Today, people have access to more data they can process and understand by using the conventional ways. It’s not a matter of intelligence but a matter of sorting XXX XXXXXXXXX. XXXXXXXXX a XXXXXX XXXX with a search XXXXXX will XXXXXXXX million of results, XXXXXXXX or not for the XXXXXX. Enterprises XXX XXXXXXX with XXX same XXXXX. Companies XXXXXXX, sort and store XXXX XXXX that XXXX will ever XXX (XXX, Lau, Zhao, 2015). This data is called “XXX data” and it’s characterized by three XXXX XXXXXXXXXXXXXXX: a bigger volume XXXX XXX XXXXXXX can XXXXXX, a XXXXXX XXXXXXXXXX XXXXX XXXX companies XXX follow XXX a XXXXXXX XXXXXXX the company really needs for taking its decisions (Fan, et XX, 2015). XXXXXXX that big XXXXX more than the XXXXXXX XXXXXXXXXX XXXXXXXX, companies XXX XXXXXXXXXX new tools XX XXXX XXX collected XXXXXXXXXXX and search XXX XXXXXXXXX for XXXX’s XXXXXX relevant. XXXXX, XXX XXXXXXX retailer in the XXXXXX XXXXXXX, managed XX shape XXX entire marketing XXXXXXXX in the last decade XX collecting data XXXXXXXXX XXXXXXXX XXXXXXXX from XXXX 40% of XXX British XXXXXXXXXX (XXXX-Baquero, Colomo Palacios, XXXXXXXXX, Molloy, XXXX). Tesco XXXXXXXX XXXX about XXXXXXXX XXXXXXXX patterns XXXX the XXXXX Club loyalty card XXXXX. XXXXXXXXX XXX XXXXXXXXXX XX use the XXXX XXXX small incentives XXX shopping discounts. XXXX is a XXXXX XXXX “XXX XXXX” can XXXX a strong business impact. This XX relevant because XX knowing XXXX XXX XXXX customers XXXX, XXXXX XXX segment XXX market XXXX precisely, XXXXXXX an XXXXXXXX merchandise stock management XXX work closer XXXX XXX suppliers XX offering XXX products customers expect. “XXX data” XX XXXXXXXX the XXX XXXXXXXXX XXXXXX and XXXXXXXXX XXXXX marketing strategies (XXX, et XX, 2015). While XXX companies have the infrastructure and tools to collect “XXX data”, small XXXXXXXXX must XXXXXXXXXX XX XXXXXXXXXX XXX improving the XXXXX XXXX XXX XXXXXXX XXX understanding the XXXXXXXXXXX. Smaller XXXXXXXXX now have XXXXX own XXXXXXX XXXX XXX XXXXXXXXXX marketing XXXXXXXXXXX about XXXXX customers. The XXX XXXXXXXX XXX relevant XXXXXXX XXXX demonstrate XXXX “big XXXX” is XXXXXXXX XXX XXXXXXXXXXXX marketing strategies, XXXXXXXXX XXXXXXXX examples proving this XXXXXXXXX.
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XXX, S., XXX, X. X. K., &XXX; Zhao, X. X. (2015). XXXXXXXXXXXX XXX data analytics for XXXXXXXX intelligence through the XXXX of marketing XXX. Big XXXX XXXXXXXX,doi:XX.1016/X.bdr.2015.XX.006
Vera-XXXXXXX, A., Colomo Palacios, R., Stantchev, X., & XXXXXX, O. (XXXX). XXXXXXXXXX XXX-XXXX for XXXXXXXX process analytics. XXX Learning Organization, 22(X), 215–228. XXX:XX.1108/XXX-05-2014-0023
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