Google Analytics Governance

How to Apply Data Governance

Part of tall order of data governance Google analytics or any other enterprise analytics platform you may have it is imperative you have a plan for analytics and tagging. For Web analytics and data governance to be successful, it should be an ongoing and cadenced activity. Here are key steps to get your data governance program off the ground and mature.

Develop a Steering Committee

One of the first steps of adopting a governance program is to develop an analytics steering committee. The committee will oversee the usage of analytics data and ensure it is aligned to business goals and strategy. As such it requires that stakeholders with strong influence and decision making power from various business areas are involved. Data governance success follows when you have influential stakeholders providing company-wide support.

Define Roles

While a steering committee oversees the high level vision for data governance and is responsible for decision making, you will need operational level support to manage the day-to-day tasks. Below are examples of the support roles:

Assign a Digital Analytics Owner – This person works closely with the steering committee, overseeing all aspects of your digital analytics platform. He/She shall serve as the resident expert and owner of the platform within your organization.

Duties/Responsibilities:

• Oversee analytics platform and supporting 3rd party tools
• Support stakeholder throughout the organization (e.g. gather requirements, training)
• Review and process analytics requests (e.g. gather requirements, training)
• Engage with technical resources as needed
• Perform regularly scheduled audits of analytics implementation
• Oversee and maintain Center of Excellence
• Support the digital analytics governance process
• Support and facilitate the work of the Digital Analytics Champions

Digital Analytics Champions – Beyond having a centralized owner of your digital analytics platform, additional support can come in the form of internal champions. These are experts within a department that serve as internal evangelists and support their team’s usage of digital analytics. They have advanced knowledge of digital analytics and the platform being used.

Duties/Responsibilities:

• Serve as department representative to the Digital Analytics Owner
• Support department business users
• Assist with configuration changes to the digital analytics and the platform to support business requests
• Respond to questions and request about digital analytics from users across the business
• Provide support to Digital Analytics Owner for incoming requests
• Regularly meet and collaborate with technical resources as needed
• Understand and support the analytics governance framework

Define Data Governance Goals

Defining the goals of your data governance program is essential to success. This ensures a clear purpose, demonstrates business value, and aligns executive stakeholders with all users throughout the organization. Further, it establishes specific measurement (KPIs) that make it easier to execute and manage data governance activities to objectively show consistent and meaningful progress on a quarterly basis that support organizational goals/objectives.

Some example data governance goals are:

• Maintain accuracy of digital analytics data over time
• Ensure our end users have access to relevant data
• Maintain alignment of insights with business needs

Ultimately, it is up to you to define what the focus will be knowing that it may evolve over time based on your short- and long-term goals.

Processes

Often, end users will ask, “How do I….?”

Building out well defined processes and making them visible throughout the organization will ensure these types of questions can be addressed quickly.

Common questions that documented processes can help address are:

• How do I get access to our digital analytics platform?
• How do I request new tracking for specific data that I am interested in?
• How do I request a report?
• How do I understand what digital analytics data is currently being collected?
• How can I get more involved in our analytics program?
• How do I surface an issue with our tracking / data?

In addition to educating your users, well defined and documented processes ensure consistency and will help protect against changes that may adversely impact your data. Since data quality is essential to building trust in the data you are collecting, establishing manual and automated processes around data validation and auditing are key.   

Example Processes

Requesting access to a GA account

1. Request submitted to analytics owner outlining what accounts to grant access to
2. Analytics owner reviews request
3. Analytics owner assigns permissions to Google Analytics requestor
4. Email to requestor

Request new tracking

1. Request submitted to analytics owner with requirements of what should be tracked and how
2. Analytics owner reviews request and follows up with requester if clarification is needed
3. Analytics owner documents specifications and resulting data output
4. Analytics owner works with technical resource to implement tracking
5. New tracking is validated by Analytics Owner or QA team on staging environment
6. Technical resource pushes new tracking code to live site
7. Tracking is validated by Analytics Owner or QA team on live environment
8. Analytics Owner or BI Resource works with requestor to develop reporting

Center of Excellence

Building out a web-based Center of Excellence (CoE) for Digital Analytics is essential to establish alignment, build the internal analytics community, and ensure accessibility of documented policies, best practices, training, processes, tools, and other resources.

We have had great success using Confluence, a web-based wiki, to create structured documentation that is easily accessible. No matter which platform you choose to house your documentation it will need to be easy to navigate, have a clear hierarchy, and be readily available to your end users.

Increasing Adoption

Once your digital analytics platform has been implemented training will educate your end users on what data is being collected and how, as well as reinforce established reporting, analysis, and other process guidelines. Ongoing analytics training will serve to develop and consistently mature the skills of your users at a realistic pace.

Your analytics owner could provide monthly training as well as open office hours where end users can ask specific questions. This will allow for close collaboration and knowledge sharing. Department specific training will also help to address the needs of different groups.

Questions? Let’s talk