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DETROIT Data mining is an often misunderstood term. Consumers hear it and they think privacy violation. Small businesses hear it and assume its only a luxury of Fortune 500 companies. In fact, neither assumption is strictly accurate. Appropriately sourced data mining can be ethical and safe for consumers and businesses alike.

And, even modest-sized companies use data mining to their advantage with the right tools and understanding.

In this article, we take a look at some of the many benefits of data mining and reflect on how your business can use it advantageously.

Data mining is the process of extracting insights from long string forms of informationusually done by identifying and interpreting patterns within the information set. Its a process that typically involves a combination of machine learning and human-driven interpretation, all combined to deliver actionable insights for business professionals.

The data sets themselves can be generated by a wide variety of sources, including internal data, and even customer surveys. While often seen as a practice exclusive to large businesses, with the proliferation of data technology, as well as the ever-increasing number of professionals with master degrees in data science, the practice has become more democratized than ever before.

Data mining helps businesses better understand their customers by extracting granular insights into their buying and product usage habits. This information is key when it comes to forming closer relationships with customers but it can also be used from a marketing perspective.

Marketers with reliable data access are not only able to enjoy customized marketing campaigns based on the specific interests of their customers, but they can also determine how and when to implement those insights.

For example, data mining might inform a business of how and when their customer base is most active on social media. With this information, they can make very specific ads on Twitter or Facebook cater precisely to their demographic.

If their customer base consists primarily of teenagers, they may target ads for the middle of the day, during school lunch breaks. Or, late afternoon, for when students get out of school.

If, on the other hand, the demographic consists mostly of business people, the ads might get posted around 7 PM when adults are most likely to be on social media.

Data mining also always you to make calculated adjustments to your product. By extracting information directly from customers who have used what you are setting, its easy to get a clear idea of what people like, and what they dont use as much.

For example, software companies update their products every several years. Though they are usually selling different versions of the same product, features are routinely tweaked to increase marketability.

This might mean tweaking features to make them more in line with what consumers are looking for. It might also mean adjusting how they describe their product, fixing ad language to make it more compatible with how consumers think of the software.

Looking at historic customer data, consumers can anticipate future product demand, using projections to accurately predict incoming revenue for a fiscal period. While is no crystal ball, it is accurate enough for businesses to make reasonable adjustments to their spending habits, equipping them to buckle down in lean periods or get aggressive with their investments during times where the cash is flowing.

Mined data can reveal two important customer insights.

Customer service has become very personalized. Nearly 80% of consumers expect this personal touch when dealing with businesses. Data mining helps you provide it, increasing profitability and making your customers happier with one move.

Data mining can also help your business recognize fraud by identifying abnormalities within patterns, and flagging unusual activity. While not a catch-all, data can help differentiate between legitimate transactions and ones that might not be.

The more transactions an algorithm can analyze, the better it gets at detecting fraud, meaning that theoretically, businesses that use data mining will be less susceptible to fraud as time goes on.

Data mining does come with its drawbacks. Most notably, complexity. Interpreting large sets of data is difficult, both as a practice and because of the technology it requires. For true data mining success, businesses must consider the services of a data professional.

Scalability is another issue. The tools required to do data mining impactfully are complicated, necessitating large databases that can be difficult for the layperson to manage.

Its also worth keeping in mind that data mining practices have been the source of some controversy amongst consumers. Though the information that is involved in data mining is typically anonymous (X customers like banana smoothies, not Sally likes banana smoothies) they can still generate bad pressparticularly in instances where that data has been sold.

Addressing the former concern is mostly a matter of hiring the right people and using the right tools while taking care of the latter can be solved with transparency. Handle data responsibly with the respect and attentiveness it requires, and there wont be any issues.

Bio: Ryan Ayers has consulted a number of Fortune 500 companies within multiple industries including information technology and big data. After earning his MBA in 2010, Ayers also began working with start-up companies and aspiring entrepreneurs, with a keen focus on data collection and analysis.

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How Data Mining Can Positively Impact Your Business - mitechnews.com