4 min.
Why Big Query and Google Analytics Premium will ignite the excitement of data scientists and marketers
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Why Big Query and Google Analytics Premium will ignite the excitement of data scientists and marketers

Analytics & Tracking

Today we’re going to dig deep into the geekiest functionality Google Analytics Premium has to offer: the integration of BigQuery. We’ll explain why this is the functionality with (shockingly?) the most potential for business intelligence, and above all how it can give the voice of your marketing and IT teams exponentially more influence in company decision-making.

For the past few years the big fish in the Analytics world (Adobe and Google – not to name names), have been getting ever more innovative in their offerings. Major players in Big Data, their goal is to respond to the growing needs of the CMOs and CTOs of data driven companies. Google, with its Premium version of Analytics, has already seduced a number of big companies in Canada, including Desjardins, RBC, and even Aldo.

One of the advantages of Google Analytics Premium is its ability to serve up unsampled data. If you want to make sound strategic decisions, they need to be based on reliable, precise, and exhaustive data. Today, more and more companies find themselves managing mountains of data from various sources, and they don’t want to lose an ounce of it. Google Analytics Premium opens the door to accessing an unlimited volume of unsampled data, while integration with BigQuery allows you to query billions of rows of data. In short, this duo will (big time) usher you into the era of Big Data.

But that’s not all. Going forward, this integration will allow Premium users to access their raw data, directly from the server, in order to carry out granular, complex queries. Which means that all your Google Analytics data will be automatically available in BigQuery, just waiting to be exploited!

Here are a few of the many concrete advantages to using Google BigQuery:



How does this concretely benefit you?

Massive computing power

Time saved: information can be accessed in seconds (vs hours).

No initial investment in hardware or software*

*Unlike other Big Data tools

Financial savings.

Management of access control lists

Secure sharing and collaboration for large teams.

Unlimited storage: you pay only for what you use

You set your own storage limit. It’s a personalized consumption model.

Multiple layers of security from Google (thanks to redundant storage in multiple physical locations)

Your data is protected, and above all it belongs to you!



Reminder: What is Google BigQuery?


Google BigQuery is nothing new – the tool has been around since 2010 – but it’s evolved significantly since then. It’s a web service that allows you to query billions of rows of data from multiple sources, with a response time in just seconds. To give an example that illustrates just how fast this tool works, a keyword search of the entire works of Shakespeare returns a result in less than 4 seconds, a feat that was demonstrated during a Google BigQuery presentation in France in 2012. It’s enough to have us watering at the mouth.

What’s more, your data is exportable, and it belongs to you. Data ownership is a feature exclusive to Premium (vs the standard version). It’s an important detail for companies across Canada, but particularly in Quebec, where provincial legislation makes a point of protecting personal data.

The integration of Google BigQuery with Google Analytics Premium allows you to directly access your raw Analytics data. Without Premium, you would need to manually download the data you wanted to look at (the data would be sampled) to then be able to execute your queries. As you can imagine, the process becomes extremely long and arduous when you have to do all that preliminary work before even running your first query. It gets even worse if you need access to a lot of data, since that equates to doing a lot of exports.

With Google Analytics Premium though, all your data is automatically available in BigQuery, so there’s nothing left to do but start running queries!

5 ways to transform data granularity into business intelligence

By this point you’ve probably understood that this tool can be used to create complex and granular queries. The ability to cross-reference data from multiple sources (Analytics, CRM, POS, etc.) opens the door to incredibly powerful queries. Say goodbye to unanswered questions!

In concrete terms, how can Google BigQuery help? It can range from addressing the simple issue of organizing data, to enabling you to glean valuable insights through Big Data analyses.

#1 Analyze data over a long date range

Google Analytics currently allows you to define a very broad date range, however the longer you go, the more sessions you’re dealing with, and the more data sampling you’re therefore dealing with. Imagine doing an analysis of a two year period using only 10% of your sessions. It wouldn’t be terribly representative. With Google Analytics Premium and BigQuery, you have raw, unsampled data at your fingertips. For example, you’ve probably wondered how many purchases on your site were made following a social media visit, and what the potential growth of this revenue source might be? Ask BigQuery. You’ll get your answer.

#2 Organize your data to deliver insights

What’s the best way to keep track of important items, and to be able to flag when something goes missing? Organize your things! The same holds true for your data. If you want to optimize your site by pulling insights or discovering weaknesses that need fixing, organize your data. When I say organize, I essentially mean giving your data more context by cross-referencing it with external data.

  • For content sites, for example, if you have complementary information on each of your articles (author, type, publication date, etc.) in a database, add that information to your Google Analytics data. This will allow you to go deeper in your analyses, and could even help you discover that a particular type of article leads to more conversions than others.

#3 Link your CRM data to your Google Analytics data for better campaign targeting

By joining your CRM data and your Google Analytics data, you can retrieve any useful piece of information and integrate it into your CRM tool to better target your campaigns, and build loyalty with existing customers.

  • For example, every week, for every customer who logged into their account, you could pull the top five products they saw on your site but didn’t buy. Pair this information with your CRM data for each client, and you could launch a campaign that reaches out to each client to remarket products that you know they’re interested in. Crazy, right?

  • Take an online shoe store. By joining your Google Analytics data with your CRM data, you might discover that girls aged 18 to 24 usually buy sandals in the month of May. Add this data to your CRM tool, and launch a campaign that targets the right people at the right time!

All it takes is to think about what you want to know about your customers for your next campaigns, and export the information via BigQuery. Your conversion rate will definitely see an improvement!

#4 Centralize online and offline information to get a global view of the user journey


We all want to know what our customer journey looks like, from the first visit to the website, to the final offline point of sales (brick and mortar store, call centre, etc.) and vice versa. This would let us see every point of contact with the customer, and avoid problems with online/offline attribution, for example. You could finally know for sure who deserves to be pat on the back for your sales!

  • Access information about how your sites and campaigns are performing: what pages did a visitor look at before making their purchase in the store, and what did they end up buying? Were visitors who saw your marketing campaign more inclined to make an in-store purchase, or less?

Let’s take it a little farther. Let’s go back to that online shoe store. Imagine that the information available in Google Analytics is also available for your physical shop: number of visits, number of transactions, shoes bought, etc. Add this information to the data from your online store. Now, not only are you able to optimize the performance of your online boutique, but of your physical store as well, each as a function of the other! The possibilities are infinite. All you’d need to do is track your offline data, something that’s becoming easier and easier to do with connected objects, mobile device functionality, etc.

#5 Go way, way deep into the details of your data

Get ready to make the longest queries of your life! Never hesitate to go deep into the details of your questions. Look at things like:

  • Among website visitors who used a promotional code, how many found your site because of the promotional code, and how many stopped midway through the purchase process only to come back 10 minutes later with a promotional code? In each case, what are the codes that were used?

  • What keyword groups are used in the campaigns that bring the most qualified visitors to the site? Which visitors convert most often, and to what extent does the content they read or product they bought relate to their initial search?

If you’d like to know more about the opportunities related to Analytics Enterprise solutions (GA Premium and Adobe Analytics), give us your email and we’ll share our upcoming webinars, blog posts, case studies,  and more.

Also read: How to use Google Analytics Premium’s BigQuery?

I would like to thank my colleagues Aurélie Bailliache and Marie Nicollet for their contribution to this post.