Computers, however, sift through this data more quickly and efficiently than humans, and they can operate 24/7/365 without taking a break.Īs machine learning algorithms and other forms of AI proliferate and improve, data analytics becomes an even more powerful field for breaking down the sea of data into manageable tidbits of actionable insights. No human can reasonably sit down and read through line after line of customer data all day long, and even if they could, they probably wouldn’t make much of a dent. Turning data into knowledgeĬapturing large amounts of data creates the problem of how to sort through and analyze all that information. Once captured, this information regularly changes hands in a data marketplace of its own.Ĭustomer data can be collected in three ways: by directly asking customers, by indirectly tracking customers, and by appending other sources of customer data to your own. Here, they are incorporating direct feedback about what worked and what didn’t, what a customer liked and disliked, on a grand scale.īesides collecting information for business purposes, companies that sell personal information and other data to third-party sources have become commonplace. This information is then used to target users’ devices with hyperpersonalized, relevant advertising.Ĭompanies also dig deep into their customer service records to see how customers have interacted with sales and support departments in the past. One example is location-based advertising, which uses tracking technologies such as an internet-connected device’s IP address (and the other devices it interacts with – your laptop may interact with your mobile device, and vice versa) to build a personalized data profile. The most obvious places are from consumer activity on their websites and social media pages or through customer phone calls and live chats, but there are more interesting methods at work as well. “A robust business strategy needs all three.”īusinesses are adept at pulling in all types of data from nearly every nook and cranny. “Customer data can be collected in three ways: by directly asking customers, by indirectly tracking customers, and by appending other sources of customer data to your own,” said Hanham. The bottom line, though, is that companies are using a cornucopia of collection methods and sources to capture and process customer data on metrics, with interest in types of data ranging from demographic data to behavioral data, said Liam Hanham, data science manager at Workday. Some collection methods are highly technical, while others are more deductive (although these processes often employ sophisticated software). This data type encompasses metrics on consumer satisfaction, purchase criteria, product desirability and more.Ĭompanies capture data in many ways from many sources. This category includes transactional details such as purchase histories, product usage information (e.g., repeated actions) and qualitative data (e.g., mouse movement information). This type of data details how consumers interact with a business’s website, mobile apps, text messages, social media pages, emails, paid ads and customer service routes. This category includes personally identifiable information such as Social Security numbers and gender, as well as nonpersonally identifiable information, including your IP address, web browser cookies and device IDs (which both your laptop and mobile device have). The consumer data that businesses collect break down into four categories: Types of consumer data businesses collect Here’s a look at some of the ways companies capture consumer data, what they do with that information, and how you can use the same techniques for your own business purposes. Some companies have built an entire business model around consumer data, whether they sell personal information to a third party or create targeted ads to promote their products and services. Through consumer behavior and predictive analytics, companies regularly capture, store and analyze large amounts of quantitative and qualitative data on their consumer base every day. This article is for consumers who want to know how businesses use their personal data and how to protect this data.Īs technologies that capture and analyze data proliferate, so do businesses’ abilities to contextualize data and draw new insights from it.Use VPNs, employ ad blockers, avoid linking apps, choose nameworthy apps and sign up for non-essential services with fake information to protect your data.California, Colorado and Virginia have enacted similar laws, though there is no federal equivalent. The European Union’s General Data Protection Requirements (GDPR) is a comprehensive law that regulates any company with EU-based shoppers.They may also sell this data for revenue. Businesses may collect consumer data and use it to power better customer experiences and marketing strategies.
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