Customer data management is the practice of gathering and storing consumer information to improve a business's service and products. Customer data can also be converted into actionable insights to enhance specific operations, such as marketing campaigns and website development.
In order to protect sensitive shopper information and reap the full benefits of customer analytics, businesses should learn how to conduct data extraction and optimize their data usage.
6 Principles for Customer Data Management
Customer data management includes collecting, organizing, and using consumer data to improve insights, shopping experience, and sales. Customer data can be collected from online browsers, loyalty members, and even first-time buyers. However, businesses should know how to properly manage this information to optimize their usage.
By understanding the six principles of customer data management, companies can improve their data collection and maintenance strategies-
1. Implement a Data Governance Strategy
Data governance helps businesses identify the type of information they need to collect and how to gather it. It also keeps employees on the same page and working in unison towards the same customer data management goals.
The typical data governance strategy has three parts-
- Alignment is the stage that standardizes how customer data is collected throughout the company.
- Validation is when the company confirms that data is being collected appropriately.
- Enforcement ensures that changes to the data collection method run through the appropriate channels.
By establishing these three steps, organizations can develop a tracking plan that details each piece of data collected, who uses it, what it's used for, and its ownership.
Without creating a governance strategy, businesses may have trouble converting data into actionable insights or find that multiple operations are collecting the same data, decreasing efficiency.
2. Prioritize Critical Data
Businesses need to ensure they are only collecting data pertinent to their company, or else they can end up wasting valuable time and resources on needless information. Collecting useless data can also overload the customer data platform (CDP), significantly restricting efficiency and productivity.
Every piece of data collected should be audited to determine its-
If a company audits their data and finds they cannot assign its purpose, value, and advantage, they should not be quick to discard it. Instead, management should ask around to appropriate departments to determine if the information is needed and relevant. If, after a thorough investigation, the organization still can't justify the data collection, they can then discard it.
3. Avoid Data Silos
Data silos occur when different departments within the same company are collecting data but fail to exchange the information. While this is not typically intentional, it stems from a lack of data governance.
For example, if a retailer wants to determine the customers' reaction to the new product line, they can collect data from-
- Social Media
- Online Reviews
- Traditional Surveys
- E-commerce Tracking
While social media managers could find there are only a few customers that enjoy the new product, data analysts may discover an increase in shopping cart abandonment. By storing data in silos, neither department would be aware of the other's findings, making it difficult to determine why there isn't much response.
By encouraging collaboration between departments, companies can gain better insight into their customer journey. Data exchange also enables stakeholders to make data-based decisions to improve performance.
4. Focus on Data Security
Data security ensures that information is protected from unauthorized users at all times, from collection to storage. Regardless of the type of data a business gathers, they must establish data security measures to protect valuable customer information.
Just one data breach can do irreparable damage to an organization's reputation and cost the company customers and capital to reconcile the data. In the United States, the average data breach can cost a business up to $7,910,000.
Companies using a customer data platform should ensure the solution is compliant with the ISO 27001 based security program. This program requires the platform to regularly review, refine, and improve their security measures.
5. Create a Data Accuracy Process
Data accuracy can be affected during the collection process if companies do not have a data governance strategy.
However, businesses can improve their data accuracy by using automatic validation processes. This solution automatically tests the tracking codes to ensure they are working correctly.
Accuracy can also decrease due to data decay, or when information changes over time. This often occurs when customers change their numbers and addresses, and the data no longer matches the information stored. By routinely discarding data from inactive customers, companies can clear up decay and secure master data.
6. Remain Compliant with Data Regulations
There are several data privacy laws businesses must abide by, such as the California Consumer Privacy Act (CCPA). These regulations determine how companies can collect and store customer data to ensure the safety of personal information.
The CCPA allows customers to request that companies delete their personal data. While this may be difficult for organizations that use multiple customer data platforms, by utilizing a CCPA compliant solution, businesses can delete information from all tools at once.