Customer Data Management | 4 mins read

Customer Data Management- 5 Best Practices for Ethical Data Collection

customer data management 5 best practices for ethical data collection
Jin Hyun

By Jin Hyun

When it comes to building a worthwhile service for clients and customers, firms need to be focusing on data. But how does customer data management work in practice?

Essentially, customer data management is the process of bringing together consumer information from a variety of different sources. It allows users to build clear profiles on specific customers and target audience members.

This data collection and analysis have become crucial in managing business growth and operations planning. Ultimately, it can help businesses understand and appreciate their customers' needs and deliver meaningful personalization of products and services. Therefore, effective data control could help to improve customer satisfaction as well as increase revenue.

3 Types of Customer Data Collection

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It's important to consider how companies and analysts get around customer data management. To build an effective customer profile while safely managing personal information, a specialist or team of analysts may need to consider a variety of practices.

Companies can obtain and use data through the way their customers use websites and online forms. Of course, due to data protection laws around the world, such as the General Data Protection Regulation, businesses must now be explicit when advising customers that their data is being collected.

To build leading customer databases and marketing data, it is important to consider various options. Here are a few examples of data collection already in use today-

1. Top-of-Funnel Data
This refers to low-consequence, easily attainable information, such as emails and names. While this basic data is susceptible to irrelevant leads and false information, it's effective when testing the success of email marketing campaigns. Businesses can collect this information by using the following tactics-

  • Web Page Buttons - Embedded or inline buttons on business websites can ask visitors to provide this information in exchange for free product trials, downloadable digital resources, or product demos.
  • Pop-Up Forms - Businesses can use customized triggers (time spent on the page, initiated exit, first-time entrance onto the website) to automate lead generation forms to pop up on a web page.
2. Bottom-of Funnel Data
Bottom-of-funnel prospects are visitors who have already expressed interest in purchasing a product or service, meaning they are usually willing to give out more detailed personal information to access resources and learn more about what the company has to offer them.

In order to gain the most value out of this method of data collection, businesses can design landing-page forms dedicated to promoting one particular product or service. Data fields can also be customized by the business to collect the desired and most appropriate customer information.

3. Existing Customer Data
This refers to consumers who have already purchased a product or service from the business. These current customers can help provide insight into how the business can improve their existing products and customer service.

This high-value data can also inform businesses of gaps in their existing range of products and help to brainstorm ideas for new items. Collecting and utilizing this information can lead to increased customer retention and revenue.

  • Questionnaires - Businesses can create questionnaire forms to gain feedback from customers. To gain the maximum value from this method, ask questions that invite long answers, and avoid yes or no questions.
  • Follow-Up Calls - This data can be collected after a purchase is made or after the consumer has interacted with the brand. These conversations can be brief and can include yes or no questions or ratings out of 1-10.

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5 Best Practices for Customer Data Management

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The above examples offer a snapshot of the simpler and non-intrusive ways to obtain and build reliable customer data profiles. However, after collecting this information, businesses must manage this sensitive information carefully to protect customer identities and consumer trust.

Here are a handful of data management best practices modern firms should consider-

1. Make Security a Priority
Studies show that a data breach costs a business $3.86 million on average, while small and medium-sized businesses lose an average of $120,000 for every time there is a breach in data. Ensuring that customer data is secure helps businesses to avoid these costs while building consumer trust. To secure personal information, companies can invest in backup systems and customer data training for staff members.

2. Practice Ethical Data Collection
Trust is critical to customer loyalty and retention, and the best way for businesses to retain trust while collecting data is to remain transparent and honest. Businesses can ethically collect consumer information by providing straightforward surveys, allowing customers to choose which information they would like to share, and drafting a clear privacy policy.

3. Only Gather the Necessary Data
Around 60% to 73% of data within a business goes completely unused during the analysis process. This data saturation can overwhelm companies and distract management from efficient decision making.

Before collecting consumer information, businesses should first decide which information to prioritize, how the data aligns with company goals, how the information will be analyzed, and how this information will help to improve the business.

4. Back up All Data
Data recovery and backup plans are essential for businesses of all sizes. However, 58% of small to medium businesses are unequipped to deal with data loss scenarios. Choosing and installing the best backup plan for a company will help keep customer data secure while increasing trust in the brand.

5. Cleanse and Clean Customer Data
Customer information can become outdated relatively quickly. In fact, some sources state that up to 25% of an average B2B marketer's data are inaccurate or out of date.

In order to utilize customer data effectively and enhance the quality of information, businesses must update and validate information such as home addresses, phone numbers, and emails regularly and ensure duplicates and irrelevant contacts have been deleted.

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