Businesses collect data for various uses. As technologies that capture and analyse data multiply, businesses’ abilities to contextualise and draw new insights also evolve. Nowadays, artificial intelligence is a crucial tool that’s used for data capture, analysis, and collection of data that are used for different purposes.
In countries like Singapore, certifications like the Data Protection Trustmark (DPTM) are created to help organisations create accountable and responsible data protection practices. Those who want to get certified can also make use of DPTM consultancy for help with policies, data breach management plans, and impact assessments.
With a DPTM consultancy, organisations can also get help with staff training so they are educated on PDPA and DPTM requirements. For those who are not aware, below are some of the ways consumer data is captured and what happens to the information in the organisation.
Different Types of Consumer Data Collected
The consumer data businesses collect can be classified into four categories:
- Personal Data. This includes personally identifiable information like gender and social security number. It also includes non personally identifiable information including the web browser cookies, device IDs and the IP address.
- Engagement Data. This kind of data details how the consumers interact with the website, print ads, customer service routes, social media pages, emails, and mobile apps of the business.
- Behavioral Data. This category involves transactional details like the product usage information, qualitative data, and purchase histories.
- Attitudinal Data. This type includes metrics on purchase criteria, product desirability, and consumer satisfaction.
How Businesses Use Data
There are many ways businesses use consumer data they have collected. Below are some of the ways data are used.
To enhance the customer experience.
For many companies, consumer data provides a better way to understand what customers want and meet them. By analysing feedback and reviews as well as customer behavior, companies can easily modify their goods, services, and digital presence to better suit the present marketplace.
To refine the marketing strategy of the company.
Contextualised data can help companies better understand how consumers are engaging and responding to their marketing campaigns and can adjust them accordingly. The highly predictive use cases can also help give them an idea of what consumers want based on what they have done.
To transform data into cash flow.
Companies that capture data can also profit from it. Data service providers that sell and buy information on customers have risen as a new industry together with big data. For advertisers, having data available for purchase is immensely valuable so the demand for more data has increased dramatically.
To collect more data.
Some businesses use consumer data to secure more sensitive information. For instance, banking institutions sometimes use voice recognition data so users can access their personal information. It can also be used to protect users from fraudulent attempts to access and steal their information.
As data analytics and capture technologies become more sophisticated, companies will find more ways to contextualise and collect data including consumers. This is essential to stay competitive well into the future. Nowadays, insight is king and insight in today’s modern business environment is obtained from contextualised data.