have to choose one or the other.
  6. Measure Your Results! Don’t “Set It and Forget It”.
    Remarketing is advertising.  And advertising campaigns should have a goal.  Don’t simply set up Remarketing without knowing the intended action you want users to take.  Instead, make sure you set up conversion goals to track how those users convert.  Do not set up the campaign and let it run without analyzing the results.  Understand the ROI of the campaign.  That’s the only way you’ll know if it worked, if the campaign should keep running, and if you should base other campaigns on the original.

 

Summary – New and Powerful Ways to Remarket
After reading this post, I hope you see the power in using segments and conditions for creating Remarketing lists.  In my opinion, too many marketers keep going after new eyeballs and easily forget about the eyeballs that already showed an interest in their company, products, or services.  I believe that’s a mistake.  Instead, marketers can craft advanced Remarketing lists to get back in front of a targeted audience.  Doing so provides another chance at converting them.

Remember, a warm lead is always more powerful than a cold call.  Good luck.

GG

 

Panda Report – How To Find Low Quality Content By Comparing Top Landing Pages From Google Organic

Top Landing Pages Report in Google Analytics

Note, this tutorial works in conjunction with my Search Engine Watch column, which explains how to analyze the top landing pages from Google Organic prior to, and then after, Panda arrives.  With the amount of confusion circling Panda, I wanted to cover a report webmasters can run today that can help guide them down the right path while on their hunt for low-quality content.

My Search Engine Watch column covers an overview of the situation, why you would want to run the top landing pages report (with comparison), and how to analyze the data.  And my tutorial below covers how to actually create the report.  The posts together comprise a two-headed monster that can help those hit by Panda get on the right track.   In addition, my Search Engine Watch column covers a bonus report from Google Webmaster Tools that can help business owners gather more information about content that was impacted by the mighty Panda.

Why This Report is Important for Panda Victims
The report I’m going to help you create today is important, since it contains the pages that Google was ranking well and driving traffic to prior to a Panda attack.  And that’s where Google was receiving a lot of intelligence about content quality and user engagement.  By analyzing these pages, you can often find glaring Panda-related problems.  For example, thin content, duplicate content, technical problems causing content issues, low-quality affiliate content, hacked content, etc.  It’s a great way to get on the right path, and quickly.

There are several ways to run the report in Google Analytics, and I’ll explain one of those methods below.  And remember, this should not be the only report you run… A rounded analysis can help you identify a range of problems from a content quality standpoint.  In other words, pages not receiving a lot of traffic could also be causing Panda-related problems.  But for now, let’s analyze the top landing pages from Google Organic prior to a Panda hit (which were sending Google the most data before Panda arrived).

And remember to visit my Search Engine Watch column after running this report to learn more about why this data is important, how to use it, red flags you can identify, and next steps for websites that were impacted.  Let’s get started.

How To Run a Top Landing Pages Report in Google Analytics (with date comparison): 

  • First, log into Google Analytics and click the “All Traffic” tab under “Acquisition”.  Then click “Google / Organic” to isolate that traffic source.
    Accessing Google Organic Traffic in Google Analytics
  • Next, set your timeframe to the date after Panda arrived and extend that for a decent amount of time (at least a few weeks if you have the data).  If time allows, I like to set the report to 4-6 weeks after Panda hit.  If this is right after an algorithm update, then use whatever data you have (but make sure it’s at least one week).  I’m using a date range after the Phantom update hit (which was May 8th).
    Setting a Timeframe in Google Analytics
  • Your next move is to change the primary dimension to “Landing Page” to view all landing pages from Google organic search traffic.  Click the “Other” link next to “Primary Dimension” and select “Acquisition”, and then “Landing Page”.  Now you will see all landing pages from Google organic during that time period.
    Primary Dimension to Landing Page in Google Analytics
  • Now let’s use some built-in magic from Google Analytics.  In the timeframe calendar, you can click a checkbox for “Compare to” and leave “Previous period” selected.  Once you click “Apply”, you are going to see all of the metrics for each landing page, but with a comparison of the two timeframes.  And you’ll even have a nice trending graph up top to visualize the Panda horror.
    Comparing Timeframes in Google Analytics
  • As you start going down the list of urls, pay particular attention to the “% Change” column.  Warning, profanity may ensue.  When you start seeing pages that lost 30%, 40%, 50% or more traffic when comparing timeframes, then it would be wise to check out those urls in greater detail.  Again, if Google was sending a lot of traffic to those urls, then it had plenty of user engagement data from those visits.  You might just find that those urls are seriously problematic from a content quality standpoint.
    Viewing The Percent Change in Traffic in Google Analytics

 

Bonus 1: Export to Excel for Deeper Analysis

  • It’s ok to stay within Google Analytics to analyze the data, but you would be better off exporting this data to Excel for deeper analysis.  If you scroll to the top of the Google Analytics interface, you will see the “Export” button.  Click that button and then choose “Excel (XLSX)”.  Once the export is complete, it should open in Excel.  Navigate to the “Dataset” worksheet to see your landing page data (which is typically the second worksheet).
    Exporting A Report In Google Analytics
  • At this point, you should clean up your spreadsheet by deleting columns that aren’t critical for this report.  Also, you definitely want to space out each column so you can see the data clearly (and the data headers).
    Clean Up Google Analytics Export in Excel
  • You’ll notice that each url has two rows, one for the current timeframe, and one for the previous timeframe.  This enables you to see all of the data for each url during both timeframes (the comparison).
    Two Rows For Each URL Based on Timeframe
  • That’s nice, but wouldn’t it be great to create a new column that showed the percentage decrease or increase for visits (like we saw in Google Analytics?)  Maybe even with highlighting to show steep decreases in traffic  Let’s do it.  Create a new column to the right of “Visits” and before “% New Visits”.  I would title this column “% Change” or something similar.
    Creating a New Column for Percent Change in Excel
  • Next, let’s create a formula that provides the percentage change based on the two rows of data for each url.  Find the “Visits” column and the first landing page url (which will have two rows).  Remember, there’s one row for each timeframe.  If your visits data is in column C, then the post-Panda data is in row 2, and the pre-Panda data is in row 3 (see screenshot below).  You can enter the following formula in the first cell for the new column “% Change”.=(C3-C2)/C3.Again, C3 is the traffic levels from the previous timeframe, C2 is the traffic levels from the current timeframe (after the Panda hit), and you are dividing by the previous traffic levels to come up with the percentage change.  For example, if a url dropped from 5,450 visits to 640 visits, then your percentage drop would be 88%.  And yes, you would definitely want to investigate that url further!
    Creating a Formula to Calculate Percent Change in Excel
  • Don’t worry about the floating decimal point.  We’ll tackle that soon.  Now we need to copy that formula to the rest of the column (but by twos).  Remember, we have two records for each url, so you’ll need to highlight both cells before double clicking the bottom right corner of the second cell to copy the formula to all rows.  Once you do, Excel automatically copies the two rows to the rest of the cells in that column.  Now you should have percentage drops (or increases) for all the urls you exported.  Note, you can also highlight the two cells, copy them, and then highlight the rest of that column, and click paste.  That will copy the formula to the right cells in the column as well.
    Copying a Formula to All Rows in Excel
  • Now, you will see a long, floating decimal point in our new column labeled “% Change”.  That’s an easy fix, since we want to see the actual percentage instead.  Highlight the column, right click the column, and choose “Format Cells”.  Then choose “Percentage” and click “OK”.  That’s it.  You now have a column containing all top landing pages from Google organic, with the percentage drop after the Panda hit.
    Formatting Cells in Excel

 

Bonus 2: Highlight Cells With A Steep Drop in Red

  • If you want the data to “pop” a little more, then you can use conditional formatting to highlight cells that exceed a certain percentage drop in traffic.  That can easily help you and your team quickly identify problematic landing pages.
  • To do that, highlight the new column we created (titled “% Change”), and click the “Conditional Formatting” button in your Home tab in Excel (located in the “Styles” group).  Then select, “Highlight Cells Rules”, and then select, “Greater Than”.  When the dialog box comes up, enter a minimum percentage that you want highlighted.  And don’t forget to add the % symbol!  Choose the color you want to highlight your data with and click “OK”.  Voila, your problematic urls are highlighted for you.  Nice.
    Applying Conditional Formatting in ExcelApplying Conditional Formatting by Percentage in Excel

 

Summary – Analyzing Panda Data
If you made it through this tutorial, then you should have a killer spreadsheet containing a boatload of important data.  Again, this report will contain the percentage increase or decrease for top landing pages from Google Organic (prior to, and then after, a Panda hit).  This is where Google gathered the most intelligence based on user engagement.  It’s a great place to start your analysis.

Now it’s time to head over to my Search Engine Watch column to take a deeper look at the report, what you should look for, and how to get on the right track with Panda recovery.  Between the tutorial and my Search Engine Watch column, I hope to clear up at least some of the confusion about “content quality” surrounding Panda updates.  Good luck.

GG

 

 

You Might Be Losing Out – How To Make Sure Sitelink Extensions in Bing Ads Are Tracked Properly [Tutorial]

Bing Ads released sitelink extensions in October of 2012, which enables advertisers to provide additional links in their text ads.  Google AdWords has had ad sitelinks for some time, so this was a great addition by our friends at Bing Ads.  For example, if you were an ecommerce website selling sporting goods, you could provide ad sitelinks for your top categories, like football, baseball, basketball, etc. right beneath your standard text ad.  Sitelink extensions are great usability-wise, while they also provide a nice advantage in the SERPs (since they take up more real-estate).

Here are two examples of sitelink extensions in action (2 Formats):
Example of Sitelink Extensions in Bing Ads for Lucky Jeans

 

Example of Sitelink Extensions in Bing Ads for Adidas

So, let’s say you set up sitelink extensions for some of your campaigns, and you’re basking in the glory of those beautiful ads (and the click through they are getting).  But, maybe your reporting isn’t lining up clicks and visits-wise.  Sure, there are several reasons that could be happening, but maybe it got worse since you launched sitelink extensions.  Well, the reason could very well be the lack of tagging on your ad sitelinks.  If those additional URLs aren’t tagged properly, then your analytics package could very well be reporting that traffic as organic search.  And that would be shame.

In this post, I’m going to walk you through why this could be happening, and how to rectify the situation.  After reading this post, you might just run to Bing Ads today and make changes.  Let’s jump in.

Sitelink Extensions and Tracking Parameters
In Bing Ads, you can include sitelink extensions several ways.  First, you can add them manually via the Bing Ads web UI.  Second, you can use Bing Ads Editor to add them locally, and then upload them to your account.  And third, and possibly the top reason ad sitelinks don’t get tagged, is that you can import them from AdWords via the “Import from Google” functionality.  Note, the import from AdWords functionality is awesome, so don’t get me wrong.  It’s just that it’s easy to import ad sitelinks and not know they are there.  Then you run the risk of uploading untagged sitelink extensions.

How To Create Sitelink Extensions in Bing Ads

So, you need to make sure that your ad sitelinks are tagged properly, based on the analytics package you are using to track campaigns.  For example, if you are using Google Analytics, then you need to make sure that you identify each click coming from your sitelink extensions.  That means you should be appending tracking parameters to your sitelink URLs.  For Google Anlaytics, you can use URL Builder to tag your landing page URLs.

Tagging Sitelink URLs Using URL Builder

 

How To Tag Your Ad Sitelinks in Bing Ads
Again there are various ways to include sitelink extensions in your campaigns, from using the web UI to using Bing Ads Editor to using the “Import from Google” functionality.  I’ll quickly cover each method below to make sure you know where to apply your tracking parameters.

1.  The Bing Ads Web UI
You can currently apply ad sitelinks at the campaign level in Bing Ads.  When you access a campaign, you can click the “Ad Extensions” tab to include ad sitelinks.  Once there, you can click “Create” to add a new sitelink extension.  If you have other sitelink extensions set up across campaigns, you will see them listed (and you can apply those to your campaign if it makes sense).

Creating Sitelink Extensions Using the Bing Web UI

If you want to add a completely new sitelink extension, then click “Create New”.  When adding the sitelink extension, Bing Ads provide a field for link text and then a field for the destination URL.  When you add the URL, make sure your tracking parameters are added!  If not, your visits will show up as “Bing Organic” versus “Bing CPC”.  Good for the SEO team, but not so good for the paid search team.  :)

 

Adding Sitelinks Using the Bing Web UI

 

2. Bing Ads Editor
I love Bing Ads Editor.  It’s an awesome way to manage your campaigns locally and then sync with the Bing Ads web UI.  And as you can guess, there is functionality for adding and editing sitelink extensions in Bing Ads Editor.  You can access your sitelink extensions by clicking the “Ad Extensions” tab for any selected campaign.

Once you click the “Ad Extensions” tab, you can add sitelink extensions by clicking the “Create a Sitelink Extension” button from the top menu.  Then similar to the web UI, you can add the link text and the destination URL.  When adding your destination URLs, make sure your tracking parameters are added.

Adding Sitelinks Using the Bing Ads Editor

 

3. Import from Google (in Bing Ads Editor)
As I explained earlier, I love having the ability to import campaigns, changes, etc. from AdWords directly into Bing Ads Editor.  It makes managing campaigns across both platforms much more efficient.  But, I’ve seen advertisers import campaigns from AdWords that have sitelink extensions, but they don’t realize it.  Then they upload their campaigns to Bing Ads and don’t understand that prospective customers are clicking their sitelinks, visiting their sites, etc., but those visits aren’t being tracked correctly.  Again, those visits will show up as “Bing Organic” in your analytics reporting.

When you go through the process of importing your campaigns, make sure you double check the “Ad Extensions” tab for the newly-imported campaign.  You just might find sitelink extensions sitting there.  And yes, they very well could be left untagged.  Make sure you add your tracking parameters before uploading them to Bing Ads (from Bing Ads Editor).

You can also uncheck the “Ad Extensions” radio button when importing your campaigns from AdWords.  Then you can add your sitelink extensions directly in Bing Ads Editor (via the second method I covered earlier in this post.

Importing Sitelink Extensions in Bing Ads Editor

 

Sitelinks Are Powerful, But Only If They Are Tracked
Sitelinks extensions are a great addition to Bing Ads, and they absolutely can yield higher click through rates.  But, you need to make sure those clicks are being tracked and attributed to the right source – your Bing Ads campaigns!  I recommend checking your campaigns today to make sure your sitelink extensions have the proper tracking parameters appended.  If not, you can quickly refine those links to make sure all is ok.   And when everything is being tracked properly, you just might see a boost in visits, orders, and revenue being attributed to Bing Ads.  And that’s always a good thing.

GG