These patterns and trends are of interest to companies, governments, and not-for-profit organizations, as these organizations can use these patterns and trends to design their strategies or introduce new programs, new products, processes, or services.

Through social media data mining and analytics, you can harness the power that social media data brings to your business. As social media grows ever more popular in being part of business and marketing strategies, AACS Consulting data mining techniques allow clients to find new insights about their organization’s status in the media. Moreover, it can guide organizations in personalizing services for their customers. Here are some examples of data mining techniques used by AACS Consulting:

• Classification: This technique requires collecting various attributes in a data set and combine them into discernible categories. AACS Consulting then gives clients insights and concludes the generated classifications of the data attributes.
• Tracking patterns: Tracking patterns is a data mining technique that specifically identifies the rules and trends in the data based on their relational attributes. This technique involves the identification of anomalies present in the data at regular intervals. It can also point out the ebb and flow of a particular variable in a data set. For instance, when determining which seasons a specific product is most widely sought by the customers, this technique comes very handily.
• Prediction: The prediction technique in social data mining helps forecast the kinds of data an organization will most likely see in the future. In this technique, trends, patterns, and predictions are obtained and analyzed. Reviewing consumer behavior, for example, can help you expect the future demands of your customers. Most prediction techniques have mathematical models as their basis. These include simple statistical models like regression and non-linear statistics.