Archive for the ‘Filters’ Category
Posted on October 21, 2007 by Robbin Steif
I have been working on this series, Filters for Google Analytics, for almost six months now. This is the last part of the series I am going to write (at least in the foreseeable future.) You can get the full thread at the bottom of this post.
So once again, I will start with the question a lady asked me on Friday morning: how does one create exclude filters that function as if they were AND filters? How, she asked, can I create a profile and put on it two different exclude filters that work together: Exclude the visit if the visitor is a new visitor AND her language is German? We can’t do that with two separate exclude filters, because as soon as the first filter works, the visit gets thrown out. Exclude filters are, by nature, “or” filters.
(If you are a little lost, and don’t remember how multiple exclude filters work like OR filters and multiple include filters working like AND filters, and how you have to work to make them do the opposite — see this post that I wrote recently.)
Well, I had to think about this one, and then realized that it was just a great practice for this series on filters for GA. The reason why: It is both a rewrite (custom advanced filters) and an exclude (custom filter). Here is the overview: you rewrite the two fields into one field, and then you do an exclude on that one field, making sure that it matches both pieces of data.
If that was clear as mud, or you are more of a step-by-step “please show me” person (like I am) — then this is a good place to keep reading.
First, you use a custom advanced filter to rewrite the data so both pieces of info — the visitor language and visitor type, which is GA-Speak for “new” vs “returning” visitor — are in the same field. Like this:
Now we have both pieces of data in the same field. If we could look at them, they would look like this, concatenated together on the same line.
1. en-us/New Visitor
2. de/Returning Visitor
3. da/New Visitor
and so on. They would be the language code followed by a slash and the visitor type. (Right? That’s the way I set it up, $A1 captures everything in visitor language settings, then a slash, then $B1 captures everything in Visitor Type.) Above, I choose three languages for my examples: English-US (en-us), German (that’s de) and Danish (da).
Next, we create an exclude filter. The hypothetical example was to exclude a new visitor whose language is German – the two excludes that must work together. This is the heart of our problem, exclude two different kinds of variables. So here is our exclude:
So what does this say? It say, go to Custom Field 1, where we now have a list of concatenated languages and visitors types (en/Returning Visitor, and so forth). If one of those lines in the list matches de (which stands for German – Deutch, right?) and has a slash and then the word new, it’s a match, so please exclude it.
And that’s how you can exclude two different fields in Google Analytics at the same time.
If you would like to read all the other posts in this series:
View Comments (24 Responses) | Categories: Filters, Google Analytics
Posted on October 7, 2007 by Robbin Steif
I spoke about implementation Google Analytics on Friday, and someone asked me, “How do I create Exclude AND filters?” This is a cool question, but it has to wait until I write the info below on how Google applies your filters (and how that differs on Include vs Exclude filters.) Note: you can read the GA documentation on this one, which is not terrible.
You might consider include multiple filters to be AND filters, when you think about the way that GA applies all of them to a profile. So if you create a profile where an include filter specifies Visitor City = Pittsburgh, and the another include filter specifies Campaign Source = organic, you will filter in only visits that came from people in Pittsburgh who used the organic search to find you. It’s not good enough that they came from Pittsburgh and used paid search, or followed a link. Both criteria must be met.
Exclude filters, on the other hand, could be looked at as OR filters. If the visit matches any of the exclude filters in a single profile, it is thrown away. So using the same example as above, Visitor City = Pittsburgh, and the Campaign Source = organic, you will exclude anyone who comes from Pittsburgh, no matter what their campaign source. And you will exclude everyone who comes on an organic search, no matter what their city.
There are ways around the AND and OR issues. For example, let’s say that I wanted to include everyone from Pittsburgh OR Raleigh. I cannot do it with two separate city filters — right? Include filters are AND filters, so two separate filters would say: include everyone who comes from both Pittsburgh AND Raleigh, which is a pretty hard act. But you certainly could do include visitor city = (pittsburgh)|(raleigh). By putting both cities in the same filter with an OR pipe, you achieve that goal.
Now that I showed you how to defeat the “ANDness” of Include filters, you will be wanting to know, how to do defeat the “ORnesss” of Exclude filters. Plus, you might want to know how to make include filters be OR filters for different kinds of fields — include if they came from Pittsburgh OR they came organically.
But that is a different topic and a new post. Maybe even tomorrow.
View Comments (8 Responses) | Categories: Filters, Google Analytics
Posted on June 26, 2007 by Robbin Steif
Before I start (again) – this is the last reminder that the Criticize GA’s Documentation Contest ends on Tuesday the 26th. Which is probably today already if you are in Australia.
I have been doing a series on filters for Google Analytics, and am almost done. I have two more posts coming up, and then it feels like I have finished.
However, I read the Google Groups for GA and I can see that the combinations of problems people have are always amazing. So if you have a filters question that I haven’t answered yet — and it is not about cross-domain work, since that will be a different series — please send it my way. You can comment or send email to my last name at lunametrics.com — whatever is easiest for you.
Robbin Steif
LunaMetrics
(see, there is all the info you need to send the email)
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Posted on June 14, 2007 by Robbin Steif
This is part of a series I am writing on filters for Google Analytics (and when I am all done, I promise to thread them all.) This current entry is a particularly beautiful capability of GA, but you might want to first read about Custom Advanced Filters if you aren’t terribly familiar with them (my most recent post in this series.) I will do just the tiniest review, else this will get too long.
Just the Tiniest Review: In a Custom Advanced Filter, you get a field A and a way to extract it into a Regular Expression, and if you like, a Field B and a way to extract that one into a RegEx, too. Then you can play with them — put them together, for example. That’s what output to constructor (the third area) is all about.
New: But what if you wanted to put together more than two fields? That’s a job for Superman Cascading Custom Advanced Filters. BTW, I made up that name. I haven’t found that one in the Google Analytics documentation, but I don’t know what to search under. (Now, if I could enter the contest, I would submit this entry. But the rules are, I can’t win.)
Back to business: so, let’s say that every day your boss wants a report that tells her what keywords people were searching on, what was the source, which ad they clicked on, how many pages they looked at and did they convert? None of this is hard in Google Analytics – the hard part is getting the information easily and quickly. What do you do when you have 50,000 keywords and you need the information for your boss every day? What do you do when your boss wants that report to also include geographic location and browser size?
(Note: Caleb Whitmore from POP, who taught me how to do cascading custom advanced filters and gets a ton of credit here, calls these Insane Filters, because, “who has time to look at 50,000 keywords every day?” And in fact, I have made my example here pretty simple compared to the one that I did for a customer last week, which included seven filters.)
So remember our fairly simple example: we are looking to get keyword – source – Ad Title – pages/visitor – conversion rate.
We start by creating a filter that will associate keyword (Campaign Term) with source, and we’ll dump in into Custom Field 1. If you are now a little lost , please read this post on how to create Custom Advanced Filters. Here is a screen shot:
Now comes the “cascading” part. In this second custom advanced filter, we pick up Custom Field 1 as our A, we pick up the next thing we need, Ad Title, also known as Campaign Content, as our B, and we associate them in the constructor, but this time we put it into its ultimate resting place.
So what do I mean by that? With the final filter, you decide which report you are going to plop it all into — that’s what goes in the “output to” field. The decision on a report is important – the report you choose will give you specifics you might need. For example, if you want conversion rate, don’t drop it into your Top Content report (because you don’t get conversion rate there.) I have been using Visitor > Languages for this (but even if you have a seemingly obscure report like languages, you should create a custom profile for this work.) Notice that I didn’t do any work on pages/visitor or conversion rate, even thought I need it — that info will come automatically with the report, if I choose it correctly.
When you get the report, the first column will look like this:
shoes,google,Buy Red Shoes for $5
Right? First comes the keyword, then a comma, then the source, then a comma, and finally the name of the ad. This is how we associate more than two fields. The reason that I used seven filters for a customer last week was because they needed us to associate eight fields (i.e. you can keep doing this, and only in the last filter do you choose where to put the data.)
The other information (pages/visit and conversion rate) will be the same as always, in columns on the right. Plus there may be data you don’t care about, depending on the report you chose. Either way, all you need to do is export to Excel and voila! there is your report.
Tips and tricks: It is nice to use a comma in the constructor (i.e. like this: $A1,$B1) . That way, your file already has commas and separates nicely. However, depending on your data, you might have other commas get in the way. For example, just think of the mess you would make if your ad title was Shoes, Sandles, More — each of those would go into a separate cell in Excel. So a better way to go might be with a separator that isn’t used as often, maybe a slash or a star * or …. well , you get it. There is probably a way to get Excel to recognize those, but I generally have to export to a notepad and tell the notepad the name of the delimiter.
Also in the tips and tricks area, there is no reason that you can’t dump the whole thing back into your final field with each filter. So if you report is going to end up in Languages, you could always have every constructor go to Languages. But my advice is to resist that temptation and use the custom field until you get to the last filter. It’s a pain to get all your work done and start to get data, only to realize that the report you chose doesn’t work. If you use Custom all along the way, you only have the change the last filter.
Don’t forget that you can change the order of filters. This might be very important — you might need a different layout of your excel spreadsheet.
And finally — if you learned something here, please submit an entry to the Criticize Google Analytics Documentation contest. You have until June 26.
Endnotes: Thank you to Michael Harrison for telling everyone about the contest. Hearty congratulations to OX2 on your GAAC status. Jeff and Nick and Brian and Helen, thank you for helping me with all my GA endeavors.
Robbin
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Posted on May 20, 2007 by Robbin Steif
Custom advanced filters can be very cool. You can use them to rewrite stuff. And much cooler, you can use them to associate stuff.
For example, you can use an advanced filter to associate a Request URI (a page someone asked for) with a Campaign Medium (the medium they used to get to your site) and then dump it all back into Request URI (so that you can see it in your Content > Top Content report.) Before I go into the technical details, you may be saying, why would I ever want to do that? Well, if you have 10,000 URIs and you want to look at them all in Excel, it would be nice to have a report that you can download into a csv file and then sort any way you like.
So here is a screenshot of what that filter would look like. (Ooh, many thanks to Steve and to our web designer, both of whom gave me the same advice on better screen shots. So now this one is legible:)
Notice the A and B stuff in the middle. Here is what I am telling Google:
My field A is Request URI. Get everything, by using .* and put it in a variable, by using parens, so get-everything-and-put-it-in-a-variable looks like (.*)
My field B is Campaign Medium. Once again, get everything and put it in a variable, hence (.*)
Now comes the magic. Output it all to Request URI. And format it so that I see the A variable (that’s why I used $A1) and then a colon, and then the B variable. That last field, constructor, is not a regular expression. You can write anything you want there — I could have written $A1/$B1, or I could have written, $A1 AND $B1, etc. Also note: in the A field, there is only one variable, (.*), so I used $A1. Same for B. But there might be two variables, and then I would use $A1, or $A2, etc.
Choosing where to output your new mashed up string is important. For example, if you want to see, how many people came through a banner ad medium, touched the home page, and then converted, you wouldn’t want to use the filter I just created — even though it creates the correct information, a mashup of the medium they came in on with the page they touched. That’s became this particular example gets output to content >top content, a report that doesn’t include conversion. A better place to output it to would be campaign name. That way, it will get dumped into your campaign report, which has conversion associated with it.
If you are doing this kind of mashup, it is vital to create a new profile first. After all, you probably need most of the reports “unmashed” for some things, and if you do this in a separate profile, you can mess around all you want, while leaving your production data untouched. Need to learn more about creating new profiles?
Endnotes: Many thanks to Caleb Whitmore from POP, who taught me so much about custom advanced filters when we were at Google training. Caleb actually wrote this particular filter a few months ago. And to Dylan Lewis, for getting our new address right, www.lunametrics.com/blog and for letting his web analyst, Joy Billings, be co-chair of the WAA marketing committee. I have really awesome pictures of both Caleb and Dylan.
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Posted on May 4, 2007 by Robbin Steif
Custom Advanced filters are so cool, and there is so little information available about them. It’s too bad that they have such an intimidating name.
I find myself using them in three ways:
- To rewrite stuff in GA. Usually, this it to rewrite a URI. For example, we work with a site where the CMS insists on calling the same page three different URIs, and we are using custom advanced filters (among other things) to rewrite them, so that we always know what page we are looking at.
- To associate data that aren’t already associated. For example, Benjamin in SF wrote me and asked how to associate a referring source with a transaction ID. This is a job for
Superman Custom Advanced Filters.
- To change all sorts of other things (but which are mostly about #1 and #2.)
So let’s look at a really easy Custom Advanced filter — rewriting all your URIs to be Title Tags. (True, you can already see them in the Content Performance > Content by Title report, but this will rewrite them for every report.)
I want to teach two things before I start.
Thing #1: When I wrote about Regular Expressions, I explained how a dot means, match any one character. And I wrote about how a star means, match zero or more of the previous items. So when you put them together, they mean, match everything.
Thing #2: When you use parenthesis, it create a variable in Regular Expressions. Most of the time, I don’t care. But it really matters in Custom Advanced filters.
Putting Thing #1 with Thing #2: When you write this: (.*) it means, get everything and put it in a variable.
OK, now we are ready to start. Check out the screen shot below
First, I gave it a friendly name (“Rewrite URI, etc.”) Then I chose Custom filters, then within custom, I chose Advanced. As soon as I chose Advanced, I got all the other options below it.
Today, we are ignoring the middle set of boxes, the ones that say “Field B” and are just dealing with Field A and output. So everytime I talk about the A stuff, I am referring to the boxes that say, Field A –> Extract A.
Now, let’s sit back for a moment and think about what we’re doing before we do it. Our goal is to get the page title and to rewrite it — to reconstruct it — so that it shows up everywhere that Request URI might. So instead of seeing URI’s (urls – you can all fight about the correct way to say that), we’ll see page titles.
To do this, we first choose Page Title as Field A (just like we chose filter fields in this post that I wrote last weekend. You have to decide, what are you working on?) Then we extract it — we create a Regular Expression(RegEx) that describes it. In this case, our RegEx is (.*), i.e. get everything and put it in a variable (like I described early in this post.)
Next, we decide where we are going to put it. We want to output it to the URI.
Now, here is the magic (or at least, that’s the way it felt to me as I went through life, trying to understand what $A1 or $B3 was.) The first variable (the first set of parenthesis) in the –> Extract A field is called $A1. We only have one variable in this screenshot, but if we had a second one, it would be $A2. $A3 for the third one (if we had one), and so on. So when we use $A1 as our constructor, it means, use the first variable (.*) in the extract A field to reconstruct our URI.
I know that was confusing, so let me say it another way. Here’s what we did. We took the title tag, and rewrote it as a Regular Expression in the A field. The expression we used was (.*), i.e. get everything and put it in a variable. (So that means, we put the whole title tag in a variable.) Then we told the constructor fields to take the Request URI and rewrite it to be the first A variable — which is now defined as the whole title tag. Consequently, all URIs get rewritten as their page’s title tag.
Please comment if you didn’t understand anything. (I’m serious. I got on someone else’s blog today and said, I just don’t understand.) Or send me email to my last name at my company name dot com.
Robbin
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Posted on April 28, 2007 by Robbin Steif
So now that the basics of custom filters (but NOT custom advanced filters, which will get their own set of posts) have been explored, let’s go through the only two hard parts: What field you are filtering on, and what the Regular Expression(RegEx) might look like. So do you remember this picture? from a couple of days ago:
Filter Field (which was Campaign Medium in this picture) and Filter pattern (the RegEx) are the two hard fields. IMHO. That’s the topic of today’s post. Now here’s the problem: this can be incredibly boring, especially when you get into all the technographic filters, like browser version. So I have picked a few interesting ones, and I hope that readers will ask questions about others.
I already wrote about Request URI and Campaign Medium. Here are a few other interesting filter fields and filter patterns (RegEx) to go with them:
- Referral.
Why/When. Use this when you want to to manipulate (include, exclude, whatever) referrals that aren’t tagged. Examples: blogs or other sites that might link to you on their own. If you have a whole profile set up that includes referrals only, you’ll be able to use tools like your funnels and know that they are peculiar to just your referring traffic.
How: Keep your RegEx as simple as possible, but be careful not to be too broad. For example, if you type in just Yahoo, you will get referrals from both my.yahoo.com and answers.yahoo.com. On the other hand, my\.yahoo\.com will get you just my yahoo (but only in the US, with the .com ending.)
- Page Title
Why/When. Maybe you have a whole bunch of title tags that are the same. You’ve heard that’s really less than optimal (no pun intended) for your SEO. But you may still want to have a filter to include just these pages, so that you can learn more about how those pages are working.
How. It’s pretty easy to mess up the RegEx on this one, so for the example above, start with a carat ^ and end with a dollar sign $, and put the whole title tag in the middle. It has to begin and end with the words you specify, once you have those characters. If you can get away with less, great, but only you know that. (I don’t know your site.)
- Visitor Browser program
Why/When. Maybe you only want to learn about your Firefox users. You might want to learn how many visits it takes for Firefox users to convert, and that report isn’t one you can segment. So a filter works.
How. Type in Firefox. (or for that matter, Opera. Or whatever browser you love/hate.)
- Visitor Language Settings
Why/When: It *would* be very interesting to understand how your French visitors are interacting with your site. Or every more fascinating, how people who speak your language, but live in another country, interact. Like all the people who speak English, but live in the UK or Canada or Australia, etc.
How: Go into your Marketing Optimization > Visitor Segmentation > Language report, and you will see all the two letter (or two letter dash two more letter) codes that Google uses, especially if you pull your report for a long period of time and have lots of data. Google does not seem to use the W3C standard, because I was unable to get a match on either en-us (English for the US) or zh-cn (Chinese PRC.) I have put a list of languages that I cobbled together here – it is not definitive, but is not a bad start. You can use these codes as your Match Field — type in en and you will be filtering on everyone whose browser is set to English of any kind.
- Visitor Type
Why/When. If you have a report that just includes New Visitors (or the other way around), you can do lots of extra segmentation on that segment. So it’s like a segmentation squared.
How. There are only two options here, New Visitors and Returning Visitor. But you might as well keep the pattern matching easy — all you need to do is type in either new or returning.
So please post questions here about filter fields that I didn’t cover, which you might be interested in. ALSO, many thanks to Pittsburgh Bloggers and Loose Tea for updating their links to this blog. to be www.lunametrics.com/blog.
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Posted on April 27, 2007 by Robbin Steif
How do custom filters work for the six options you might attach to a link that you would create in your e-mail marketing, or in your Yahoo! search ads: campaign name, source, medium, term, content and ID? If you want to learn more about some of those options (as opposed to the filtering), check out this blogpost by Meredith Smith from ROI Revolution.
This is an easy one (that’s why I did it today, when I am supposed to be on vacation.) As always, you give the filter a friendly name, you choose Custom, you choose the action you are interested in — for example, do you want to an include filter? — you choose one of those six filter fields I specified above, and you write your regular expression.
So let’s say that you are writing an include filter for just your paid search. We know that Google calls it cpc, but you may have tagged it as ppc in your Yahoo or MSN ads. (Side note: having a filter like this, and applying it to a new profile, would be incredibly helpful, because then you would be able to apply all your GA tools against just your paid search.) Here’s what the filter would look like:
Notice the Regular Expression — the filter pattern — at the bottom. cpc|ppc. The pipe in the middle means OR, so this will capture and include only visits that came on a paid search where the search was coded with cpc OR ppc.
End notes: Many thanks to ROI Revolution for updating their blog with our new www.lunametrics.com/blog info (Yes Tim, you were right when you wrote this comment.) Also to June Li (who has to suffer with me at the Summit), and to Justin Cutroni (who loves creating a separate profile for important campaigns like cpc), both of whom updated their info. And then there is Jacques Warren, who shoes I try to fill at the WAA. And how about this one, AutoJini? (AutoJini, you have to write a comment and introduce yourself to the WA community, or maybe just to me.) And of course, the Benri Blog. I would write about future blog posts coming from Benri, but I don’t want to put too much pressure on the author. Thank you all for updating your info. It comes through slowly in WordPress, I just saw the link from Mine That Data, and I know that Kevin Hillstrom did that update a week ago…
Robbin
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Posted on April 22, 2007 by Robbin Steif
Lots of people subscribed to this blog last week. (Twelve. About 2.5 of all subscribers came in the last seven days.) So if you are interested in conversion or other analytics, please forgive — you just happened to land in the middle of a series about filters for Google Analytics. I really wanted to do this series; I think we need better GA documentation.
So, custom filters. As explained in Part 2b, What have we here?, there are many different kinds of custom filters. You will use them a lot, because the “out of the box” filters won’t do much. And don’t be afraid of them — just set up a new profile every time you want to try a fancy filter, and apply your filter to that profile only — that way, you can mess it up all you want.
With custom filters, you decide what to name your filter, what kind of filter to use, and what the regular expression will be that will match — just like with Out of the Box filters. But now, you have an additional decision to make: which field you are going to filter. (“Filter field.”) So here’s an example of an include filter that I would use to include just an IP address (this would be very helpful if I wanted to be sure that ONLY my data were included in a profile, then I could see how well the analytics track what I do.) My Filter Field is “Include a visitor IP address” — that’s the additional decision you are required to make with Custom Filters.
In the next post, I will go through many of the filter fields. First, let me point out that you can get this information from the Google Help, it is just not always as helpful as I want it to be. Also, if I went through them all, you will be really bored, so I will just choose a few important ones. Today, we will have just one: Request URI.
Request URI: This is the one you will choose when you want to filter by the page or section of your site that the user requested. It is a relative address; in other words, you don’t have to include the www.mysite.com part of your URI. If your site is www.mysite.com/blog, and you want to exclude people who visited your blog, you would do a custom exclude filter and match to ^/blog. Remember that Regular Expressions are greedy, so they will match to everything that starts with www.mysite.com/blog (and maybe that is what you want.) On the Google page I referenced above, they make it sound like you can only filter by a specific page (This is incorrect, you can filter by a whole section or string in the URI.) Also, they don’t tell you that you should be using RegEx, although I had a hard time coming up with an example where you could really hurt yourself badly here.
More coming soon. Many thanks to Mike Keyes, Avinash Kaushik, Stephane Hamel, Kevin Hillstrom, and of course, the manager of the LunaMetrics Australian office, Steve, for updating their links to this blog.
Robbin
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Posted on April 20, 2007 by Robbin Steif
I am writing a series on filters for GA. This is the first actual implementation post I am doing in the series. This one is called “easy implementation,” because it is just implementation of the three “out of the box” filters I wrote about in Part 2. In Part 2, I only wrote about what they do; here, I write about how to make them work for you.
So first, go to the Filter Manager, found in Analytic Settings. And to make this as easy as falling off a wet rock, here is a picture of it:
Notice how you have to click on the white text which has a charcoal background to create a new filter (the top border), not on the blue underlined Learn More. And the next screen will be similar, you have to click on the white “Add filter,” which is on a charcoal background. Hard to see, easier after you have done it hundreds of times.
Easy Filter #1: Exclude all traffic from a domain. Remember that you are excluding traffic based on the visitor’s domain, and that domain has to be an ISP, before you start this. Here, let me be more clear: you can’t use this filter to exclude all the traffic from Google — it will only exclude the traffic from people who work at Google. Don’t remember this? Well anyway, your screen looks like this:
All you need to do is give the filter a name (and it just needs to be descriptive so that you’ll remember it). Then, use the drop down box to choose “Exclude all traffic from a domain.” Only the final part might be hard — the domain. (In fact, I would love to get email/comments from anyone who actually uses this functionality.) When you screen out a domain, and it is an isp, you are going to exclude a *lot* of traffic. Did you really want to exclude everyone from Verizon? From Microsoft?
Well, let’s say that you do. You can keep your RegEx simple, and merely type in Microsoft. Regular Expressions are greedy though, and will include Microsoft.com and Microsoft.ca and anything else. If that’s what you want, great, and if not, make them specific: microsoft\.com or if you are really compulsive, microsoft\.com$. Need to understand how to use the characters that make up the Regular Expressions, like the backslash and dollar sign?
Easy Filter #2: Exclude all traffic from an IP address. This is a much more selective way of excluding traffic. You’ll do it the same way as above: First you give the filter a name that is meaningful to you, then you choose “Exclude all traffic from an IP address” from the drop-down box, and finally, you create the regular expression that defines your IP address(es). You might just have one, like this: 66.249.72.68, in which case, you’ll write it like this 66\.249\.72\.68 , thereby turning the magic dots into simple everyday dots. Or maybe, you have a range of IP addresses – you can still get them into that one box by using Regular Expressions. So if you own IP addresses 72.77.12.26 through 72.77.12.40, inclusive, you’ll write ^72\.77\.12\.(2[6-9]|3[0-9]|40). If this is complete gobbledygook to you, the way it was to me a year ago, check out this post on Regular Expressions – the same example is used there.
Easy Filter #3: Include only traffic to a subdirectory. So it’s the same drill. First you give the filter a name that means something to you, then you choose “include only traffic to a subdirectory” from the dropdown box, and finally, you create a regular expression that defines the subdirectory. For example, if I only wanted to see traffic to this blog, which is now at http://www.lunametrics.com/blog, I could do it a few ways, but the safest would be like this: ^/blog/
Why? The carat ensures that the directory has to start with the word blog. And because there is a slash after the word blog, the RegEx will stop working at that point — it won’t pick up another random directory calling, for instance, blogging.
And now how do I apply these easy filters? You created extra profiles, right? So use the bottom half of that Filter Manager screen and choose which profile to add the filter to. Alternatively, you can just start with a profile and create a filter for it. (But you still have to find the white text on the charcoal background to Create a Filter.)
Check your filters the next day to see if they are working correctly. If you pull in only the new day’s data, you’ll be sure that you don’t have any unfiltered data. Do they make sense? Compare them to unfiltered data over the same time period – does the difference make sense?
Robbin
Lunametrics
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