Tag: configuring google analytics

  • Why you need at least 2 views in Google Analytics

    The first thing any GA implementation should include is two views: a working view and a ‘raw’ unaltered backup view. One day that raw view will save you from a data disaster.

    The ‘raw’ unprocessed view is one in which the data has not been modified in any way when configuring the view settings or by adding filters.

    You should always have such a set of data available so that you can sanity check anything else you do against a pure source. And you will also have a backup in case anything you do in your working views messes up the data.

    Updated: February 2014 Google have changed their terminology. What used to be called ‘profiles’ are now called ‘views’
    Updated: September 2012 Make that 3: why you need a spare GA view
    June 2012 How to use ‘Copy View’ in Google Analytics v5

    How to Set Up a Raw View

    When setting up a raw view you should enable ecommerce and configure search where relevant (but do not strip the search parameters). Doing this will just enable more reporting, no data will be changed.

    You should not configure the view to ignore any parameters and you should not configure the default page. Doing either of those would modify the data.

    Configuration setting for raw Google Analytics profile

    Off the top of my head I cannot think of any filters that you would dare to apply to this view. You don’t want to filter anything out, and you don’t want to use filters to change data.

    So definitely NO excluding of IP addresses, or changing all the URIs to lowercase. This raw view is precisely the one you would want to cross-check against when debugging such filters.

    What to Do if You Only Have One View

    If you only have one view set up for the site at the moment, check whether any filters have been applied, or if the default page or any parameters to ignore have been configured. If none of the above have been done, then this view should become your raw view. It will contain historical data in the raw form, so it makes sense to keep this valuable resource intact and create new working views instead.

    If this is the case, I recommend editing the name of the view to make it clear what it is. It’s probably called something like ‘www.mydomain.com’, which will sort nicely to the bottom of most lists. So I would just add a function and warning to the end: ‘www.mydomain.com (raw data – do NOT change)’

    If you haven’t got a view like this already, you need to set one up as soon as possible. I recommend sticking the date of the next day at the end of the name when configuring this view so that you can see at a glance when the data begins.

    Update, June 2012: You can now use ‘Copy View’ to quickly create a clone of an existing view and then edit the settings.

    Setting up Goals in a Raw View

    Although you should not have any filters applied to your raw view, it’s possible to configure goals. In the days when GA was limited to four goals per view I used to use this view for housekeeping and debugging goals, such as the goal for the 404 page, so as not to us up slots in the main working views.

    I’d recommend having at least that goal configured here. The ‘Reverse Goal Path’ report will then have a full, un-modified set of data to work with when you need it to go looking for internal sources of bad links. But I would also configure such a goal in one of the main working views these days and configure an Intelligence alert for its conversion rate. This is data is something you need to have in front of you, not hidden in a view you seldom visit.

    How the Raw View Can Help You or Save The Day

    For most purpose the raw view is one that sits in the background collecting all the data. It’s not a view most people would want to see.

    You’ll need the raw when configuring filters which do things like include or exclude visits of some kind. By comparing the new filtered figures with the un-filtered version you will be able to sanity check whether the difference is credible or whether you need to re-check your filters.

    You’ll also find the raw view useful if you find a situation in which a parameter you have stripped out by using the ‘ignore parameter’ setting suddenly turns out to have a use. For example, you would normally strip session ids out of a working view. But it’s conceivable that at a later date you might want to be able to find all the sessions which encountered some error page and create a segment in order to track what other aspects those visits have in common.

    Finally, you’ll also be very grateful for the raw view if you ever make a mistake with a filter and discover days later that it has trashed some relevant data. You won’t be able to undo the damage in the working view, but at least you’ll have the raw data to fill in the gaps in an external report…

     

    Updates

     


    September 2012: Why you should also have a spare view in Google Analytics
    Two views is the minimum you should have for each GA web property. But it’s much better to have a third view available for the future.

    I’ve just been reminded of this by an experience with a client who has just moved their ecommerce site to a new platform. They have built up many years of historical data in the existing views. So there is a big benefit in continuing to use the same view in order to preserve the continuity and make easy comparisons possible.

    BUT… the new site has a very different structure and uses different URIs. The existing goals need to be replaced by new equivalents.

    Most of the existing goal slots have been used up in the main working views. We need a new views with a fresh set of 20 slots. But a new view will have no historical data.

    Fortunately the client already has another spare view which has been storing data for several years. It has a limited set of data-hygiene filters in place to create a ‘clean’ set of data so this is not a ‘raw’ view. But all 20 goal slots are empty.

    This approach means that although historical comparisons of things like checkout abandon rates will need to be done externally, most of the key comparisons of ecommerce conversion rates and so on will all be fine.

    Of course, as soon as this view becomes the new working view, we must remember to set up another spare for next time….

    June 2012: How to copy and duplicate views in Google Analytics
    The easiest way to create a new view in GA is to copy an existing view.
    1. Go to the ‘view settings’ tab in the Admin area:

    Screenshot showing the profile settings interface in Google Analytics

    2. There’s a ‘Copy view’ button down at the bottom of the screen, to the right of the ‘Apply’ button:

    Screenshot showing the copy profile interface in Google Analytics

    3. Choose a name for your new view and click the ‘Copy profile’ button:

    Screenshot showing the profile settings interface in Google Analytics

    4. Then click back over to the ‘View Settings’ tab and make your changes.
    In the case of a ‘raw’ view, remove any ‘default page’, ‘Exclude URL Query Parameters’, and uncheck ‘Strip category parameters out of URL’ if you have it configured in the site search section. Also check to make sure that no filters are being applied to the raw profile.

    Screenshot showing the profile settings for a raw profile in Google Analytics

    The view’s goals will also be copied into the new view. This may be exactly what you want. But if you will need to use those goal slots for something else, you will need to try to stop these recording any data. At the moment there does not seem to be any way of deleting the goals. So the only solution I know of at the moment is to set the goal to ‘inactive’:

    Screenshot showing how to stop a goal collecting data in Google Analytics

  • Setting up more profiles in Google Analytics

    Why would you want to set up more than one profile for each website in Google Analytics?

    1. There are things which GA advanced segments cannot do
    2. You should always have two sets of data

    One of the classic uses of profile in the early days of Google Analytics was to look at chunks of traffic. Segmentation. So when Advanced Custom Segment appeared the days of using profiles to look at the behaviour of different types of visitor seemed over.

    Advanced segments have many advantages over profiles for this purpose.

    You can see the different segments alongside each other in the same report in order to make comparisons. This is particularly useful when looking at charts.

    Example of graph showing Google Analytics custom segment in use

    You’ll find this a great way of establishing which type of traffic was responsible for a change which you have noticed in the overall numbers.

    Techniques like this allow you to see things at a glance in an illuminating way. Try setting up a segment for ‘medium contains email’ and then comparing it with the default ‘search’ segment (or, better still, a ‘medium=cpc|ppc|organic and keywords=your brand terms’ one). You may well find that surges in email traffic are also matched by simultaneous rises in navigational search visits. This would suggest that your emails are reminding people to visit the site, via search, even if they’re not clicking on the email itself. Those emails are worth more to you than the basic clicks suggest.

    Custom Advanced Segments are also much better than the old ‘profiles’ approach, because you can think up new ones on the spur of the moment and they will be applied to all your historic data.

    I used to love the old Clicktracks system because it allowed me to do something similar. If I suddenly thought “I wonder if…” and wanted to delve into the data, I could set up a set of rules-based conditions and use them to segment all my data. Except in those days you could go for a coffee, or maybe lunch, while the data was processed. GA does it so fast some people even use the ‘test’ feature in segment configuration to extract a set of numbers and never bother to save the segment.

    But…

    There are some things which GA advanced segments can’t do

    The most limiting of these is that you cannot segment funnel reports. So you cannot use segments to see how different types of visitor behave in your checkout or your other micro-conversion funnels.

    This is a significant loss.

    Common sense says that an existing customer returning because of an email about a very strong offer is going to have a very different reaction to your shopping cart page from someone landing from a generic search and who has never heard of you, let alone already been through your checkout. So how would you set about optimising the shopping cart page for that last group when their data is mixed in with all the others?

    Segmented profiles also mean that you could give different people access to only the data which is relevant to their work. For example only the email traffic, or only the unpaid search traffic. Even if the ‘different people’ is actually just you with a different hat on, it can be useful to have this task-specific view of the data without all the other noise.

    So, although Advanced Segments are one of the greatest features in Google Analytics, I think every site should still set up a series of profiles, rather than just rely on the basic two.

    Two?

    Why you need at least two Google Analytics profiles

    Yes, two. You should always have one set of raw, unmodified data being captured alongside your main working profile so that you have something to cross-check against. Or fall back to.

    But I’ll go into more detail about what you should and shouldn’t do with your raw profile next time in a post explaining how to set up a raw profile in Google Analytics.