The Essential Guide to Data Governance

Essential Guide to Marketing Data Governance


What is Marketing Data Governance?

Data Governance is the collective practice of gathering user details through a set of people’s roles, company processes and data standards for the enablement of an organisation to achieve its goals. In many organisations, the responsibility of data management and use has fallen between the IT department, the operations department and the marketing team. In this essential guide to Data Governance, we look at the multitude of areas you need to consider when creating a data governance strategy for your enterprise. Through various routes of collecting data, companies can find out a range of attributes to a customer, such as name, email, company name...the list of data can go on and on. But how you store, handle and share this information is increasingly managed through complex data laws on national and global levels. Customer data, lead data and buyer behaviour data are all key to growing your business. By obtaining and keeping data, organisations can build a persona for their key markets and understand their customer targets. Ultimately, utilising data in the most consistent manner should be integral to your business planning as this data holds the key to the success of your business. The efficiency across data management allows businesses to act on the data in order to grow and understand market behaviour.

Why is Marketing Data Governance important?

A crucial aspect of every business, data governance is more than important. It’s at the core of every successful business decision and infiltrates each area of the business strategy. Data Governance is required to ensure that an organization's information assets are securely, legally, functionally and efficiently managed throughout the enterprise to secure its trust and accountability. It drives the legal and ethical standards of the business and represents to its shareholders the strict guidelines to which the business adheres to both to its customers and the wider community. Before reading on you may want to understand how form inconsistencies contribute to data hygiene problems.

Data Governance

What are the Benefits of Data Governance?

The range of benefits of data governance include the following: clear and guided support for decision-making; protection from legal issues including data breaches, data storage and data security; understanding of roles and expectations within the business; helps to guide the sources of data; and helps to manage global sources of data.

1. Clear and Guided Support for Decision-Making
A strong foundation in data governance gives way to data-driven, sound decisions. These can be the core in presentations to stakeholders and investors about taking a business forward to succeed.

2. Protection from legal issues
Think about the multitude of legal issues that can arise, especially at enterprise level. These include data breaches, the way in which data is stored and data security. Identifying these risks and addressing legal compliance in a governance strategy supports the structure of the business.

3. Understanding of roles and expectations
Data governance can reach all areas of human resources – from the way internal data is kept to the roles and responsibilities of those managing the data itself. Identifying who in your organisation will have access and responsibility for managing data helps to outline specific roles and the legal expectations within those roles. Signing non-disclosure agreements around data adds an extra layer of security for anyone able to access that data. Who inspects, cleans, understands and ultimately transforms data hierarchy will be acting in a key role as data manager.

4. Helps guide the sources of data
Data collection can include important information about potential customers, current customers, employees and potential employees. By clearly defining the sources of data deemed acceptable (both by your board and by law), enterprises are able to ensure easy, accessible data that guides business decision making.

5. Aims to manage global sources of data
Operating models based on region could potentially affect the way data is stored and managed. Something as simple as postcode placement within an address can cause issues. Identifying these early on and understanding local markets and local needs gives precedence to any arising issues from global sources of data.

4 Steps to Building and Testing your Marketing Data Governance Strategy


Identify the origins of your data. Multiple applications of data often occur across large global companies. Identify key sources of data collection and work to standardise this across your business. By standardizing the data you are collecting, you are limiting inaccuracies that prevent it from being used across your organization across teams and on a global level.


Define the data collection points and analyze the best storage options for your data. Efficient data storage is often cloud-based allowing accessibility across your company, no matter what the department. It also allows security to be maintained at a high level, granting access at multiple security levels.


Data functionality must work within the ever-changing data laws that happen on a state, national and global level. Constant review of data laws will increase quality assurance and usage across a multitude of tasks and projects. Enterprise-wide data management drives compliance, ensuring data quality throughout the entire data structure.


The strategy itself is often less important that the implementation. Working across multiple IT and marketing teams, often in multi-language forms, means that data collection can very quickly become obsolete. Standardize reviews as part of the initial strategy, establish how it can be scaled and trialed across regions to identify issues early on.

What Makes a Good Data Governance Strategy?

Because Data Governance provides the solid, overarching strategy for how your organisation obtains, stores and maintains data, it’s important that the strategy itself is sound. This means you’ve tested against issues that may arise in future. Apart from security being a top priority, there’s another area that is key to the longevity of your strategy. Scaling growth of data governance is often left out of the equation, added on as an afterthought to an often-lengthy document. There are multiple dangers here – including the ability to forget the basic strategy in the first place, but also scaling the growth of that strategy as you reach global levels of data gathering.

Identify Data Access

Mapping roles and responsibilities, access and security and ultimately the department responsibility will guide how your organization handles data governance. Creating a data access agreement adds a formal layer to your strategy, highlighting security levels and identifying which roles have ultimate responsibility for stored data.

Address Legal Barriers

Emerging data trends are currently being guided by data governance litigation. Data laws have been quite lax in the US until recently. However, CCPA is looming in California as data governance is rapidly expanding globally. A clear data storage and governance strategy will allow your enterprise to adapt and change with the varying layers of law as they come to affect your data.

Scale Data Systematically

The complexity of wrestling with huge quantities of data, especially when collected across multiple regions with language variants, is an area where additional tools can support. Through functional and user-friendly interfaces, these tools allow businesses to scale up data collection through a new way of deploying lead forms. Below we discuss tools further, but scaling and growing data sources is ideally reviewed by the data manager alongside an audit of support tools.

Grow and Maintain Quality

Data acquisition is divided into four methods: Converting legacy data, exchanging or sharing data, purchasing data and acquiring new data. Each of these methods will require an in-depth review using the following objectives: Access, Compliance and Quality Assurance. Once these areas are established, factor in scaled growth across region and language. Here are five ways to improve your data quality.

Operationalizing your Strategy

Who is responsible?

Cross-departmental groups should take the lead in large enterprise data governance planning. Whilst it’s useful to gain insight from the IT department, it should not only fall onto this team to provide technical advice and manage and govern data on its own. Organisations should consider electing a data governance board, data trustees and cross-business functional heads to lead the discussions. A data trustee is accountable for the security and privacy as well as the data quality and definitions used within the domain of data governance.

Building your framework

Apply a data maturity model to your current framework to see how it holds up. Make sure that your data framework includes all aspects of your larger business goals in data form. Reaching targets and maintaining clean data should be at the forefront of your framework. Make sure your framework is trustworthy, complete and generally understandable to all teams in the business.

Technology and tools

First, get your data under control. Once you do, take full advantage of its value by scaling the audience to reach everyone in a clear and concise manner on a global scale. The process of data governance can often lead to a bottle neck – clogging the data gathering with unnecessary steps. Free your employees of boring, repetitive tasks. Give them the tools to work simply and smoothly within your marketing and IT functions to truly access a data set that will see your business soar. Although tools are not the singular answer to this issue, it’s essential that your data governance team understand the various solutions available, such as big data platforms, data warehouses, data lakes, ECM (enterprise content management) systems, quality solutions and data management solutions. Each of these are not necessarily required. However, when you do take on a new solution, be sure to factor in training costs within the budget to ensure full usage.

Training and monitoring

Every business is unique, and a detailed training and monitoring plan should be outlined by a data governance manager. Roles and responsibilities can be implemented more easily by identifying training requirements and continuously monitoring data management. As mentioned in the above section, tools and tech may require their own training. But there is also wider training across the entire organisation to implement – data handling, processing and storage are all areas that should run as regular training and management sessions for the appropriate team members.

How We Can Help?

This guide may seem like a mountainous task to achieve a marketing data governance strategy that works for your enterprise. However, there are tools and tech to support you through each step. In our digital era, much of data collection relies on automation and support tools like Our site offers tons of resources to help you plan your strategy. Get in touch to discuss ways we can help you to start or audit your data governance journey.

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