Combining Google Analytics data with external sources – the next level of analytics

James Standen Analytics Canvas Tool, Google Analytics API Leave a Comment

combining Google Analytics with other data sourcesGoogle Analytics data is incredibly valuable stuff.

But there is a way to make it radically more useful. Combine it with other data, from outside Google Analytics.

If you are not doing this now, then using data that is external to Google analytics will bring your “Analytics Game” to the next level. If you are doing it, push it further.

Example 1: Understanding web traffic in terms of Product attributes

Say you have different areas of your website that relate to different products. Those products have attributes that are stored in your marketing systems. If you can link pages to products, and products to attributes, you can now understand trends in online traffic and behavior in terms of higher level marketing concepts- which lets your analysts quickly explore new possibilities and hypothesis.

You do this by maintaining a page to product cross reference table in an external database or spreadsheet.

In a more sophisticated scenario, you can cross reference each page to a given member of a product hierarchy, so that pages that are overviews, or dealing with an entire product group, are accurately mapped.

Example 2: Enriching analysis by building dimensions on geography

Another example is the geography dimension. While location information by its nature is not pinpoint accurate in Google analytics, it often can be very useful- but particularly if it is connected to other data sets.

A brick and mortar retailer might, for example, want to analyze web traffic behavour based on the likely rough distance from a store, or based on the concentration of stores in a given region. Again, a reference table is built, perhaps with store density by state in the US, for example. It is now possible to see how website visitors behave based not on location, but on retail store density.

How to do it

While you can store a small amount of data in Google Analytics itself, to do any serious analysis, you need to get the data out, and into another system.

Spreadsheets, spreadsheets, spreadsheets!

In some cases, a simple export from Google analytics into excel might work. Once in excel you might need to either do some manual cut and paste, or delve into some VLOOKUP action. Anyone who has tried to do anything sophisticated knows the pitfalls- and when you want to update the data, you have to mess with it all again.

There is also an issue with data volumes with this approach- while some addins will let you pull up to 10,000 rows, very large spreadsheets can get cumbersome.

Databases, databases databases!

A more powerful possibility is to load your Google analytics data into a database, either by exporting and then loading, or by developing using the Google GData API.

Usually, this means you’ve got some pretty serious database and programming skills, or you’ve got the cash to hire someone who does.

A new, faster, cheaper, easier way.

We’re working on a new way. The Analytics Canvas tool aims to bring this capability to the desktop in an easy to use, powerful tool.

By enabling easy querying of data from Google analytics using the API as well as files, spreadsheets and databases, and then providing a visual data transformation environment to combine it, Analytics canvas is going to change the way people get at Google analytics data.

Lots of Analytics data.

It will be available in a range of editions, with different capabilities, making it affordable no matter what the complexity of your needs. The higher end editions will be capable of pulling hundreds of thousands of rows of data from multiple accounts and profiles, as well as data from multiple databases and files.

The cutting edge of data extraction and transformation for Google Analytics is about to move. Apply for the private beta of Analytics Canvas by registering, be the first on your block to try it out- and the most active beta testers will be scoring a free license.

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