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TopIntroduction To Purchasing History
Consumer purchasing behavior can be studied and targeted via direct mail or other forms of marketing by many industries (Gheisari et al. 2021), such as supermarkets, airlines, and credit card companies, which have built extensive databases of individual consumer transactions for this purpose (Abdel-Basset et al. 2018). Many businesses have honed their marketing strategy with advanced analytics (Liu et al. 2015). Because several transactions are now computer-mediated and these processors can readily be interconnected to data centers, retailers may now access databases of purchase histories in real-time (Abou-Nassar et al. 2020). Using such information, they can target customers based on what they have previously purchased (Kuthadi et al. 2021). Vendors can charge a different price for each customer, give them a special gift and voucher, or provide customized recommendations (Amudha et al. 2021). Individual pricing discrimination becomes possible with computer-mediated transactions (Singh et al. 2021). It is much easier to gather and analyze data because everything is done online (Gao et al. 2020). The HTTP protocol permits web servers to store transaction information or unique identifiers in cookies (Abdel-Basset et al. 2020).
These cookies remain on the user's computer even after the session has finished (Le et al. 2020), allowing an overall server to match the user's identity with previous interactions the next time the user enters the server (Abou-Nassar et al. 2020). Over time, information systems have progressed from being simple systems for documenting transactions to being sophisticated tools for making corporate choices at all levels (MeenaakshiSundhari et al. 2020). For making business choices, conventional data systems relied heavily on internal information sources like enterprise resource planning systems (ERPs) (Gao et al. 2020). In order to make sound business choices, companies often rely on information that can only be found inside the walls of the organisation. Sales, finance, marketing, and human resources are all areas in which a corporation can collect internal data for its own benefit. Customers' purchases are tracked in order to calculate revenue and profit. These datasets were formatted and managed using a relational database management system (RDBMS) (Amudha et al. 2018). These were implemented to enhance internal business choices, such as inventory control, price decisions, identifying the most valued customers, and identifying loss-making products (Rao et al. 2019).
Furthermore, data warehouses were created with this information for analysis and processing (Verma et al. 2019). Enterprise application integration (EAI) solutions combined these data sources with data from business parties like suppliers and consumers (Wu et al. 2019). For the last fifteen years, most commodities have been purchased at physical establishments such as groceries, boutiques, etc., (Yassine et al. 2019). Purchase power was minimal, and clients often lacked sufficient product information at that time (Ghasemaghaei et al. 2019). Their purchasing habits were heavily influenced by their way of life and the businesses in their neighborhoods (Yoseph et al. 2020).