Saturday, 6 December 2008

Don't get lost in Google Analytics - here's the map

It should be pretty obvious that we think Google Analytics is neat. Neat as in essential to your business! It qualifies as one of those technologies that is clever, cool and seriously useful. The inherent risk using clever, cool and useful tech is that one can get awfully lost in the clever and cool without gaining any value.

For example, I have been guilty of spending many an interesting hour building and rebuilding custom reports - a great new feature in the GA beta interface. I had to catch myself though - were these reports relevant? Were they useful? Were they aligned with our clients' Key Performance Indicators?

I undertook an exercise to rationalise the custom segments and custom reports we had available to our GA account.

The general profiles and filters that we set up in the last blog post are exactly that - general. Sufficiently generic so as to be useful to 90% of GA users...probably. Anyway - custom reports and custom segments should be developed so as to be aligned with business Key Performance Indicators.

Think about it: Why would a board member be so interested in the bounce rate on the website broken down by OS, browser type and browser version? Would a developer really be 'bovvered' by relative marketing campaign keyword performance? Probably not. So, as we created profiles to capture filtered data, we can also create profiles to present data.

Let's say we created a developer specific profile - this doesn't mean to say other users can't view the data but it is a profile focused on the preserntation of data that a developer would want to see. Any report - even a custom report can be added to the dashboard for the profile that you are currently viewing:



And here is the report added at the bottom of the dashboard:



Remove the 'clutter' from the report for the given profile by hitting the X in the top right of each report overview in the dash board.

Now you can have a dashboard for each business function tuned to specific needs, custom segments and reports that are relevant and useful!

Monday, 17 November 2008

Google Analytics baseline setup

This is going to be a longer post where I'll explain what Moneyspyder does to clients to help them attain what we consider to be the bare minimum Google Analytics setup.

GA (Google Analytics) is really easy to get up and running but it's not so obvious what should be done to start getting the best out of it (see a previous post on why quality data is essential).

Default profile
Having initially setup GA you are the proud owner of one single, unfiltered, raw profile. This profile will capture all the data sent to it by your website traffic.



Notice the two links highlighted above - these two little chaps are going to help a lot: Profiles and Filters.

First of all, let's get our raw profile sorted out:


  • e-commerce tracking

  • search tracking

  • filter internal traffic

  • lower case data



Standard Profile Edits

First of all, click 'edit' next to your standard profile :



Then click 'edit' again in the top right:



Now, if you site is a transactional site you'll want to track the e-commerce data generated by your site so click the 'Yes, an e-commerce Site' radio button.

Likewise, if your site has internal search you'll want to track it so click on the 'Do Track Site Search' radio button:



Having clicked the relevant controls, be sure to tell Google what currency you're using and what search parameters to look out for. Say your site uses a parameter 'q' on the url for searches:

http://www.yoursite.com?q=widgets

Then type 'q' in the Query Parameter box.



Now 'Save Changes'.

Standard Filters

Now head back to the Analytics Settings page for your site. Click on 'Filter Manager' (bottom right), and then click 'Add Filter' (top right):



Here is a filter to turn all data into lower case:



Notice that the filter name is totally up to you. Choose custom filter, lowercase, Request URI and add your single profile to the 'Selected Website Profiles' list. Now 'Save Changes' and all your data will be lower case. This is results in nice consistent case in your data - shouldn't be necessary but say users search for 'Widgets' and 'widgets' - you'll see the data for the two search terms as one which is more useful.

Now, one more standard filter:



This filter will exclude your internal traffic from your data. Obviously you'll need to change the regular expression to match your IP address range. You can exclude multiple ranges or single addresses - if you can build the reg exp (perhaps using Rubular which is a neat tool) you can filter the addresses out.

Caveat

We normally apply these two standard filters to all profiles but when you start building more advanced custom filters you will need to think carefully as to whether you want to apply these filters to your standard profile or another specific profile. Filtered data can never be retrieved. Once it's filtered, it's gone. If you apply a filter by mistake, you can create holes in your data. This is to be avoided so be careful!

Now, time for some

Advanced filters and extra profiles

We suggest starting with 4 extra profiles covering the basic customer segments:

  • New

  • Returning

  • Organic

  • Paid



As you will see, the filters that can be applied can get quite 'fruity'. Depending on your Key Performance Indicators you may choose to add or remove filters that are better aligned with your website strategy so as to measure your tactical goals more accurately.

Let's setup the profiles first of all:

Click 'Add Website Profile' in the bottom left of the Analytics Settings page for your site in GA.



Choosing to add a new profile for an existing domain will create another profile that will receive data from your website. No new GA tracking codes or scripts are required. Slightly off topic though: Make sure your test, staging and production sites all have separate Ga accounts - keep the data clean!

Give it an appropriate name of course...

Now repeat for the other profiles and you'll end up here:



Don't be concerned by the this will change in a few hours. New profiles, even though they may be using an existing URL, are new profiles. they do not have data, they are not copies of existing profiles.

Remember the standard filters and profile tweaks. Do them to these new profiles. Make them all track search if your main unfiltered profile tracks search and likewise for e-commerce.

Now we need to filter the data going in to these profiles. We shall set up the New Visitors filter first and apply it to the New Visitors Profile.

Go into 'Filter Manager' and create a new filter:



You'll notice some similarity with the 'Lowercase' filter. It's a custom filter again. This time we 'include' traffic based on 'Visitor Type' being 'new'. We apply this filter to the New Visitors profile ONLY!!!!

Now let's do the same for returning visitors:



Cool! Now we have an unfiltered profile albeit with slightly filtered (for cleaning purposes) data, and two corresponding profiles containing data pertaining only to New Visitors and Returning Visitors. Already we have better visibility of our two main customer types and what they are doing on our site.

Now the home stretch (for now) where we can create another two customer filters to capture two more really useful segments - organic traffic and paid traffic:





take a moment to browse through the filter fields available - awesome huh? You're probably thinking already how you could use some of these fields for future profiles and filters. I am!

Now you should end up with a list of filters like this:



take a moment to double check your profiles to make sure you have the right filters on the right profiles - always worth performing a gross error check at this point cos now you have to wait for the data to come flying in!

Couple these basic segments (filtered profiles) with the new GA custom segments and reports and you start to see how powerful clean data can be.

Friday, 31 October 2008

Downtime is bad, right?

Not always no. This week we did a pretty large update to www.beautifulpure.com involving some lengthy database work. Whilst this is happening, of course transactions cannot happen on the site.

So, we do this work in the dead of night and plan the downtime. With appropriate planning, testing the deployment as well as testing the new functionality and faultless procedural execution of the deployment we still met our 99.9% uptime SLA.

Overall for this year we are running at 99.91% which roughly equates to 6.5 hours of downtime accross all clients for the whole year so far.

The next part of this analyis will take into account planned vs unplanned downtime and of the unplanned downtime - what time of day did it occur?

Watch this space.

Monday, 27 October 2008

Stop Press!

Catalogue|e-business magazine reported today that Snow Valley has partnered with Site Confidence to provide monitoring for their client's sites.

Woo hoo...

Moneyspyder have done this for over two years. For Free. Coupled with Pingdom for a back up. Engineyard run their own in house server monitoring in addition. For Free.

Using these services mean that Moneyspyder can honestly claim to have 99.9% uptime or better for all sites for as long as we have been running.

Saturday, 4 October 2008

Why Formula 1 is boring and what we can gain from it.

You may have seen the recent Grand Prix on television....You did? And you fell asleep? Thought so. Dull huh? But what does it have to do with Moneyspyder and why?

There are so many reasons but there is one main reason we can learn from and make use of: the precision with which the teams race now pretty much ensures they know what the result will be bar any accidents or freak weather. With 20 or so cars flying around a track at over 200mph how can they be so certain of the outcome? These are pretty complex pieces of machinery after all! Be great if we could be so certain about the outcome of our businesses, huh?

thing is, the science of Formula 1 has been applied to the measurement of key performance indicators on racing cars enabling the teams to know to the nearest 10th of a second how well the car is performing against expectations set by a mathematical model of what should be possible.

Sounding familiar yet? Think about an internet retail site; What sort of bounce rate, conversion rate, daily unique visitors, email open rate, basket abandonment rate, etc. etc. is expected? How does current site performance measure against the expectation? How are these expectations set? In a similar way to Formula one cars funnily enough.

By now, you should be saying 'yeah yeah, I have Google Analytics. So what?'. If you aren't saying this please call Moneyspyder now! So you dohave Google Analytics (GA)? Are you able to measure your site performance to an adequate level of precision? Are you confident in the accuracy of your data?

Recently we've seen a fair amount of GA data with a broad spectrum of precision and quality of data. To get any value from GA it is fundamentally important to get clean and precise data on which to base our expectations and indeed any subsequent measurement.

For example, customers arriving on your (all important) landing pages from marketing emails will probably arrive with a url payload:

http://yoursite.com/email=abc123

Now, each email is likely to have a different value associated with it. How is this going to manifest itself in your GA reports? Your landing page usage measurement will be totally useless if you measure each unique request based on unique url's.

http://yoursite.com/email=abc123
http://yoursite.com/email=abc124
http://yoursite.com/email=abc125
http://yoursite.com/email=abc126

Nightmare!

'Course, You don't have to be on the Moneyspyder platform to get quality GA data...but it helps! The quality of your analytics data will define the quality of you analysis and how much trust you can place in it. Treat you online business to a bit of Formula one style accuracy - give us a call.