Building marketing cultures centered around accessible and actionable customer data for all
With evolving privacy laws, changes in consumer privacy preferences, browser restrictions/the death of third-party cookies, data deprecation is no longer imminent—it’s rapidly become a reality. In response, CMOs must bring an ecosystem-oriented mindset to MarTech and rely on accessible first-party customer data more than ever.
The path to fostering a marketing culture centered around accessible and actionable customer data for all is data democratization, which is the process of enabling everybody in an organization, irrespective of their technical know-how, to work with proper data comfortably, to feel confident talking about it, make data-informed decisions, and build meaningful customer experiences.
Gartner® points out that “as business users get more involved in data management, organizations are reevaluating their solutions and demanding offerings that align with business oriented KPIs.” This is creating an enormous competitive advantage for companies that enable their teams to rapidly integrate data and use the insights throughout different aspects of the marketing flow, from research to acquisition and from engagement to optimization. “By 2025, 70% of organizations will choose data management software products based primarily on the business user experience, up from less than 20% in 2021,” according to Analysts Alan Dayley and Sharat Menon, Gartner Inc.
What follows is a high-level summary of the factors that are driving marketers to double down on data and the common milestones across the data democratization journey.
The Driving Factors
Marketers request data access for two primary reasons: messaging and communication experiences and insight development. In the past, that meant a business user would sit with an IT person to define list criteria or interrogate the data. The value of data has skyrocketed in recent years leading to more data requests. Data-driven marketers cannot afford to wait in the queue for their request to be processed because their customers will not tolerate it, as their expectations are near real-time. They will look for brands that can deliver more dynamic experiences than is possible from a dated list or marketing brief. “Time and money spent on data and analytics enablement, from data democratization to embedded analytics, is wasted when work is not connected to business decisions,” according to Create The Culture Needed to be Insights Driven, co-authored by Srividya Sridharan, VP, Group Director, Forrester.
Enterprise data management is another aspect. Marketers are investing heavily in creating a single unified profile to deliver better journeys or execute loyalty programs where rewards points represent currency which must be displayed accurately with no exceptions. Creating a unified view of your customer also means that data requests need to be handled by a single shared services team that can change their mindset from lists supporting individual channels (email, paid media, etc.) and expanding that to an overall journey.
Delivering right sized access to allow marketers to execute journeys could be the response to these trends. Brands are finding that in doing so, the more success they have and the more requests they receive throughout their organization. Getting ahead means investing in the right infrastructure to harness data, governance, and tools.
The Building Blocks Along the Data Journey
There are stages in the data transformation process and key considerations for each step. Having a roadmap and understanding the key obstacles to success is critical on the road to democratizing data.
The Early Days – Organizing Your First Party (1P) Data Across the Enterprise for Better Customer Experiences:
Think of data as individual blocks residing in disparate places throughout your organization. Building upon the data, block by block, will help to drive transparency helping you better understand your customers.
- Unified customer view: Imagine having a one-to-one customer view. Democratization is likely not the initial goal, but it is a prerequisite for success.
- Personalization: Unified data will help you recognize customers across offline and online channels. You’ll start by personalizing within your owned channels. The ideas on how to do this better and better will strengthen over time. Eventually you can apply this to enable real-time targeting online as well as target optimization. People will want to interrogate the data as they see success and activate audiences on their own.
The Transformation Stage – Rethinking Basic Operational Tenants to Understand Your Data’s Value:
The data blocks do need fences. Getting the right data to the right users is a strategic (and responsible) imperative.
- Data Governance: This will evolve as you mature. But shifting access from a central IT
- organization to a broader team requires tight controls. You will need to determine the right level of access across the organization, create clear user personas and have strict rules and business processes to ensure customer data is handled responsibly.
- Data Center of Excellence: A central group representing multiple functions must be created both for change management, adoption and of course governance. Uniting data literate people across internal teams is a massive accelerant for democratizing data.
Maturation – Optimizing Entire Journeys with Analytics and Insights:
The blocks are coming together, forming real people and audiences with similar attributes.
- Common Audience Definition: Towards the end of your journey, you will be ready to start handling all the diverse types of audiences. Allowing different marketers to create their own version of “outdoor enthusiast” or “vegan” can lead to an unruly number of audiences. Defining common audience definitions while respecting regional needs is a critical step. Deciding who owns that decision doesn’t have to be tricky.
- Analytics Driven Experiences: Once you have created standard audience definitions, the next step is determining who gets to talk to them and when. Developing predictive models that encompass first party interactions and enriches them with shared data is key to understanding which brands or business units a consumer wants to hear from; transcending that it is always the highest revenue product. Investing in data sharing practices across the organization can be a big unlock.
Data democratization is about helping your business move faster to keep up with demanding consumer expectations. The tools and skills will evolve as you mature, but the goal should be to organize your online and offline data and set it up in a way that IT and Data Science teams can easily query any audiences, and marketing teams working in clean rooms can use data to optimize and automate major aspects of their workflow. Having an enterprise ready Customer Data Platform (CDP) that can manage online and offline data is a foundational step in making data democratization a reality.