In modern day business scenario, strategic decision making in the field of marketing largely depends on quality and amount of customer data collected through various online and off-line survey exercises. Due to internet explosion and rapid mobile penetration, more and more people are nowadays resorting to online purchase. Various online as well as mobile portals offer innumerable products which could be selected and purchased through online mode. Detail information of each online purchase can be recorded and collected using web robots/web-spiders and stored in huge databases for further processing.
Apart from this, the online behavior of customers can also be tracked and their likes/dislikes regarding any particular item can be guessed from their online history. The social networking platforms such as Facebook, Twitter, LinkedIn, Google+, Pinterest, Instagram etc. contribute to a large extent in determining the customer acceptance of any newly launched product and influence the strategic marketing decisions considerably. Even various instant messaging sites such as WeChat, WhatsApp , Line etc. can predict the future sales of any freshly launched product. On the other hand, in case of in-store purchase, the POS terminals at billing counters store the details of each purchase which can be collected and used for research purpose. The data collected manually through traditional survey methods are also used along with the data collected through various electronic and online modes as described above.
This vast sea of data collected from both online and offline sources are sorted and stored in huge data repositories called data warehouses. Analyzing the data for extracting relevant business information that will help in strategic decision making is not an easy task. Business intelligence offers techniques by which proper analysis can be performed on raw field data in such a manner that useful patterns will emerge out of seemingly disjoint sets of customer data. Data mining is one such technique that utilizes pattern recognition method to dig out useful product or market related information that helps in strategic planning and decision making. Various statistical analysis techniques such as predictive analysis, cluster analysis, regression analysis, time series analysis etc. are also performed in order to extract meaningful and structured information out of unstructured raw warehouse data.
The analyzed data is further processed using OLAP (Online Analytical Processing) tools and beautiful tables and charts are created out of the analyzed data. Thus business intelligence presents structured information in the form of attractive and informative tables and charts so that managers can instantly realize and recognize the information that were so far hidden among thousands of irrelevant data. The real importance of business intelligence is, it instantly presents extremely important and to-the-point information at the fingertips which was impossible to extract otherwise. Thus BI helps business leaders in taking right decisions at right moment and helps in formulating business strategies to a great extent.