As web analysts we live and die by segmentation. Without the ability to segment traffic we can not isolate which segments are producing and which need improvement.

Google Analytics offers many different ways to segment data. Each has pros and cons but there is always a way to get the data you need…. well, almost always.

There are 6 different ways to segment data in Google Analytics:

1. Using certain reports
2. Dimension drop down
3. Report filters
4. Advanced segmentation
5. Custom reports
6. Profile filters

Bet you didn’t think there were SIX ways to segment data. 🙂

Using Certain Reports

Ok, you may think this form of segmentation is lame, but it’s not!

Many reports in Google Analytics are segmented by some default piece of information. There’s nothing for you to do.

For example, the Browsers report segments your data based on the different web browsers that visitors use to access your site. Google Analytics automatically identifies this information when collecting visitor data.

Other segments that are automatically include in Google Analytics include:

* Visitor type (new and returning)
* Geographic information
* Operating system (and many other “nerd” segments)

Marketing segments are not AUTOMATICALLY segmented. You need to configure Google Analytics to track campaigns (i.e. link tagging) in order to get correct traffic source segmentation.

Pros:
* Easy

Cons:
* You better make sure you’ve got your campaigns tagged correctly 😉

Dimension Drop Down

Many reports have a dimension drop down that allows for segmentation right in the report. This is a handy way to quickly drill down into a piece of data.

For example, let’s say I want to see the most popular landing pages in a particular state. I can navigate to the state in the Visitors > Map Overlay > Regions report, click on the state I’m interested in, and then choose Landing Page from the Dimension drop down.

You can see in the image above that you can segment based on campaign information, some technical information and some visitor information (visitor type, language).

Overall, this is a good way to go when you’re drilling down and want to segment a single data point by some dimension.

Pros:
* Quick for one-off segmentation

Cons:
* Can trigger sampling
* Limited number of dimensions and no metrics
* A pain if you need to segment a lot of things, like top landing pages for every US state

Report Filters

Bet you don’t think of filtering as segmenting, but it is!

Any report displaying tabular data has a filter tool at the bottom of the data. This let’s you quickly view data that matches, or does not match, some condition. The condition is the pattern, or regular expression, that you enter into the filter. Using a regular expression you can add lists to the filter.

Here’s an example. Suppose I want to quickly view traffic coming from the Pacific sales region. I can apply the following filter to the Visitors > Map Overlay > Regions report:

California|Oregon|Washington

[The above is a regular expression matching California OR Oregon OR Washington]

Notice that the Scorecard (the top row of data in the table) indicates how our segment, i.e. the data that matches our filter, compares to the overall site? We can now compare the Pacific sales region to the entire site.

And here’s a neat trick, if you add the filtered report to your dashboard the filter will persist in your dashboard widget. I call it a sticky filter.

Pros:
* Quick and relatively easy
* Can be applied to historical data
* Will not trigger sampling

Cons:
* Restricted to one report and the data in that report
* You should know some basic regular expressions
* Can not be shared easily

Advanced Segments

There has been a lot of conversation over the last few months about Advanced segments and rightly so. This analysis tool is really powerful and let’s you slice the data many different ways using different dimensions and metrics. Want to see all visits that generated more than $100, coming from paid search and occurring after 8 AM? No problem with an advanced segment.

But there are some downsides. First, sampling. Because Advanced segments re-process data in real time there is a sampling algorithm applied to minimize the load on Google’s servers.

You can’t segment more than 200k visits. If sampling is applied you’ll see a confidence interval next to your data.

Again, the problem is that small segments of data will be really inaccurate when the sampling algorithm is applied. There is no way to disable sampling.

The most common ways to get around sampling are segmenting using profile filters or potentially a report filter. It really depends on the exact situation.

The second issue is that not all reports can be segmented. Due to the segmentation technology certain reports can not be segmented, like the Absolute Unique Visitors report and the Funnel visualization report. Those reports can only be segmented with profile filter (see below).

Pros:
* Can be applied to historical data
* LOTS of flexibility, can segment based on a huge number of dimensions and metrics using different combination of both

Cons:
* Sampling will be applied if trying to segment more than 200,000 visits
* Not all reports can be segmented
* Specific to your username, can not be shared with other users

Custom Reports

Another beta feature that can be used for segmentation is the Custom Reporting tool. This tool is more than just pretty reports. It allows you to create 5 levels of segmentation in a report.

In a previous post I talked about segmenting campaigns by time of day to better understand day parting.

We could take that example one step further by adding geographic region to the report. The result would be a report that has Campaigns data that could be segmented by time of day and then by geographic location.

The problem is that not all dimensions can be used together. The reason is that only certain metrics are related in the Google Analytics data architecture. You can find a complete list of combinations in the GA support docs.

Pros:
* 5 levels of segmentation
* Advanced segments can be applied to a custom report
* Can be shared using automated email feature

Cons:
* Can only segment using dimensions, not metrics
* Limited number of dimension combinations
* Can only drill into one data point at a time

Filtered Profiles

Filtered profiles are the nuclear bomb of segmentation. They are permanent, segment every report in a profile, and can easily be shared.

In case you’re not familiar with filtered profiles, you can include and exclude data from a profile using a filter. Google applies the filter during data processing, thus segmenting the data.

Once the data has been processed it can never be changed. This means that you can filter historical data AND if you mess up the configuration of a filter you could have really crappy data.

Another issue with filtered profiles is not all data can be filtered. For example, transactional data is different than pageview data. This can cause some funky information in campaign reports and commerce reports.

If you need to filer pageview data then you’ll need to filter your commerce data with different include or exclude filters. Also note that Event data can not be filtered.

But, on the up side, you can use filters to segment things like Absolute Unique Visitors and the Funnel Visualization report. Neither can be done with an Advanced Segment.

Pros:
* Segmentation of every report in Google Analytics
* Can control access by assigning users to filtered profiles

Cons:
* Only effective from date of implementation forward
* Limited number of dimensions
* Issues with filtering other types of data, like events and transactions

I hope this inspired you to come implement different segments using different techniques. As I said in the beginning, there are a lot of ways to slice data in Google Analytics. Find the technique to suit your needs and start segmenting!