8 Customer Data Management Best Practices To Follow

With more digital interactions than ever, and data flowing in from myriad sources into multiple systems, companies need to follow customer data management best practices to store and manage their data effectively.

However, the process of analysing and storing data can reveal issues like data inaccuracy or even data decay, which substantially harm the quality of the data being processed and stored.

Implementing a watertight customer data management strategy is essential to ensure your organisation does not become susceptible to vulnerabilities and avoids data discrepancies. This blog details the best practices in order to manage customer data effectively.

What Is Customer Data Management?

Customer data management is a process that encompasses all of the tools and frameworks necessary for businesses to collect, organise and analyse customer data. The result is a better understanding of customers, increased conversion and higher retention rates. 

When discussing customer data management, it’s usually on a first-party data basis (the type of data collected first-hand by your organisation). First-party data can detail anything from how your visitors interact with your website, to individual transactional data collected from user purchases.

Managing customer data is a complex journey if not done right. Data can be traced to the many different tools used by departments, all collecting slightly differing information about customers in their own way. 

Thus, when it comes to managing a customer’s personal info, cohesiveness is key: one of the ultimate goals for any organisation should be to move away from data silos and organise these multiple tools and data sources into one central system for your entire company to access. 

The History Of Data Management and Its Growing Importance 

Data management is more than just another buzzword: it’s now the backbone of any successful business. As it’s an ever-evolving process, businesses today are now able to collect and use customer data for a number of reasons. 

Some companies may want to know more about what customers are looking at, while others might be hoping that something in this information will give them an idea into how they can better serve their clients or even make improvements on products. 

Because most data-driven organisations now collect, aggregate, clean, organise and store data on a daily basis, data management has gained momentum as an effective practice to minimise errors and vulnerabilities whilst protecting data security.

In addition, with the increase in regulatory requirements and data volumes, organisations are also realising that their current systems for managing this information may not be sufficient. This results in a need for better access to a company’s datasets for more efficient management.

Overall, bringing together the multiple components of data management avoids the risk of data becoming siloed and unsecure.

8 Customer Data Management Best Practices To Follow

1. Outline your business goals 

Data analysis and data management are two of the most important parts of a company’s day-to-day operations. However, it takes time, energy and valuable resources to get the processes up and running correctly in order to obtain accurate insights that drive decision-making.

Because they are so resource-heavy, it’s essential first to outline your business goals to ensure that the analysis you perform matches the outcomes your business is trying to achieve.

Ask questions like:

  • Are you looking to increase customer acquisition or customer retention
  • Do you want to sell more of a specific product, or sell an entire product line?
  • Do you want to capture business from existing sources or instead acquire business from new ones?

2. Implement a data governance strategy

Data governance is an important initial step in quality customer data management because it will help you identify what information to collect and how. It also helps keep everyone on your team up-to-date about any changes in policy that affect managing customers’ personal info.

Every data governance strategy has three parts:

  1. Alignment: The alignment stage standardises the collection of customer data across your company.
  2. Validation: During the validation stage, you’ll need to confirm that the data is being collected to the best standard. 
  3. Enforcement: The enforcement stage ensures any changes that need to be made to the collection of data will go through the correct channels so that the collected data is collected in the correct manner and that it is useful.

The final result of your data governance strategy will be a customised and comprehensive collection system that not only increases efficiency, but also saves time by ensuring all the information about each piece is accurate.

3. Identify business critical data

To avoid overwhelming your Customer Data Platform (CDP), you need to ensure that the information being collected is relevant for business purposes. Even if it’s directly related to what a company needs from its customers’ personal information, gathering more than necessary can be problematic. 

For every piece of data you collect, audit it by comparing it against these three questions:

  1. Who needs this data?
  2. What does it do?
  3. If we didn’t collect it, could we still operate in the same way?

If the answers aren’t immediately clear, it may be worth evaluating with your team if the data should be deleted.

4. Avoid and break down data silos

Data silos occur when data is being collected by different departments in the same organisation, but the data is unintentionally not accessible between departments.

Data silos usually come from a lack of a cohesive data governance strategy for handling customer information across all areas. For example, Customer Support teams have no access to purchase history data in order to offer solutions that are relevant to each customer’s transactions. 

Meanwhile, Marketing teams might lack data on a customer’s previous support interactions to help them produce campaigns that target them based on the challenges they’ve faced.

Data works best when it’s shared across departments because it promotes cross-departmental collaboration, allows marketers to get a complete view of the customer journey and its touchpoints, and offers problem-solving opportunities across the company.

A Customer Data Platform (CDP) is the key to breaking down data silos. CDPs provide a single customer view that consolidates your data into unified profiles. It allows the product management team to develop products better aligned with customer expectations. 

They also allow marketers to create personalised marketing campaigns that target specific stages of the customers’ journey, and constantly monitor the digital customer experience

CDPs can even help analytics teams get a more accurate view of acquisition costs and lifetime values.

5. Evaluate data protection and security

Data security is one of the most critical elements in customer data management. No matter what type of data you’re collecting from your customers, they want their information protected and secure at all times. 

A data breach can cost the company a lot in terms of negative press and money; on average, it costs companies $25,612 in America for just one hack.

Making sure the Customer Data Platform (CDP) you’re using is compliant with up-to-date privacy and security regulations, which include certifications such as:

  • The ISO/IEC 27018, which demonstrates that Personally Identifiable Information (PII) in public cloud computing environments is protected
  • The Certified Information Privacy Technologist (CIPT), which demonstrates a company’s commitment to privacy through its top management being IAPP Certified International Privacy Technologists.

6. Keep data clean, accurate and actionable

The accuracy of your data can be affected when you collect it, but also months or years down the road because data changes over time — in a process known as “data decay.” 

Data decay happens when there are changes in information like email addresses, phone numbers, and physical locations. For example, an email address you collected from the Chief Financial Officer at Company Z might now be incorrect if that person has left the company.

Data inaccuracy can also lead to data decay if data collection events aren’t set up correctly. 

For example, a simple date such as MM/DD/YYYY vs DD/MM/YY will cause inaccuracy and change if at the point of collection an organisation doesn’t have a defined data governance strategy. Automatic data validation can solve this problem by testing tracking codes to make sure it’s working properly. 

The General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), both of which have been enacted in recent years, are changing the way that companies collect and manage data. 

These laws require businesses to get consent from their customers before they can use their information. This is why many company websites now include banners asking what you would like them to do with your personal data when visiting a site. If you’re using lead generation and marketing tools, you’ll also need to ensure these all operate within those regulations and fit your policies as well.

The challenge is twofold:

  1. Consent for an individual customer can be captured in multiple touchpoints, and then can differ for different activation channels and messages – which makes it difficult to act on consumer consent preferences at speed and scale.
  2. GDPR and CCPA regulations also require companies to give their users access to the data they have collected for deletion purposes. However, if your organisation is using multiple tools to collect data, the process of deleting and deploying your customer data becomes difficult. For example, if a single user’s data is stored in 3 different tools, a good Customer Data Platform (CDP) will make GDPR & CCPA compliance easier by enabling you to delete user data across all of your tools in one go. 

Even if your organisation doesn’t have a physical presence in Europe, it can still fall under GDPR rules if it is collecting data on visitors who reside in the EU. This leaves your website with two options, either:

  • Completely block people from the EU from accessing your website


  • Deploy consent management on your website to collect user data safely, then enable that data to be automatically reflected across omnichannel marketing campaigns using Consent Orchestration.

8. Have a data backup plan

You never want to end up in a situation where you need your data and it’s nowhere to be found. This is why preparing for the worst case scenario with a data backup plan is essential.

The statistics are alarming. 60% of SMBs that lose their data will shut down within 6 months if they don’t have a plan in place for what to do if disaster strikes. A good backup and recovery process helps avoid becoming one of those businesses not prepared for the worst case scenario.

Vital questions to consider when making your data-backup plan include:

  • What is your organisation’s data-backup plan budget?
  • What type of backup plan will be best for your organisation?
  • Where will your organisation’s backups be stored? 
  • Is the storage location safe and encrypted? 
  • What is your organisation’s data recovery plan?

The correct data backup plan keeps your customer data safe, making your organisation a reliable partner. 


Customer data management is the future of marketing. We cannot know about our customers without understanding their human needs and wants, which can only be done through a unified view that spans channels on customer interactions. 

Today, organisations must understand how to collect, analyse and organise the correct data in order to obtain insights capable of allowing them to deliver meaningful and personalised experiences to their buyers. Customer Data Platforms (CDP) can contribute significantly to these efforts when paired with effective customer data management, which can be achieved by following the above best practices and investing in the right CDP.

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