I recently came back from the annual Google Marketing Platform Partner Summit. I think this is my 10th or 11th year attending and I still look forward to these events as I did my first one. You get to mingle with some of the smartest minds in the analytics and media space and connect with industry superstars, all while attempting to absorb all the product announcements that Google throws at you. While some of these announcements such as the Google Analytics 360 – Salesforce integration, merit their own blog posts, I decided to step back and reflect on state of the industry given the fast pace of change we’re experiencing.
Now, around four months into the launch, and having an opportunity to speak to CMOs, CTOs, Data Scientists and Digital Analytics execs, we’ve had time to think about how to get the most out of the platform. And we aren’t simply talking about configuration and reporting.
We’ve also reflected on the clients we have worked with over the years who have demonstrated success in maximizing the value that they get from data over the long term. These are organizations that we think are truly “data-driven.”
There are certain common approaches that lead to return on investment and added value. In this post, I’ll share my thoughts on two approaches to get the most out of your implementation of the Google Marketing Platform.
1. Think of analytics as a product
Organizations that view analytics as a product – not just a standalone project – get more long-term value from data.
What does it mean to view analytics as a product? Products have a life cycle and a roadmap. They evolve iteratively over time. The success of a product is tied directly to the value customers believe they are receiving when using it. Such long-term thinking puts organizations on a very different path than those that think of analytics as an “IT project” or a “marketing project” or as a “check the box” function.
Agilent is one such company that embodies the analytics-as-a-product approach. Starting out with a vision to develop a self-service analytics practice supported by the Google Marketing Platform, Agilent planned and executed an “analytics as product” strategy with clear goals of service to be delivered to its internal customer base. Committed to building out over a multi-year period, Agilent steadily developed data integrations, functionality, visualization, and training programs, ultimately leading to 400% growth in the use of data-driven insights.
2. Apply “old school” data governance rigor to digital data
I’ve been in the data and analytics world for nearly 20 years… (not bragging about this :), but just want to provide some context).
Digital data, of all of the data sets that are used by organizations, is probably the least standardized and hardest to validate. Not to mention that digital data presents some of the biggest challenges in collection and formation of a complete and reliable data set. At the same time, there is generally less rigor in data governance, security, access, definition and understanding the intended purpose of the data.
Many of these challenges can be controlled through Google Tag Manager (or if you happen to be a fan of of our friends at Tealium, the concepts in this post apply to Tealium iQ as well). If you think about it, Google Tag Manager can be used as a sort of “data governance center” of the Google Marketing Platform.
I find that many data executives don’t fully realize how to leverage features of a tag management system to solve a host of risks associated with inconsistent data collection, lack of data definition and loosely controlled access to tag deployment. This is especially true in enterprise organizations with multiple teams, business units and developers who need to collect data frequently and in tight-deadline scenarios. And GTM has evolved so quickly and extensively since its introduction in 2012 that it’s really no surprise executives don’t understand this.
The point is, there are a number of levers you can pull, buttons you can push, and directions you can take when you configure GTM to define, control, govern, collect and manage digital data. In other words, GTM already possesses the features and tools needed to support important aspects of data governance.
To get a sense of what I’m talking about, I suggest you take a look at some of the coverage our senior consultant Eric Fettman has given to Google Tag Manager. Eric has taken a deep dive into Google Tag Manager since it was introduced. I really like the article he wrote about the workflow and security features. It’s a good primer on some of the features that can help you deploy the data governance policies you will need to put in place as you develop your data integration and compliance initiatives over the coming year.
Similar to the analytics-as-a-product approach I discussed earlier, we recommend scaling GTM with the same considerations in mind – taking a strategic, long-term approach to building out and rolling out functionality.
In this post, I wanted to reinforce the importance of these two foundational concepts that will set you up for success as you build out your marketing and analytics technology stack with Google Marketing Platform: thinking of analytics as a product, and creating solid data governance practices. In my next posts, I’d like to share how these principles improve your media-mix planning and investment strategy with Display and Video 360. If you’d like to talk to me about maximizing value from Google Marketing Platform, before I write my next post 🙂 drop me an email at firstname.lastname@example.org or find me on Twitter at @ferasa.