Data Governance in Marketing: Why It Matters and How It’s Done

A strong data governance strategy is foundational for modern marketing. Data governance best practices are a formal set of policies, processes and procedures—enabled by technology—that dictate how data is treated as it flows throughout the organisation. A strong data governance strategy should seek to break down silos, create standards for data format, storage and treatment, and ideally create that single source of truth marketers dream about.

Read on to learn what marketers and marketing data analysts need to know about data governance.

Then check out our latest guide, Data, Insight, Action: Machine Learning & AI for Marketing Analytics, for an in-depth exploration of customer data and marketing analytics in the age of machine learning.

Why Data Governance Matters for Marketing

#1: Compliance

Let’s start with the most obvious benefit of good data governance: Legal compliance. Laws like the EU’s General Data Protection Regulation require organisations to closely comply with consumers’ data preferences. The penalties for violation can be staggering. The highest fine to date was 746 million euro, or about $662 million pounds.

Managing permissions and privacy is virtually impossible in an organisation with siloed data. Customers might express their preferences to the customer service department, for example, and marketing might continue to use their data, never realising the customer has opted out using another system.

#2: Customer Trust

Beyond simply avoiding a fine, there’s a far more valuable business asset at stake here. Customer relationships are built on trust, and customers increasingly expect transparency about how their data is used, and whether it is to the customers’ ultimate benefit.

A good data governance strategy can help earn and reward that trust, enabling businesses to make strong claims about privacy and data usage. Moreover, data governance can provide the proof to show that customer requests are being honoured throughout the organisation.

#3: Consistent Customer Experience

Let’s go beyond the minimum of “don’t abuse customers’ trust or run afoul of the law.” Data governance can also actively improve the quality of your marketing and its relevance to customers.

In a siloed organisation, for example, a customer could buy a product in your retail store, be dissatisfied with the purchase, complain to customer service, be issued a refund… and then receive an email voucher to buy the same product.

A good data governance strategy that unites and standardises data across the organisation creates a working memory of each interaction with an individual customer, both online and offline.

A solution like Adobe Customer Journey Analytics compiles data across channels into actionable customer profiles. This means customers can feel seen, known and understood as individuals, rather than reintroducing themselves to the organisation with every new interaction.

#4: Capacity for Personalisation

All of the above are primarily concerned with data governance from the customer perspective. From the marketing perspective, there are clear advantages,too.

With a standardised, central source of data available, analysts can apply machine learning to spot trends, identify buying signals and customers at risk of churning, and much more. Intelligent algorithms can even create audience segments based on the behaviour of customers who have chosen to remain anonymous.

All of this means smarter, more relevant personalisation. With the addition of a solution like Adobe Journey Optimiser, you can even automate these personalised experiences in real-time and at scale.

Best Practices for a Data Governance Strategy

The first step in developing a smarter data governance strategy is to map your organisation’s data landscape. It’s important to understand where different types of information are stored, who has access, and where data is being duplicated or connected to other systems.

It’s doubly important to distinguish where personally identifiable information is stored and who has access. This type of data is of paramount concern for legal compliance and managing customer permissions.

Once that map is in place, you can begin to map out your governance journey. Keep these best practices in mind:

#1: Centralise Systems and Policies

It’s important to make your strategy organisation-wide, with a minimum of exceptions. This will make it easier to manage the change, as well as monitor and ensure compliance. Centralisation also reduces the amount of IT overhead needed for governance.

#2: Standardise Data Formatting

If your marketing department uses dd/mm/yyyy formatting, but customer service uses mm/dd/yyyy, combining their records can lead to confusion. Standardisation is a crucial part of centralisation. Automated tools can make data cleansing less of a time-consuming manual process.

#3: Plan for Scalability

Your organisation will take in more data over time, not less. Any data governance strategy should take future growth into account. This should include practical considerations like storage and access control, as well as processes and people concerns.

Your data governance plan should also account for potential future privacy regulations. While you can’t predict the future, the processes and systems you put in place should have the flexibility to meet new guidelines and restrictions.

Choose a Platform with Data Governance Built In

Proper data governance requires a central source of data truth — an intelligent data platform that can actively help manage the flow of data. Adobe Real-Time CDP, on Adobe Experience Platform, makes it easy to implement enterprise-wide data governance. The result is smarter governance with fewer resources needed to administer and maintain it.

Ready for a deeper dive into marketing analytics and machine learning? Read Data, Insight, Action: Machine Learning & AI for Marketing Analytics to get started.