Data is the new oil: Why customer data management is critical

How much time does it take to manage customer data effectively? How do you ensure that you don't miss out on anything?

Customer data management (CDM) is the practice of managing customer information across multiple channels and systems. This helps businesses gain insights into their customers' behaviour and preferences.

The oft-repeated phrase, "data is the new oil", rings true, and companies that fail to properly manage their customer data risk being left behind.

To get started, you'll need to identify where your data lives today. Then, build a plan to move forward. The good news is that CDM tools exist to help you automate processes and streamline operations.

In this article, we look at customer data management, its benefits, key principles of effective customer data management, and elements of an effective customer data management strategy.

Customer data management and the customer experience

Customer data management is the practice of collecting, organising, and using data about customers to improve the customer experience and support business objectives.

This can include things like collecting information about customer preferences, purchasing habits, and interactions with a company's products or services.

This data is often used to create targeted marketing campaigns, improve products or services, and provide personalised customer support.

By effectively managing customer data, companies can gain valuable insights into their customers and use this information to drive business growth and success.

Lesser known benefits of customer data management

There are several other key benefits of customer data management, including:

1. Increased sales and revenue: By using customer data to create targeted marketing campaigns and offers, companies can drive more sales and increase revenue.

2. Enhanced product and service development: By analysing customer data, companies can identify trends and patterns that can inform product and service development, leading to improvements and innovations that better meet customer needs and preferences. 

3. Reduced costs: By using customer data to automate processes, such as customer support or marketing, companies can save time and resources, leading to cost savings.

4. Improved customer insights: By analysing customer data, companies can gain valuable insights into customer behaviour, preferences, and needs, which can inform business decisions and strategies.

The pillars of effective customer data management

There are several key principles and practices that organisations should follow to successfully manage their customer data. These include:

1. Data governance

Data governance involves establishing policies, procedures, and processes for managing customer data in a way that is compliant with relevant laws and regulations, and that protects customer privacy and security.

A data governance strategy is important because it establishes clear policies, procedures, and processes for managing data in a way that is compliant with relevant laws and regulations, and that protects data privacy and security. 

A data governance strategy can help organisations ensure that their data management practices are consistent, transparent, and accountable, and that they are aligned with the organisation's overall business objectives.

Having a clear data governance strategy in place can also help organisations avoid legal and regulatory violations, and can protect them from the financial and reputational risks that can arise from inadequate data management. 

Additionally, a robust data governance strategy can help organisations build trust and confidence with customers, employees, and other stakeholders, by demonstrating a commitment to responsible and ethical data management practices.

A data governance strategy can help organisations ensure that their data management practices are compliant, effective, and aligned with their business objectives.

2. Data quality

Data quality involves ensuring that the collected customer data is accurate, complete, and relevant, and that it is regularly reviewed and updated to maintain its quality.

Customer data quality is important for several reasons. 

First, high-quality customer data is essential for effective customer data management, as it enables organisations to gain accurate and complete insights into customer behaviour and preferences. 

Without high-quality data, organisations may make decisions or take actions based on incomplete or inaccurate information, which can lead to wasted resources, missed opportunities, or even negative impacts on customers.

Second, high-quality customer data is essential for creating personalised experiences that are tailored to individual customers. 

By using accurate and up-to-date information about customers, organisations can create marketing campaigns, product recommendations, and other experiences that are relevant and engaging to customers, which can improve customer satisfaction and loyalty.

Third, high-quality customer data is essential for protecting customer privacy and security. Inaccurate or incomplete data can make it more difficult to adequately protect customer information, which can expose customers to privacy risks and increase the likelihood of data breaches or other security incidents.

Customer data quality is important because it is essential for personalised customer experiences, and customer privacy and security. 

By ensuring that customer data is accurate, complete, and up-to-date, organisations can gain valuable insights into their customers, and can use that information to drive business growth and success.

3. Data accessibility

Data accessibility involves making customer data easily accessible to those who need it, such as customer service teams, sales teams, and marketing teams, to support business objectives.

Data accessibility is important for several reasons. One of the main reasons is that it can help to ensure that data is used to its full potential. 

By making data easily accessible, organisations can more easily use it to make decisions, develop new products and services, and improve their operations. 

Additionally, data accessibility can help to support collaboration and information sharing within an organisation, which can lead to more efficient and effective work.

Data accessibility also helps avoid data silos. These are bad because they prevent different departments or divisions within an organisation from accessing and sharing data with each other. 

This can lead to inefficiencies and difficulties in making decisions, as different departments may be working with different or incomplete sets of data. 

In addition, data silos can create security vulnerabilities, as sensitive information may be stored in silos that are not properly protected. 

By breaking down data silos and promoting data sharing, organisations can improve collaboration, make better decisions, and reduce security risks.

4. Data integration

Data integration involves combining customer data from different sources, such as different departments or business units, to gain a comprehensive view of customer behaviour and preferences.

Customer data integration is important because it allows organisations to combine customer data from multiple sources and use it in a coordinated and meaningful way. 

By integrating customer data from different sources, organisations can gain a more comprehensive and accurate view of their customers, which can help them to better understand their needs, preferences, and behaviours. 

This can enable organisations to provide more personalised and effective services to their customers, which can improve customer satisfaction and loyalty. 

Additionally, customer data integration can support collaboration and information sharing within an organisation, which can lead to more efficient and effective work.

 5. Data security

Data security involves protecting customer data from unauthorised access, use, or disclosure, and implementing measures to ensure the security of customer data, such as encryption, access controls, and regular security audits.

Customer data security is important because it helps to protect sensitive information about customers from unauthorised access, use, or disclosure. 

This can include things like credit card numbers, social security numbers, addresses, and other personal information that customers have provided to an organisation. 

By protecting this information, organisations can help to ensure the privacy and security of their customers, which can build trust and confidence in the organisation. 

Additionally, protecting customer data can help to prevent financial losses and other negative consequences that can arise from a data breach or other security incidents.

The cost of data breaches can vary depending on several factors, such as the size and nature of the organisation, the type and sensitivity of the data involved, and the extent of the breach. 

According to a report by the Ponemon Institute, the average cost of a data breach for organisations in the United States in 2022 was 4.35 million USD. 

However, the cost can be much higher for larger organisations or for those that experience more severe breaches. In some cases, the cost of a data breach can include legal fees, damage to an organisation's reputation, and loss of customers or revenue.

The difference between CRMs, CDPs, and DMPs

customer relationship management (CRMs), customer data platforms (CDPs) and data management platforms (DMPs) are all used in the context of customer data management, but they refer to different types of systems and technologies.

CRMs help companies manage customer interactions and relationships, such as by tracking customer information, managing customer interactions, and automating processes such as sales, marketing, and customer support.

CDPs help companies collect, organise, and analyse customer data from a variety of sources, to gain insights and support business decisions. CDPs are often used to create personalised customer experiences, such as targeted marketing campaigns or personalised product recommendations.

DMPs help companies manage and organise data, such as customer data, to make it easier to access and analyse. DMPs are often used in the context of digital advertising, to help companies target their ads to specific audiences based on their interests and behaviour.

The main difference between these three types of systems is their focus and functionality. CRMs are focused on managing customer relationships, CDPs are focused on collecting and analysing customer data, and DMPs are focused on managing and organising data.

Key elements of an effective customer data management strategy

A customer data management strategy needs to include several key elements to ensure that your organisation's approach is effective. These elements include: 

1. Data collection: Establishing processes for collecting customer data from a variety of sources, such as online forms, surveys, customer interactions, and other sources.

2. Data organisation: Organising the collected data in a way that makes it easy to access and analyse, such as by creating customer profiles or segmenting customers into different groups based on their characteristics.

3. Data analysis: Using tools and techniques to analyse the collected data, such as statistical analysis, machine learning, or other methods, to identify trends, patterns, and insights.

4. Data usage: Using the insights gained from the data analysis to inform business decisions and strategies, such as creating targeted marketing campaigns or improving products or services.

5. Data governance: Establishing policies, procedures, and processes for managing customer data in a way that is compliant with relevant laws and regulations, and that protects customer privacy and security.

Ensuring your customer data management is effective

While it's clear that effective customer data management is important if you want to leverage it to its full potential, doing so is not always easy, especially for mid-size or enterprise organisations. 

One way to ensure that your efforts are to partner with a data management consultant who can help establish best practices and set in place a strategy that will help guide your entire organisation’s management of customer data.

At Huble, we’ve helped implement CRM solutions for many organisations across the globe, enabling them to gain a deeper understanding of their customers and serve them better. If you want to hear how we can help you with your customer data management needs, contact our team.