Information gathering, or data mining, involves collecting and analyzing large amounts of information using computers. It is useful for marketers, researchers, and other professionals to identify trends and relationships in data. It can also be used for forecasting future performance and spotting industry or national trends.
Information gathering, better known in some industries as data mining, is a method of collecting and qualifying large amounts of both paper and digitized information. A large part of intelligence gathering lies in data analysis. By collecting, categorizing and summarizing information, users can determine relationships and trends that might otherwise go unnoticed. Such information is useful to marketers, researchers, retail store owners, market analysts, accounting professionals, and many other professionals, business entities, and statisticians.
Computers are essential for gathering information. Mining large volumes of data from customer records, online databases or international retail records could take years to collect, summarize and classify on paper. Data mining software products and other methods of incorporating automated sorting using a computer allow for faster and more accurate processing of large volumes of information. For example, automated information collection can track, sort and summarize the shopping habits of hundreds of thousands of customers at various national retail stores in moments.
Business studies and marketing strategy development are the two most common uses of information gathering technology. For example, a university or government agency could collect and aggregate thousands of bits of information about specific industries, such as manufacturing. Using intelligence gathering technology, research teams can pinpoint economic trends such as average commodity prices, increases in the production of certain products, historical data on production times, or even trends in the imports and exports of specific goods.
Marketers and retailers use data mining and other information gathering methods to spot trends in buying habits, cost of goods sold, and inventory levels, to name just a few uses. Specific information, such as the day of the week most men shop, or the number of times the average household frequents a local grocery store, can provide valuable insights to store owners and marketers. Based on this type of information, you can develop and plan sales events, customer reward programs, and pricing strategies to maximize effectiveness and success.
Identifying trends and patterns within large volumes of information, as well as establishing relationships between disparate data, helps compile meaningful historical data for use in forecasting future performance. Transactional data, such as computerized sales records or accounting information, is a commonly used data type for intelligence gathering when applied to an individual business. Industry data, such as industry-level sales, local market forecasts, and raw material purchases, are all types of data used for large-scale intelligence gathering. Typically, large-scale data mining projects are performed by financial or economic analysts to spot industry or national trends.
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