Customer data

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Customer data or consumer data refers to all personal, behavioural, and demographic data that is collected by marketing companies and departments from their customer base.^[1] To some extent, data collection from customers intrudes into customer privacy, the exact limits to the type and amount of data collected need to be regulated.^[2][3] The data collected is processed in customer analytics. The data collection is thus aimed at insights into customer behaviour (buying decisions, etc.) and, eventually, profit maximization by consolidation and expansion of the customer base.^[4]

In the internet age, a prominent method for collecting customer data is through explicit online surveys,^[5] but also through concealed methods like measurement of click-through and abandonment rates.^{[citation needed]}

Online surveys are a direct approach, allowing companies to gather detailed customer insights by asking specific questions. This method provides qualitative data, which can be analyzed to understand customer preferences, opinions, and behaviors.

Measurement of click-through rates (CTR) is another vital method. CTR measures how often people who see an online ad or link end up clicking on it. This metric helps companies assess the effectiveness of their marketing campaigns and understand what attracts their audience's attention.

Abandonment rates measure how often users leave a website or an online process before completing their intended action, such as filling out a form or making a purchase. High abandonment rates can indicate problems with website usability or the customer journey, providing valuable data for improving user experience and increasing conversions.

Together, these methods offer a comprehensive view of customer behavior and preferences, enabling businesses to make data-driven decisions and enhance their marketing strategies.

Customer data is gathered for customer research, especially customer satisfaction research and purportedly serves to increase overall customer satisfaction.^[6]

A possible classification of business customer information was proposed by Minna J. Rollins, who distinguished the levels a) market b) organizational c) business unit, and d) individual.^[7] For private consumers, different levels are a) personal identifying data b) psychographics data, c) transactional (buying) data, d) demographic, and e) financial data.^[6] While the individual data level for business customers has some overlap with the data gathered from individual consumers, the other business-related levels roughly correspond to the demographic part of individual customers.^[8]

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