5 Uses for Data Mining

Data mining is the process of gathering information and analyzing it for actionable patterns, which can then be used to develop marketing strategies, new products that fit customers’ wants and needs, and cost-saving strategies. Data mining can even ferret out fraud and error-based losses. Used ethically, data mining is an effective tool companies can use to remain viable and relevant in the marketplace. Here are the top five things you can do with data mining:

1. Basket Analysis

This term refers to either the real-world or virtual “shopping basket” that customers will use when purchasing items. The data analyst will look at customers’ preferences and seek to predict future buying trends based on what has already happened. In addition to keeping track of products and services bought, basket analysis is also useful in monitoring payment options and rewards cards.

For example, let’s create a hypothetical shopper named “Sam.” Sam goes to the grocery store and buys items that yield extra points on the store’s rewards program. Sam then pays for his purchases with a credit card. The company can then correlate credit card use with reward program redemptions and stock levels to manage its inventory effectively.

2. Sales Forecasting

Although this is a similar concept to basket analysis, it involves trying to guess when customers will buy certain items again in the future instead of trying to guess what they will buy. For example, if Sam buys a blender that should last three years based on performance reviews, the store from which Sam bought the blender would plan to release similar blenders three years from now so that Sam might buy one from them even if the new blenders aren’t the same brand as Sam’s old one. A store can also look at similar purchases customers make at other stores and tailor its approach to match that of the other stores in an effort to attract future customers.

3. Database Marketing

By means of this data mining strategy, a company can create a line of products and services that sell themselves. Instead of looking at what Sam wants, the company will analyze, through data mining, what 100,000 “Sams” want. In this instance, let’s say Sam is an overweight, 60-year-old Native American. The company will look at the preferences of 60-year-old, overweight Native Americans and create advertising programs that speak to that demographic. Even if one particular “Sam” doesn’t respond to the advertising, the idea is that enough “Sams” will respond to it, which will make the marketing strategy worthwhile to the company.

4. Inventory Planning

This use for data mining easy to understand. If a store has sold at least 2,500 doohickeys during every summer since 2003, then it stands to reason that the store can plan to sell at least 2,500 doohickeys next summer too. It’s also fairly simple to assess increasing or decreasing sales trends on a month-to-month or even week-to-week basis and make well-reasoned decisions about which products to stock that people want to buy.

5. Customer Loyalty

A company can look at data regarding its customers to see how price changes either attract them or send them scurrying to a slew of competitors. This data mining strategy ties in closely with a store’s rewards program.

For example, if Sam has redeemed reward points for his blender, a rice cooker, a trip to Easter Island, and $1,000 in free groceries over the years, it’s safe to say that he’s a loyal customer. The store can plan its offerings around Sam’s preferences and know he’ll keep coming back. It’s not all about price either. By checking out customer loyalty statistics, a company can determine what its customers consider valuable and work toward creating extra value that falls in line with the customers’ preferences irrespective of pricing.

As useful as all of these data mining techniques and the accompanying information being analyzed can be, it’s essential for a business to handle them ethically. Fair use is one thing, but selling the gathered information to scam artists or fraudsters for a profit crosses the line. Besides, should the world at large find out a company has done such a thing, it won’t be hard to track the buying trends of that company as they enter free fall. By being ethical and intelligent with their uses for data mining, a company can maintain its place in the world market.