SEO KPIs

Clients, it turns out, want to see how the efforts they’re paying for are working.We show clients lots of reports that indicate the success of their SEO campaigns, and KPIs are slightly different for ever client depending on what kind of a site they have, what their goals are, etc. However, there are three univeral SEO Key performance indicators that we use for everyone.

• Traffic: Our major KPI for Search engine optimization is the increase of inbound organic, non-branded traffic month over month (or year over year etc.)
• Rankings: A lot of clients come to us obsessing about rankings and to tell you the truth, we’re obsessed about rankings too. But it’s impossible, simply impossible, to use a 3rd party tool to figure out every single derivation of a short-tale key phrase that might possibly rank. Sure we track a select list of short tale key phrases in order to provide a barometer for the campaign, but the only purpose for getting higher rankings is to increase quality traffic to the website which brings us back to our main KPI.
• Links: As we all know, increasing inbound links plays a huge role in getting a site ranked higher. Therefore, another SEO key performance indicator for us is the quantity of inbound links we generate. There are lots of external tools you can use to track these links like Majestic SEO and Open Site Explorer, but you can use Google Analytics to keep tabs on them too, assuming you build quality links that get traffic as well as raise rankings.

Tracking Traffic In Google Analytics

This is usually ridiculously easy to track through Google Analytics if you use the old interface. If you use the NEW interface, the score card no longer shows comparisons with past data, only comparisons to the site average, which, in my opinion, is super, super lame. You just use Advanced segments to filter out everything but non-paid organic search traffic and run a keywords report and filter out the brand name. Easy right?

Well, what if you’re only responsible for optimizing a certain section of a site. For instance: For internal political reasons, one of our larger clients has a lot of editorial leeway on a specific section of their site where they can make all the on-page optimization changes (titles, metas, copy and headers) changes that we ask for.

For this reason, we’re optimizing just that section of their site. So how do you measure SEO success just for that section? For the purposes of protecting client information, I’m going to use LunaMetrics data instead for this instance. Say I’m responsible for optimizing the Blog section of the site. This section is www.lunametrics.com/blog. So in order to find traffic progress month over month, I’d do the following:

Step 1. Get the correct Date Comparison in Google Analytics. In order to make a clean comparison and take the weekly dips in traffic over the weekends into consideration, I start the date comparison on the same day of the week, even if it means going a bit into the previous month:

Google Analytics Date Comparison

Step 2. Under Traffic Sources, choose Keywords.

Google Analytics Keywords Report

Step 3. Make sure you click the “non-paid” link to make sure you’re filtering out any paid search. We don’t want to take paid search into consideration while we try to judge the efficacy of organic search efforts.

Non Paid Keyowrds

Step 4: Choose the Landing Page secondary dimension

Landing Page Secondary Dimension

Step 5: Using the advanced filter, filter out branded keywords and the landing pages that are in the section you’re considering.

Google Analytics Advanced Filter

Advanced Filter Example

Step 6: Enjoy your report which shows how many people landed on the page in the section you are concerned with through organic search and which keywords they found that page with. Both the number of visits and the quantity of keywords should go up month over month.

Blog Traffic Increases

Tracking Inbound Links in Google Analytics

We use the Referral report as one way to track inbound links from other sites. Get it? Cause the linking sites refer traffic? There are a couple ways to use the referral traffic data. If you’re keeping a list of sites that from which you’re pursuing links, you can simply filter the referrals page for those sites and see if you’ve started getting any traffic from them. Even one visit means someone came from a link on that site.

Referral Traffic in Google Analytics

If you’ve got a strong link-bait campaign going, you can track progress on that by choosing the secondary dimension “landing page” and then filtering for the page that you wrote as link bait.

Referral traffic to Link Bait

Hopefully this has given you some good insights into how to judge the efficacy of your SEO campaign using  nice, free, easy-to-use Google Analytics. Happy Analysis!

How to use Google Analytics to Track SEO Progress is a post from: Google Analytics, SEO, Social Media and PPC blog

aka “Catching the Purple Squirrels”

Google officially recommends not to use more than one include filter, because it can lead (rather unintuitively) to excluding all the data in an Analytics profile.

“Adding more than one Include filter to a profile can cause data to not appear in your reports. To allow data to populate your reports again, we recommend assigning a maximum of one Include filter to each of your profiles.”

But sometimes using more than one include filter is the only way to catch the purple squirrels. Let me explain.

When One Include Filter Isn’t Enough

A reader sent us this question:

“I’d like to create a GA profile and to apply one filter to include only the SE organic traffic coming to a specific part of my site…. For example, all the traffic coming from SE organic to www.example.com/mydir/”

Unfortunately, even though he’d thought outside the box and (very creatively!) tried to use a single include filter based on Campaign Target URL, he was not successful.

In this case, a single include filter will simply not suffice. He needs one include filter for the traffic medium (organic) and another include filter for the set of pages visited (the specific subdirectory).

Why Using More Than One Include Filter Can Exclude All Your Data

So what’s the problem with using more than one include filter? Why does Google recommend against it? Here are two helpful tips to remember:

• When it comes to filters, “include” means include only (i.e., exclude everything else)
• When applying multiple filters, imagine the word “and” between them

If you remember those two things, then applying filters like the following will obviously exclude all your data:

“Include only squirrels AND include only dogs AND include only cats…”

It all boils down to the types of data you’re trying to include. Ask yourself, can members of one type be members of another type, or are they mutually exclusive?

Why Using More Than One Include Filter Can Be Okay

Our reader is trying to include two types of data that are not mutually exclusive. He needs to include data from organic search traffic and data from pages in a specific subdirectory. Viewed another way:

• Data from one subdirectory is our set of squirrels (a different subdirectory could be dogs, etc.)
• Data from one medium is our set of purple things (a different medium could be yellow things, etc.)

And here we want data that belongs to both sets, i.e. the elusive purple squirrels.

In this case we absolutely can use two include filters. We can say “include only purple things and include only squirrels” because then we’ll end up with the purple squirrels.

How To Catch the Purple Squirrels

First, the standard warning. Don’t apply new filters to existing profiles! Always create a new profile or use a test profile to “test drive” new filters and make sure they get the data you want.

Now create your two include filters. Navigate to the new/test profile, then go to the Filters tab and click +New Filter.

To include only organic traffic, create a custom filter. Choose “Include” and Filter Field “Campaign Medium” and Filter Pattern “organic” (don’t include the quotes). Click Save.

Then create another filter to include only traffic to a subdirectory. You actually have two options here: One way is to create a predefined filter. Choose “include only” and “traffic to the subdirectories” and “that are equal to” and then enter the subdirectory, such as /mydir/.

Predefined vs. Custom Filters

The drawback to the predefined filter is that it does not recognize regular expressions. (Say what? Check out our free e-book for an easy intro to regular expressions.)

So the other way to include only traffic to a subdirectory, and the only way if you need to use regular expressions, is to create a custom filter. Choose “Include” and Filter Field “Request URI” and Filter Pattern ^/mydir/.

In a custom filter I can use special characters from regular expressions, like the caret (^). The caret means “starts with”. So I enter Filter Pattern ^/mydir/ if I want to match pages like /mydir/abc.html but not /sub/mydir/abc.html. To match /mydir/ at any level, just leave the caret off.

And voilà! With an include filter for organic traffic and an include filter for /mydir/, our reader has a new profile containing exactly the data he wants.

But one more thing before I go…

Catching Squirrels and Dogs

Remember how I said you can’t include only squirrels AND include only dogs? We can actually work around that, using custom filters.

What I’ll do is create a custom filter that says “include squirrels OR dogs” because I can use a special character from regular expressions called the pipe (|). The pipe, or vertical bar (found above the Enter key on most keyboards), simply means “OR”.

To include traffic to /mydir/ or /mydir2/ create a custom filter, choose “Include” and Filter Field “Request URI” and Filter Pattern /mydir/|/mydir2/.

To match pages that have to start with /mydir/ or /mydir2/, change the Filter Pattern to ^/mydir/|^/mydir2/.

What are some other issues you’ve had with filters? Have you discovered creative ways to get the data you need? Let me know in the comments.

How To Use More Than One Include Filter (without losing data) is a post from: Google Analytics, SEO, Social Media and PPC blog

We wrote recently about a visitor who asked about enforcing capitalization consistency in URLs in Google Analytics. This is a pretty common thing.

In fact, there are a variety of ways your URLs can show up in inconsistent ways in Google Analytics. What you should recognize is, whatever the URL of the page is in your browser is what Google Analytics records. Now, often your webserver treats slightly different URLs as exactly the same page (differences in capitalization, leaving off a trailing slash, and so on). So if multiple versions of a URL are, in actuality, the same page, we want to clean up those URLs in Google Analytics.

Default pages

Here’s one scenario: you look in your Top Content report and you see your home page in a couple of places, like this:

• /
• /index.php

Or something like that. (Remember the URLs we see here are only the part after the .com or .org or whatever. So one of these represents http://www.example.com/ and one represents http://www.example.com/index.php.) We know these are both really the home page, but seeing them as two separate URLs in this report isn’t very helpful. We have to add up the pageviews for both to see what the total number is.

Google Analytics gives us a simple way to fix this. It’s in your Profile Settings and it’s this one right here:

Here, we can just put in “index.php” as the default page. Now Google Analytics will just add “index.php” to any URL that ends in a slash. Tada!

Multiple default pages

That doesn’t work for every scenario, however. Consider this:

• /
• /home.php
• /careers/
• /careers/index.php

Well, we can’t go and use the “Default page” setting from above, because now there are multiple possibilities, depending on where we are in the site.

Or, for that matter, what if we like the nice, clean, trailing slash URLs and want to get rid of all the index.php?

Well, this you can do with a Search and Replace filter. The setup looks like this:

Notice that I’m searching for anything ending in “/index.php” (the dollar sign means “end with” in Regular Expressions). I’m replacing that with just the slash. In the example above with both “index.php” and “home.php”, I could just create two filters, one for each one. Once I’m done, for my data going forward, I just get the trailing-slash versions of the URLs.

Trailing Slashes

Here’s one more thing that can be a problem, and this one is really challenging:

• /careers
• /careers/
• /careers/index.php

We’ve already solved the “index.php” problem. But notice we also have a problem with slashes. A lot of webservers automatically correct for this kind of thing with redirects. (Here’s some information on how to do it with Apache.) But if yours doesn’t, you can fix the data in Google Analytics (again, with filters).

This one is a little hard, because the patterns we want to match are kind of ambiguous. Here’s what I came up with, but chime in on the comments if you have a cleaner solution.

So, here’s the regular expression I used to match these URLs:

^(/[a-z0-9/_\-]*[^/])$

OK, so it starts with a slash (duh), then it contains 0 or more characters that are alphabetic (a-z), numeric (0-9), or an underscore or hyphen. (You may have to adjust a little if you have other characters in your URLs). Then it ends with a character that is NOT A SLASH. (That’s the important part.)

Why such a specific Regular Expression? Why not just:

[^/]$

That says “ends with any character that is not a slash”. Well, unfortunately that’s probably not specific enough. Because we might have pages like the following:

• /careers/jobs.php
• /careers/?search=web%20analyst

Notice that neither of those end in a slash, but they’re not the kind of URLs we want to end in a slash, either. So we need a regular expression that doesn’t match a few key characters (like the dot and question mark) that clue us in we don’t have just a directory name, but a full page in the URL.

So then the Advanced Filter just grabs the original part of the URL and appends a slash to it.

So that’s a variety of instances in which you have opportunities to clean up URLs and improve the data you have in Google Analytics.

Cleaning up URLs in Google Analytics is a post from: Google Analytics, SEO, Social Media and PPC blog

Today, while reading our KissInsights, I saw this question:

“[I came to your site to] learn how to aggregate all pages that are the same to be the same page when using Google Analytics. Currently, we have a number of instances where the same page shows up multiple times because the page is capitalized in one case and not in the other.

I know we’ve come really far in GA since we were force to use lots of filters and profiles, but this truly is a case for filters. In fact, there is a special lowercase filter for this (and one to use if you want to make everything uppercase, too.) Go create a new profile (never experiment on your production data, someone once told me) and then create a new filter, like the one I have below:

Robbin

Capitalization and GA: Basic but necessary is a post from: Google Analytics, SEO, Social Media and PPC blog

It sometimes happens that someone will accidentally use your GA Web Property ID (UA-xxxxx-y) in their website.

When this happens, pageviews and visits from their website will show up in your GA reports.

To prevent this, you can create a filter and apply it to your main profiles.

The screenshot shows the use of a Custom -> Include filter on the Hostname field.  This example is for the site cats.com.

We are only including pageviews that happen on a domain that matches the regular expression “cats.com”.  This will match all of your subdomains such as my.cats.com or pictures.cats.com.

Website spanning multiple domains:

If you have a website that spans multiple domains such as cats.com and mycats.com and bluecats.com, then instead of filtering on “cats.com” you simply list all your domains, separated by a pipe:

Instead of:

cats.com

use:

cats.com|mycats.com|bluecats.com

Note:
If you have a profile that doesn’t have any filters on it, for raw data and troubleshooting, make sure you don’t add this filter to that profile.

Filtering out traffic that is not from your website is a post from: Google Analytics, SEO, Social Media and PPC blog

Recently, a reader sent a question to me about ways to create a “member only” segment. He wrote this:

“I was wondering if I can create an advanced filter [emphasis mine] that would create a profile for subscribers (url containing /authenticated/) and non-subscribers?”

I like to use filters and profiles a lot. That is why this reader wrote me, and in his email (not copied fully here), he even referenced blogposts I have written about filters.

However, this particular problem is really a job for Advanced Segments. First, let me explain the issues that one usually faces, then let me explain why they don’t matter here:

The issues: One of the big differences (but not the only difference) between using Advanced Segments vs Profiles/Filters comes into play when you want to look at only specific pages. Example, only pages that include /blog/ or only pages that include /shopping/ etc. With profiles and filters, you can include just those pages. With Advanced Segments, you will get a segment of all visits that included a trip to the page(s) that are being included. Advanced Segments are arguably the most useful when you are looking to segment by type of user: only users who came from India, only users who arrived by an email click, etc.

Why they don’t matter here: This individual, who wrote me, wants to segment between member and nonmember, and notice he pointed out that the difference between them can be easily understood — members are those that visit a page with /authenticated/ in the URL. So all he needs to do is create an advanced segment at the page level, like the screenshot below. When the segment includes only visits to pages that include /authenticated/ in the URL, it really means it includes all visitors who included a trip to one of those pages in their visit. In this case, he will be able to harness the problem of Advanced Segments (it pulls in ALL the pages of a visit if it includes the specified page) and use it to his advantage (he WANTS to see all the pages of those visits.) The result will be that he’ll have an easy-to-create Advanced Segment with retroactive data.

Sidenote: One problem with this solution is that some members might visit the site and not visit a page with “authenticated” in the URL. A better solution might be to create a visitor-level custom variable that would get set whenever a member did visit an authenticated page. That implementation would mean that the member would have his “membership” stored in a cookie on the browser, and it would persist across many visits, including those where he didn’t visit an authenticated page.

Robbin

Advanced segments for member/nonmember is a post from: Google Analytics, SEO, Social Media and PPC blog

Ever since starting at LunaMetrics, I’ve become increasingly immersed in and enthralled by Google Analytics. I thought I knew a lot about it before, but every day I find out about a new way to mine and organize the data I need on a day to day basis. I also think it’s interesting that the more one knows about how to do things, the more one comes to rely on the resulting reports.

My recent find, thanks to my coworker Jim, is a unique use of the new secondary dimensions and pivot function.

Keyword Research and Google Analytics

There are a number of ways to do keyword research using Google Analytics, but until the addition of the secondary dimensions, there was no easy way of extracting actionable data from keyword reports generated by Google Analytics.

For instance, have you ever done a GA keyword report, found an unexpected keyword in the top ten and wondered where in heck the user found your site by searching for it? Well, now you don’t have to wrack your brains and search through every single search engine ever created.

Lets say you are doing keyword research. You want to find out the following:

• What keywords are bringing users to the site
• What landing pages are those keywords bringing users to
• What source is directing traffic through those keywords (Google, Yahoo, Bing, PPC Campaign etc.)
• How qualified is the traffic that is coming from those keywords

Generating the GA Keyword Pivot Chart

All of these things can be found in one easily generated report. Here’s now to create it:

1. Go to Traffic Sources in the Dashboard and choose Keywords
2. Refine your report by clicking “Non-Paid” so that you only see keywords used in organic search
3. Choose “Pivot” From the available views. (This is where it gets good!)
4. Keep the default Pivot selection “Source”
5. Keep the default metric “Visits”
6. Add “Bounce Rate” from the adjacent drop-down.
7. Keep the dimension “Keyword” then add “Landing Page” next to it.

Voila. You have a list of keywords, what landing page they go to, where the visitors came from and bounce rates or whichever metric you’re most interested in.  If you get a lovely list of branded search terms, use the advanced filters to exclude those keywords. It’s much easier now that you don’t have to type in all the regular expressions anymore. Here’s a screenshot of what the final product should look like:

There are many things this information can tell you among which are:

• Conversion Stages: To see what stage of the buying process users are at when they reach a certain page.  Long tail keywords usually denote a readiness to buy/convert whereas shorter phrases typically indicate a research phase.
• Traffic Quality: If you’ve done your homework right and you’re drawing traffic in through keywords that you’ve optimized for, but you’re lacking conversions or continue to have a high bounce rate, you could be going after the wrong keywords.
• Usability: Once you know what keywords visitors are using to get to your site,  you can tailor the pages to fit their goals.
• Keyword Potential: There could be keywords that you never though of in this list. Take them into account when setting up an PPC campaign, or deciding how to further optimize the page.

I hope you found this report as useful as I find it! I’d love to hear about other uses or variations. Feel free to comment!

Who loves GA Secondary Dimensions and Pivot Functions? I do, And so will you! is a post from: Google Analytics, SEO, Social Media and PPC blog

There is one particular mistake I see over and over with regard to setting up filters in Google Analytics.  This has been talked about before, but it comes up so often that I don’t feel bad about addressing it again (and again, and again).

The Mistake

Multiple Include Filters, causing no data to get into the profile.

What it looks like

1. Include – Request URI – /page.html

2. Include – Request URI – /other.html

What is intended?

The person that adds these 2 filters to a profile wants to include both /page.html AND /other.html.

But why doesn’t that work?

The Technical:

When GA processes filters it does so, sequentially, one at a time.  Filters are like a series of gates, in-line, along a road. In order for data to get from point A to point B, it has to pass through each gate in turn. If there is any one gate that it can’t get past, then no point B and it doesn’t end

up in the profile.

Each Include filter can be thought of as an “Include Only” filter.  Let’s look at the 2 example Include filters above with that wording in mind, and see how far our data makes gets.

Data –> A) /page.html, B) /other.html, C) /index.html

1. Include – Request URI – /page.html
2. Include – Request URI – /other.html

The first thing that happens is our data is checked against Filter 1.

Filter 1 says “Include ONLY data that has a Request URI that matches /page.html”
Data A matches /page.html
Data B does not match /page.html
Data C does not match /page.html

Now we have
Data –> B) /other.html, C) /index.html   -> didn’t make it past the filter
1. Include – Request URI – /page.html
Data –> A) /page.html
2. Include – Request URI – /other.html

The only piece of data that made it past Filter 1 was Data A, /page.html

Now it is tested against Filter 2, which says “Include ONLY data that has a Request URI that matches /other.html”

/page.html, is tested against Filter 2, /other.html.  It does not match, and ends its trip short.

So, no data in our set can possibly make it past both filters, since there is no single page that can match BOTH /page.html AND /other.html

The Solution

The solution is to use a single filter that looks like this:

1. Include – Request URI – /page.html|/other.html

We put both pages that we want to include into a single filter and seperated them with a pipe.  The pipe is the vertical bar symbol usually located just above the Enter key.  This is a Regular Expression (RegEx) symbol that can be read as “Or”.  So the filter says Include ONLY pages that match either /page.html OR /other.html.

Mistakes with Include Filters is a post from: Google Analytics, SEO, Social Media and PPC blog

Google announced lots of new features last week, and one of the most exciting is Advanced Segments. There are already some great posts out there in the analytics blogosphere explaining what Advanced Segments are all about and how to use them (here’s one from Justin Cutroni, and one from Avinash Kaushik). But we wanted to take a few minutes to compare and contrast using Advanced Segments vs. using profiles and filters to get a different view of the same site.

Up until now, there were some reports in Google Analytics, like the Visitor Loyalty reports and the Funnel Visualization report, that you could only segment by creating a new profile for your site with filters on it to get just the traffic you want. For example, do you want to see the Visitor Loyalty report just for your paid search visitors? Create a profile that only includes your paid search traffic. We’ve done lots of posts about filters in the past detailing how they work to set up exactly these kinds of things.

With Advanced Segments, though, many of these reports can be segmented. Here’s a screenshot of a segmented Visitor Loyalty report. (The Funnel Visualization report, sadly, remains un-segmentable.)

And the real upshot of using Advanced Segmentation is, you can look back historically on the data! With profiles and filters, the changes you make only have an effect from the time you make the change going forward. With Advanced Segmentation, the report instantly shows you the segments for the historical data you have.

Advanced Segmentation has several other advantages as well. You can see multiple advanced segments simultaneously in the same report.

You can also create advanced segments that wouldn’t have been easy or even possible with filters, such as segments for visits with metrics in a certain range (more than 3 pageviews, more than 2:00 on site, and so on).

And finally, the interface for creating advanced segments is much more intuitive than creating filters — you don’t necessarily need to understand regular expression to create most advanced segments you can dream up.

So given all this, who even needs to use profiles and filters any more? Forget them! Well, not exactly. There are still several very good reasons for using profiles and filters. One is for kinds of traffic you almost always want to exclude from your reports, such as internal traffic from your organization to your website (you don’t want your employees counted as visitors in most cases — and IP address isn’t a dimension you can use for creating Advanced Segments anyway). You’ll also still want additional profiles to handle more than four goals. And lastly, you can manage access to profiles with the User Manager, so it’s easy to keep track of who can see which sets of data — you can assign different users to different profiles as either read-only users or administrators. (Advanced Segments, on the other hand, are tied to a particular user’s login, like the Dashboard or email preferences. Each user has their own set of Advanced Segments that are available on whatever accounts or profiles they have access to.)

So here’s a summary of the differences between the two approaches…

Advanced Segments:

1. Segment previously un-segmentable reports (except Funnel Visualization), including historic data.
2. See multiple advanced segments at once in the same report.
3. Types of segmentation that weren’t possible with filters: visits with conversion, visits with more than 3 pageviews, visits that spent more than 2:00 on the site, etc.
4. More intuitive to set up for non-technical users.
5. Tied to a user login.

Filters & Profiles:

1. Still useful for filtering certain kinds of traffic you almost always want to exclude, like your internal traffic.
2. Segment the Funnel Visualization report.
3. Use multiple profiles for more than four goals.
4. Tied to the Google Analytics account, manage access with the User Manager.

- Jonathan

Advanced Segments vs. Profiles & Filters is a post from: Google Analytics, SEO, Social Media and PPC blog

On a post way back in April on Custom Advanced Filters, Idris left a comment asking about the required/not required selection (seconded by Paul):

Hey, great articles. I am trying to do some advanced filtering, but I’m confused by the “Field X Required” option. If I say “Yes” to the requirement, which of the following two things does that mean?

a. If the regex in this field does not match, do not include this hit in the profile at all.

b. If the regex in this field does not match, skip this filter, and move on to the next, but still include these hits in the profile.

These two are obviously very different. Which does Google Analytics do?

The confusion is about what exactly is “required”. We were pretty sure we knew, but we did an experiment to confirm. It’s basically b from what Idris suggested.

Here are the details:

1. If the field is required and the regex matches, the output is written to the field you select.
2. If the field is required and the regex does not match, the output is not written to the field you select.
3. If the field is not required, the output is written to the field you select regardless of whether the regex matches.

In no case are the pageviews excluded from the profile entirely (you need an exclude filter for that). The filter just doesn’t apply if the field is required and it doesn’t match.

Advanced Filters with Fields Required/Not Required is a post from: Google Analytics, SEO, Social Media and PPC blog