The future of omnichannel: Manufacturing, D2C, data in e-commerce era
Whether B2B or B2C, it's no longer enough to survey customers. To engage, retain, and earn customers, brands must understand buying habits and behavioral patterns.
Shifting business models and increased customer expectations make growth in the age of massive data sets complex, to say the least. Customer data management by definition is having systems in place not just for collection, but also for the protection and use of data. Having a customer data management strategy has grown beyond previously designed tools, and is crucial for brand success in marketing, sales, CX, and more.
Defining your strategy for customer data management is mission-critical, as is finding the right solution for it.
Start with the customer data management (CDM) definition
Customer data management definition is the operation of gathering, organizing, and drawing insights from customer data across multiples sources and filtered through specific qualifiers in order to create unified customer profiles. This process creates valuable information to build upon across diverse departments in an enterprise with a dual-pronged end goal of improving customer experience and revenue.
Understanding why you are collecting data, really thinking through the end-use, helps to create a process of combining planning and data to achieve goals. Customer experience is actually a part of the customer data management definition because as data is more closely regulated and customers expect more personalization, your data collection needs a plan.
What is customer data management strategy?
A customer data management strategy is defined as the practice of collecting, storing, and using customer data. It allows a brand to better understand, target, and serve its customers – and its importance cannot be underestimated – experts estimate the cost of poor quality data to be several trillion dollars per year.
Research shows the vast majority of consumers are more likely to make purchases from brands that offer personalized experiences.
Customer data management strategy: 7 best practices for success
The thing is, a successful customer data management strategy is not simply about the technology that supports it. It includes automation-driven software that aggregates and organizes customer data across devices and channels and eliminates silos, building unified customer profiles that reflect the entire path-to-purchase.
The customer data management definition clearly lays out a need for processes and guidelines. Brands need to adopt 7 best practices around a customer data management strategy to help define an overall plan and goals:
- Understand the business objectives
- Cleary define the data strategy use cases
- Understand data governance standards – before you start
- Identity must be at the core of your customer data management strategy
- Recognize that data privacy betters the experience for brands and customers
- Define who has control over the customer data internally
- Select technology that’s real-time, data-driven, and best for your sector
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Organizations should focus on business objectives to craft a customer data strategy
To focus on business objectives, you need to understand them. Here are two questions you should ask:
- What are you looking for customer data management strategy to do for your brand?
- What are the business goals and objectives you’re trying to achieve?
Whether it is to foster personalized experiences, improve privacy and accuracy, or boost the bottom line, figure out what’s driving attention and investment in this area.
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Data strategy use cases should be clearly defined
Customer data management use cases should be defined to reflect the different ways that teams and departments will benefit.
For example:
- Marketers may want to set up parameters for known customer behaviors to trigger personal engagements.
- Sales may want to integrate customer data with other tools to determine buyer intent.
- Customer service organizations want the full context of a customer’s experience with a product or service at their fingertips.
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In today’s online marketplaces, data governance standards are required
For successful customer data management, it’s essential to establish a framework of policies and standards that address compliance, regulations, and handling of data across the enterprise.
With the right data governance standards in place, brands can:
- Improve decision-making
- Avoid collecting bad data
- Boost security
Identity should be at the core of any customer data management strategy
Knowing your customer is a primary goal for any customer data management strategy. That means honing in squarely on identity. The brand must unify customer data around a foundational identity in order to create holistic, first-party profiles.
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Data privacy serves the interests of both customers and brands
Your customer’s interests should be at the heart of customer data management strategy, which, in turn, helps boost the brand. That includes respecting data privacy.
After all, According to Gartner, 65% of the world’s population will have its personal information covered under modern privacy regulations in 2023.
Brands should make sure their customer data management tools fully address consent and permissions.
Customer data ownership should align with goals
Different teams may use customer data management for various use cases, but brands should make sure to determine who has responsibility and ownership over customer data.
Is it marketing operations? Sales? IT? Does a member of the management team play a key role?
There’s no right answer, but the decision should align with the organization’s goals.
Choose technology based on real-time customer data management
Data-driven insights help brands understand their customers, engage with them confidently, and deliver on brand promises.
Customer data management requires best-in-class technology that provides real-time solutions to activate useful insights at just the right moment. Your investments should focus on tools that offer accurate engagement across every touchpoint.
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Customer data management strategy for omnichannel engagement success
Every brand needs to elevate their customer experiences if they want to stand out in a fiercely competitive landscape.
Whether that’s related to e-commerce, brick-and-mortar POS, B2B sales, or customer service, how organizations tackle the vast data sets that help them understand customers more deeply can make the difference between long-term loyal customers and cart abandonment.
Focusing on the best practices that enhance holistic, unified customer data management is a must for any brand looking to unlock omnichannel customer engagement.
Taking these seven principles and employing them in your customer data management strategy is a surefire way to accelerate your journey to success.