What is customer data management?

Customer data management is an all-encompassing term for the tools, processes, strategies, and standards that a business deploys to manage customer data.

This management has become essential as our digital economy has created an explosion of customer data.

Therefore, businesses have access to more customer data than ever before. But the downside to the overabundance of customer data is the challenge of making sense of it all, along with ensuring its high quality.

This is vital because up to 83% of businesses lack confidence in enterprise data accuracy. This means that most data-driven companies are being misled by dirty data. After all, your decision-making is only as accurate as the data it’s based on.

This article will explain customer data management and how to manage customer data.

An overview of customer data management

CDM or customer data management involves the practice of acquiring, organizing, and storing customer data. It enables organizations to analyze data and understand customer intent and behavior.

However, customer data management involves more than just the tools utilized to make sense of data. It also includes both the security measures for protecting customer data and ethical framework for customer acquisition.

In addition to being used for sales and marketing purposes, it’s usage has to pass through the legal department to ensure it maintains regulatory requirements.

The ultimate objective of customer data management is to establish a quality data foundation.

The benefits of customer data management

Here are some of the benefits of customer data management:

• Provides a single, unified view of customer data: Placing all customer data in one tool provides immense benefits for software solutions. This is especially true for applications that manage customer data for sales and marketing teams. The centralization makes it easier to find customer profiles.
• Customer data hub: Customer data management improves operational efficiency across sales, marketing, finance, and customer service with accurate customer profiles.
• Identify and eliminate duplicate data: Customer data management makes it easier to find duplicate data in customer datasets. It also enforces normalization database techniques that reduces the entry and storage of duplicate data.
• Maintaining a high quality standard: A significant benefit to identifying and removing duplicate data is maintaining quality data by constantly analyzing, revisiting, and reviewing existing data.

5 Principles for improving customer data management

Possessing customer data doesn’t mean it’ll automatically work in your favor. Here are some of the principles and standards to follow in order to ensure your customer data works for you:

1. Create a data governance strategy

Data governance defines the processes, policies, and standards used to maintain data integrity and security. It’s regarded as the fundamental principle of good customer data management because it helps set markers on the type of data to be collected and how it will be collected.

2. Focus on relevant data

To boost and improve the quality of customer data, you need to have a laser focus on collecting customer data that’s highly relevant and useful to your organization. Acquiring unnecessary data only bloats your customer data platform needlessly, most likely with poor quality.

To collect quality data, you need to ask yourself the following questions:

• Who really needs this data you are collecting?
• Is there a viable use case for the data being collected?
• What does this data do, and if you didn’t collect it, will it fundamentally change how your business operates?

3. Avoid data silos

Data is most viable when it can be integrated and repurposed with other data to discover hidden insights. Unfortunately, decision-making suffers when managers aren’t able to understand customer behavior because they can’t find patterns.

The most common reason for data silos is because data is often collected independently for various departments in the same organization. Data silos are typically a manifestation of poor data governance or lack of a data orchestration strategy.

4. Implement robust data security

Good user data management entails protecting customer data from unauthorized access and misuse. Nothing reduces public trust for an organization more than poorly protecting customer data.

Inadequate data security results in data breaches that inflict reputational damage on the organization.

Also, non-compliance with legal requirements for personally identifiable information (PII) attracts heavy fines. According to IBM, data breaches cost companies an average of $4.24 million per incident.

5. Establish a data accuracy process

Data inaccuracy typically occurs at the point of collection. Your organization can avoid data inaccuracy by properly setting up data collection processes. For instance, ensure forms use the correct data and field types to capture information.

Another advantage of a refined data accuracy process is that it helps organizations curtail the collection of useless data. The problem with useless data is not only that it wastes storage, but usually breeds confusion about what the organization is doing with the data.

Wrong, useless, and inaccurate data inevitably leads to data security issues.

Customer data management made easy with Lytics

Customer data management has become imperative as companies generate data at an unprecedented level. But customer data management doesn’t have to be a hassle, even with the vast amounts of data you have to deal with.

If you’re looking to implement an effective customer data management system, talk to one of our experts or get started with a free trial.