Customer data management (CDM)

Define your customer data strategy by starting with your vision and objectives for becoming more data-driven and customer-oriented in the years ahead. Identify your target customers and pinpoint the main challenges and opportunities they face throughout their journey with your brand. Ensure alignment of your vision and strategy with key stakeholders.

Next, outline relevant use cases that support your defined objectives and translate them into necessary capabilities across platforms, processes, and people. Determine the specific customer data needed, along with collection methods and usage scenarios.

While maintaining focus on your long-term vision, proceed incrementally by starting with key use cases and conducting Proof of Value or pilots within your organization. Think big, but initiate action on a manageable scale to achieve tangible progress.

Based on your clarified objectives and needs, as outlined by clear use cases, you can pinpoint the necessary capabilities, some of which will translate into technical requirements. Assess the disparities between your current customer experience (CX) tool ecosystem and the required capabilities, determining whether new solutions or adjustments to existing components are necessary.

Two key areas of focus in CDM include establishing a robust data warehouse for collecting and storing specific customer data, and implementing a customer data platform (CDP) to seamlessly gather and activate customer data in real-time when needed.

Our primary objective is to ensure your organization’s data is structured, organized, and readily accessible for optimal impact. Whether you need to centralize data from diverse sources, establish adaptable data pipelines, or develop resilient data frameworks, collaborate with our experienced team or partner supplier to devise a customized architecture tailored to your unique business needs.

Establish and configure the necessary customer data architecture and tools to gather a multitude of customer-related data, ranging from demographic details and contact information to purchase records, browsing patterns, social media engagements, and beyond. Throughout this phase, it’s essential to cleanse the data, addressing any duplicates, verifying accuracy, and rectifying discrepancies as necessary.

An integral element of CDM is the ethical handling of all customer data, ensuring compliance with worldwide data protection regulations like GDPR, CCPA, and others. This entails implementing stringent data governance protocols, obtaining customer consent where needed, and fortifying data security measures to prevent breaches.

Using a unified and refined dataset, you gain the ability to analyze customer data comprehensively, unveiling valuable insights into customer behavior, preferences, and emerging trends. Leveraging advanced analytics and AI capabilities, you can pinpoint patterns, unearth intriguing customer segments, and anticipate future behaviors, empowering targeted marketing initiatives and informed strategic choices. By categorizing customers with shared characteristics into segments or audiences, you can tailor your approaches more effectively.

The true value emerges when leveraging customer data to enhance the customer experience. Customer segments or audiences are dynamically activated across various channels (e.g., advertising platforms, social media, marketing automation, web personalization, customer care), optimizing and personalizing interactions at every touchpoint with your brand.

In a robust CDM architecture, segmentation transcends traditional static categorization, evolving into flexible customer cohorts. Customers dynamically qualify or disqualify for segments or audiences in real-time, enabling the delivery of consistently relevant and precise communication. Research and experience affirm that this approach heightens customer satisfaction, boosts conversion rates, and drives revenue growth.

In the early stages, prioritize refining processes and empowering individuals within your newly established customer data management architecture. Given the transition from traditional silos and the introduction of enhanced capabilities, adapting or developing new processes becomes imperative. Additionally, consider introducing or reshaping roles to be filled by individuals possessing the requisite skills and experience for effective implementation.