Businesses and organizations across the private and public sectors rely heavily on the use of data analytics to provide valuable and effective products and services to customers. Optimizing the customer experience now depends on a business’ ability to process a vast and growing volume of consumer information. However, the sheer amount of data can be overwhelming or have little utility if the data are “thin”—that is, lacking critical context or failing to capture deeper consumer insights.
Relying on basic data analytics that use big data technologies to glean consumer insights is no longer sufficient for businesses seeking truly reliable insight. For instance, most data-driven analytics rely on sheer volume and repetition of key words that is easily hacked. Big data enables computational analyses and predictive analytics that exponentially exceed human cognition, but they do not diminish or negate the role of human observation and immersion in social settings.
“Big” Data vs. “Thick” Data
Big Data refers to large data sets that reveal patterns, trends, and associations when analyzed. However, due to their complexity, big data can be difficult to store, analyze and visualize. Big Data are typically derived from technologies that automatically generate large data sets, collected by various sensors and mobile devices across platforms and physical locations.
Big Data enables a company to see patterns and identify anomalies with far greater speed and accuracy. It is even used to help public policy experts write more informed recommendations in areas ranging from social services to global health threats. But Big Data is collected at such a large scale, and growing exponentially with each passing year, that an increasing number of data processing platforms are no longer capable of capturing, storing, and analyzing it. While Big Data has been the source of significant advances, by its very nature it does not capture deep context about the people and places that benefit from actions taken based on analysis of Big Data.
Generating insight requires sound techniques to measure consumer engagement more precisely and offer depth analytics to the consumer data story. Anthropologists, sociologists, and human geographers, among others, generate highly contextualized and nuanced data, referred to as Thick Data. Thick Data can complement, refine, and calibrate Big Data insights.
Thick Data provides nuanced and contextualized information that can be filtered to enhance the relevancy for a business, particularly in societies, localities, and demographic groups that are not adequately captured or examined by the practices typically associated with Big Data.
Utilizing Thick Data
While Big Data are broad and thin, Thick Data are narrow and rich. Therefore it stands to reason that blending them can yield a more holistic picture of a business’ target consumer population. Mixed Analytics can help improve the decision-making driving nearly every aspect of a business. The value of blending to the two approaches is readily evident on the individual level: If you’re trying to make important decisions about your health, wealth or happiness, quantitative data is rarely enough. The things that ultimately figure most prominently in a person’s private decision-making process–such as values and emotions–cannot be precisely measured. Thick Data aims to build empathy and understanding of humans between data points. By yielding personal insights into what customers really care about and how they consume services, Thick Data can inform both the collection and analysis of Big Data.
Age Verification and “Thick” Data
Thick Data aims to uncover people’s emotions, stories, and models of the world they live in, providing unique perspective, meaning, and personal insight into individual consumers. Thick Data can influence business decisions by building customer empathy. While Bag Data and Thick Data produce different types of insights, they do complement each other.
However, employing the insights of Thick Data only works if you can match the results to actual customers–apples to apples. By implementing digital identity and age verification connected to a government-issued ID and other verifiable personal information, businesses can confirm users are who they claim to be, regulate age-restricted content, and protect unauthorized users from accessing products and services or committing fraud.
Without Thick Data insights, businesses are forced to guess what matters most to their customers. The over-reliance on mountains of thin data inevitably will lead to erroneous conclusions.
Build the Right Solution
Integrity by Aristotle makes it easy for businesses to pair quantitative data with qualitative insights, so they can better understand what their customers ’wants and why. By giving your business access to richer qualitative data, Integrity can help your business develop deeper customer empathy which translates directly into an improved customer experience and stronger bottom line. Contact us today to learn how we can help you leverage Thick Data in your customer analytics.
Aristotle’s SVP of Business Development, Michael Bolcerek will be attending Money2020 Europe from June 7th – June 9th 2022 in Amsterdam. If you are interested in meeting in person, please email [email protected] to arrange for an appointment.