Data mining can bring enormous value to organizations that do it well, but how it’s done—and how it is received—is changing as a result of evolving technologies, consumer data concerns, and some public malpractice. Here are the trends driving enterprise data mining efforts in late 2023 that organizations need to be aware of when planning their own data mining strategies.
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Table of Contents
Using Generative AI to Extract and Mine Data
Generative artificial intelligence (AI) tools like ChatGPT have changed the technology landscape in the past year. These tools can summarize materials at a larger scale and greater speed than can be done manually or using conventional means, making it easier to extract relevant information. A number of vendors have already released data mining plugins for generative AI products that significantly reduce the time and effort involved.
As a real-world example, employees at an insurance company fed claims data into ChatGPT to help find the most common reasons for losses to improve its underwriting. The company said it believes this approach will help it stay competitive against bigger and better-funded competitors in an increasingly challenging market.
However, there’s risk involved in using generative AI tools for data mining. By default, these tools allow all user-inputted data to be used to train future versions of the product’s algorithms, which is problematic if sensitive material is used. Organizations considering using generative AI for data mining should be sure they’ve changed the default settings or opted out of relevant usage policies.
Learn more about data mining and how it works.
Finding Ways to Overcome Customer Data Concerns
Generally speaking, customers give their data to companies in exchange for perks—this is how customer loyalty programs work, for example. But as data mining techniques continue to advance, some people are beginning to consider them intrusive and people are growing increasingly concerned about what happens to the information they agree to share and whether the companies will handle it responsibly.
In one 2023 survey, 74 percent of American respondents said they believed there was nothing they could do to prevent privacy intrusions. Another revealed that 58 percent of people worried about organizations or individuals tracking them through their devices. These statistics strongly suggest people are not as open to data mining as companies might hope.
It’s not too late for businesses to regain trust by proving they can use data in mutually beneficial and responsible ways. For example, they might include easy-to-understand data-usage policies on their websites that give customers straightforward ways to request all the information the company has on them, or to ask for it to be deleted. Being transparent as possible about what data you collect and why could go a long way toward putting customers at ease.
Balancing Product Personalization and Customer Rights
Enterprises that collect and use customer data to personalize products and features—smart TVs, digital assistants, need to find the balance between feature personalization and privacy to engage and retain customers. A good example of this is the auto industry.
Modern automobiles are increasingly high-tech, personalizing the driving experience based on owner preferences and using technology to control entertainment, cabin environment, navigation, and more. While the shift toward increased information retention might keep people safer—many new cars have features that detect tired or distracted drivers, lane changes, and objects in blind spots, for example—it also relies upon collecting and retaining a ton of information about drivers and owners.
And there’s some concern about how automakers handle that information. A recent investigation showed automakers have significant room to improve on privacy issues—all 25 car brands in the analysis collected too much data, 84 percent of them sold or shared user data, and only two allowed car owners to request their data be deleted. Cars provide abundant data-mining opportunities, but people may be willing to opt for less advanced features in exchange for more privacy.
Tech Companies Partnering with the Military
The military uses data mining for a number of applications, and recently has begun combining it with other technologies like machine learning (ML) to make recruitment, battlefield missions, and veteran care more effective. In combination, the military can better use existing data by analyzing it to make smarter decisions.
A tech company called Scale, founded by two friends who were beginning to see the possibilities of AI, specializes in enabling clients to work with and label data used for AI algorithms with the military as its target audience. Data labeling is a critical step for well-trained algorithms—data annotation tasks submitted to the Scale platform are labeled by proprietary ML models for a more reliable result than manual human labeling.
As defense leaders become increasingly interested in data mining, Scale and other companies will continue finding new ways to use technology to expand the scope and increase the efficiency of their efforts. By reducing the time it takes to analyze massive datasets for valuable information, technology may be able to give the military the competitive edge it seeks.
Scammers Mining Data through Social Media Quizzes
As people get wiser about cybersecurity scams, cybercriminals are getting more creative about their methods—and there’s a growing risk of hackers exploiting data mining for malicious purposes. The FBI recently highlighted social media quizzes being used to collect information that scammers can use to break into users’ accounts.
For example, a quiz might ask users to “Combine the name of the street you grew up on with the model of the first car you owned—the answer is your rock band name,” in the process learning the answers to the security questions people use to safeguard new accounts. Some scams prey on the unhappy—”Provide the last three digits of your phone number to learn what you need to be happy or successful,” for example—while others promise nonexistent jobs in exchange for Social Security numbers or bank details.
As people grow more leery of providing data voluntarily, businesses should exercise caution about what they expect people to share with them and how they ask for it. While quizzes and surveys can be fun ways to engage customers, they should be transparent about how they plan to use the information they collect using them.
Data mining can help businesses with everything from customer engagement to product design, and new technologies bring new approaches and abilities to gathering the information that feeds those data mining efforts. However, anyone who handles data must do so responsibly, with full awareness of the consequences for mishandling customer information.
Read 10 Best Data Mining Tools for 2023 to learn about the software organizations are using to gather and analyze data.