2023 The retailing environment is influenced by many factors including consumer preferences the | Assignments Online

The retailing environment is influenced by many factors, including consumer preferences, the state of the economy, current fashion trends, popular culture, and the retailer’s store image.

Think back to all the topics that have been covered during this course (e.g., consumer behavior, fashion forecasting). Identify a specific merchandise category (e.g., consumer electronics, apparel, home furnishings) and discuss how the current economic, societal, and/or technological environment can affect the successful sale of this merchandise category. Consider each factor and choose one that you believe will have more impact than the others. Discuss your answer in detail.

Reference:

Technology and Fashion Merchandising

Retailers use information systems in the form of registers to organize all the data (e.g., sales, inventory, and consumer information) they collect during each business day. Software programs help make sense of data and provide the merchandise buyer with valuable information regarding sales performance for a specific brand or classification, or for price points, consumer preferences, and purchasing patterns (Frings, 2008). In today’s retailing environment, computers have become the standard device for collecting, storing, and maintaining the retailer’s data. Computerized point-of-sale (POS) registers and universal product codes (UPC) placed on merchandise provide a wealth of information that the merchandise buyer can use to identify slow sellers, the sales that were generated from each classification, and consumer and vendor data.

Within the retailing environment, the following technological advancements have been widely used for inventory and sales tracking:

• POS register: This is a computerized cash register that uses a scanner to read the UPC attached to the retailer’s merchandise. Any transactions that are recorded by the POS register are then transferred to the retailer’s and vendor’s data systems using electronic data exchange (Kunz, 2005).
• Universal product code: This is a code that contains a large amount of information about an item, but it is stored using a small amount of space (e.g., computer/register memory) (Fiorito & Gable, 2012).

Several innovative strategies that are facilitated through technology have been introduced to the fashion industry and have enabled the merchandise buyer to work efficiently by keeping more accurate records of inventory, sales, and distribution data. These include: 

• Quick response: This strategy attempts to minimize the time between the production of merchandise and its distribution to the retailer. The implementation of computer technology is the means by which this strategy is successful (Kunz, 2005).
• Collaborative planning, forecasting, and replenishment (CPFR): This strategy is used collectively by merchandise buyers and vendors to make decisions regarding what merchandise styles to order, when to distribute the merchandise, and when to replenish the merchandise (Fiorito & Gable, 2012).
• Electronic data exchange: This strategy allows retailers and buyers to exchange information (e.g., merchandise orders and returns) by means of computers, which reduces lead-time for merchandise ordering and distribution (Frings, 2008).

Innovations in technology allow retailers and vendors to work together to meet the needs of consumers. In addition to technology being a great facilitator of business-to-business communications, it is also used by retailers to develop consumer databases. Retailers use their computerized POS registers to collect information about their consumers (e.g., demographic information, average purchase amount, form of payment, and merchandise returns) that is used to make more effective marketing strategies. Data mining is an example of how retailers make meaningful inferences from the data they collect. With data mining, a computer is used to analyze consumer data. The retailer uses the data to identity consumer patterns. For example, data mining could provide insight on how to target consumers to buy more merchandise when the retailer has a sale (Fiorito & Gable, 2012).

The information that retailers collect from consumers through the POS register allows them to analyze the information to gain a better understanding of their consumers. This strengthens their relationship and allows retailers to offer consumers merchandise that they desire in an appealing shopping environment.

References

Fiorito, S., & Gable, M. (2012). Retail buying: Practices and policies in a global economy. Upper Saddle River, NJ: Prentice Hall.

Frings, G. (2008). Fashion: From concept to consumer (9th ed.). Upper Saddle River, NJ: Prentice Hall.

Kunz, G. (2005). Merchandising: Theory, principles, and practice (2nd ed.). New York, NY: Fairchild Publications.