Understanding Customer Data and How to Collect It

Before you begin collecting customer data, you need to identify the information you want to collect in the first place. The data you collect should be relevant to your business and sales goals and should help get you closer to achieving those goals.

There are four main customer data types to consider when beginning the process of data collection:

• Demographic data: Demographic data includes basic information gathered from clients and customers like name, address, gender, age, email, occupation, and other contact information.
• Purchase and buying behavior: This data refers to customer interactions with your company like recent purchases, customer loyalty data, purchase history, and trends in purchase behavior.
• Communication preferences: Your customers all have different preferences on how they want your company to connect with them. Whether it’s through email, SMS, or phone call, it’s important to know and remember each of your customers’ communication preferences.
• Engagement with digital channels: How your customers interact with different digital channels can say a lot about them and help you understand how they interact with your brand. Engagement data points to collect include social media likes, shares, comments, and follows.

Learn how to identify which customer data you want to collect:

• Identifying key customer segments

Customer data is used to help businesses gain valuable insights into their customer base and make data-driven sales predictions. The accuracy of these predictions rides on the quality of data being taken in. Through data quality and accuracy strategies, you can do just that.

Ensuring customer data quality and accuracy in a CRM starts with collecting data that is timely, accurate, reliable, and consistent. Not only does high-quality data help businesses make accurate sales forecasts, but it also helps them create targeted, data-driven marketing campaigns and supports sales representatives in delivering great customer service.

There are three major processes that can help you ensure you’re collecting and maintaining customer data that is timely, accurate, reliable, and consistent:

• Data validation: Data validation involves reviewing the customer data stored within your CRM to confirm it meets the standards and rules set forth by your business and industry. With data validation, you can ensure your data is error-free and easily interpreted.
• CRM data cleaning: Data cleaning, also known as data scrubbing, is the process of modifying or removing customer data that isn’t needed. This includes data that is inaccurate, outdated, duplicated, corrupted, or inconsistently formatted.
• Data governance: Data governance is the process of setting up internal standards and policies concerning customer data collection and storage. These standards help you manage how the data in your CRM is collected, stored, analyzed, and deleted.

Learn more about CRM data quality and accuracy:

• Ensuring data quality and accuracy in CRM software