Are you happy you’ve met the traffic goals at the end of the month? Hold on, the data displayed on your Analytics dashboard also includes the internal traffic (visits from staff/internal office network) on your web site. You may have hired some web developers living on the other side of the globe working on your web site. What about their visits while they work on your site? Their visits are also counted in your traffic. So, are you getting the true picture of actual number of genuine visitors coming to your site?

Here comes the role of filters that can be used to exclude visits from specific sources on your web site. Power users are able to harness the true power of filters with the help of custom regular expressions. In our case, we will see how to exclude visits from selective sources so that they do not count in our traffic statistics.

Excluding visits from a network

Let’s assume your company has two offices in different locations. One network has the IP range of 3.67.232.1 to 3.67.232.189 and the other has the IP range of 10.17.115.1 to 10.17.115.137. Now you want to exclude all visits from these two networks to get a better estimate about the actual number of visitors coming to your web site.

To achieve this, simply create a filter as shown below. I’m assuming you are currently in your Analytics dashboard.

1. Go to Analytics Settings -> Filter Manager -> Add Filter.
2. Give an appropriate name to the filter (for exp: ABC Inc Internal Traffic).
3. Select ‘Exclude all traffic from an IP address’ from the drop down list of Filter type option.
4. Now for first IP range our regular expression will be:

^3\.67\.232\.([1-9][1-9][0-9]1([0-8][0-9]))$

For second IP range, the regular expression will be:

^10\.17\.115\.([1-9][1-9][0-9]1([0-2][0-9]3[0-7]))$

For specifying more than one range, we have to separate both expressions with a ” pipe symbol. So the final expression becomes:

^3\.67\.232\.([1-9][1-9][0-9]1([0-8][0-9]))$^10\.17\.115\.([1-9][1-9][0-9]1([0-2][0-9]3[0-7]))$

Write this regular expression in the IP address field. If you find it difficult to create these expressions for your IP range, here is a handy tool to create regular expressions for a given IP range.

Note: In Google Analytics, the maximum allowable length of a regular expression is 255 characters. If your company has large number of networks, you have may have to create several filters to accommodate all IP ranges.

5. Next, you have to select the web site profiles on which this filter should be applied. Select the sites from the left side table and click Add >>. Click Save Changes to complete the filter creation process.

Now all visits from these networks will not be counted in your traffic and you will be able to get a better and clearer picture about the actual performance of your web site.

Excluding visit from a single IP

To reduce the complexity, I’m not discussing about excluding traffic from dynamic IP addresses. The process of excluding traffic from a single IP is same as shown above. All the steps are the same except the regular expression. Suppose, you want to exclude all traffic from IP address 10.31.119.45.

The regular expression for this IP will be 10\.31\.119\.45

Regular Expression Primer

The table shown below will help you in experimenting and creating your own regular expressions.

? -match zero or one of the previous item
. (dot) -match any single character
() -remember contents of parenthesis as item
- -create a range in a list
* -match zero or more of the previous item
-or
^ -match to the beginning of the field
$ -match to the end of the field
[] -match one item in this list
+ -match one or more of the previous item
\ -escape any of the above

If you are hungry for more, here is an excellent tutorial to learn regular expressions for Google Analytics. So what are you waiting for? Go ahead and use this extremely powerful feature of Google Analytics.

How To Use Filters In Google Analytics To Remove Your Own Data is a post from: The Direct Approach Blog owner: Rebecca Atkinson (Muller)

You can read more detail in some of the posts that have since spawned here and here.

What’s most interesting about this is how the big guys must be shaking in their boots. Let’s not forget, Google is still free. With these enhancements – especially the advanced segmentation features (I’m drooling), suddenly Google has just entered the major leagues.

Analytics tools like Omniture and Web Trends have been charging tidy sums of money for these kinds of services for years and now they are free.

Let’s not forget that the ability to custom reports, more complex data extraction (API) and fun “dancing” bubble charts have always been the claim to fame for some of these companies. It’s been their unique and differentiating factor from Google. They could give us something Google couldn’t. And implementing these things were so complex that they required huge internal tech team coordination and support staff/client care reps whose job it was to keep you so confused that you didn’t think you could live without paying for their services.

Now don’t get me wrong, I’m not saying the pay-for analytics models don’t have a place or that they aren’t any good. In fact, many of these tools still have their own unique factors and still offer much more robust services than Google does – which for the biggest of biggest clients – is definitely required.

But these companies will need to get better at explaining why it costs so much for their services and why you need them vs. the freebie.

For companies – it will become increasingly important to create vendor RFPs designed to understand and evaluate which service or company can best deliver on your analytics objectives and needs.

Looks like times are changing – and with the current economic crisis, I’m inclined to think a lot of the small-mid sized companies are going to be looking long and hard at which analytics system best fits their needs.

Google Analytics – Not Just a Toy Any More is a post from: The Direct Approach Blog owner: Rebecca Atkinson (Muller)