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The shopping behavior between men and women is by a big chance driven by the shopping pattern and mentality associated with the two genders. As observed, Envirosell researchers estimated that 65 percent of men bought the jeans they tried on compared to 25 percent of women. This stems from the fact that men are not excellent shoppers and hence they tend to take the shortest time possible when shopping in stores (Underhill, P.,2009). More so, such behavior stems from the fact that men tend to get bored quickly especially when doing shopping hence they do not take up much of their time in the stores. On the other hand, men tend to visit stores with a fixated mind on what they are going to acquire in the stores thus they are less likely to do impulse buying, mostly associated with women. Therefore, when men try on jeans and they find fit, they tend to buy them to get over the shopping time as quickly as possible.
Similarly, according to Underhill, P. (2009), more browsers are likely to buy computers after 5 pm than in the morning. In such an observation this trend is more psychological than an established pattern. It is important to realize that during morning hours more people are interested in similarity as compared to evening hours when people want stimulation. Therefore their shopping decision is to a large extent influenced by the feeling of that new device or an item they unleash in the evening after a long day hence the eagerness and excitement accompanying such a decision as compared to acquiring such an item in the morning hours. More so such buying may be influenced by events such as a celebration, as a gift, or also as an upgrade of an existing computer thus observing such events tends to take place from evening hours.
According to Gladwell, M. (1996). To improve the statistics which are very crucial to business survival and profitability, it is important to invest more in facilities within the stores that are likely to attract and catch the eyes of men. According to De Montjoye, et. al.,(2015)., in a resting bench especially for men, stores can take advantage of such spaces to introduce to men products they are likely to take notice of. More so in such areas, they can put product-themed magazines that are likely to attract the attention of these men and invoke their urge to find out more in the said sections. Such moves are likely to improve if not soar the statistics of these stores.
In a recent visit to a store, after time spent in the store, I happened to leave without doing any shopping, the main aim of the visit was to do browse shopping. I was checking out if there were any new products of interest that the store had introduced. More so I was checking for any improvement in the store setup as well as the layout of the different products in the store and how the sections were labeled. From the parking lot, there were bold labels on the new product and the discounts being offered on more popular brands associated with the store to a large extent these signs had a striking effect. The parking lot at the store is strategically positioned such that it is almost impossible to ignore the witty adverts employed by the storefront.
On visiting a small grocery store, there happened to be an established pattern by the customers. Most customers when they accessed the store tended to move straight to the freezer section where most of the vegetables were placed which is direct from the entrance. Then all of a sudden there was this peculiar habit with the customers, on reaching this section they turned back again to the left side where the fresh vegetable section was stationed. From this observation, it was evident that customers were more inclined to buy freshly procured vegetables as compared to those that had been in the freezer for some time.
According to Baye et. al., (2018), the conversion rate, which shows the number of customers at a store and those who buy something was observed to vary depending on the time of the day. During that time I stood at the entrance. During the morning hours, the conversion rate observed was low, which was expected especially on working days, however, over the weekends, the conversion rate was still the same in similar hours, which was not expected as it was expected that most people shop over the weekends which they have adequate time. In the evening, from 5 pm, a high conversion rate was observed which was not a surprise, with higher rates observed over the weekends as people had more time to spare (Gladwell, M., 1996).
Shoppers Time in store (in minutes) Displays section looked at. Products picked per section Did they read labels Did they check prices? Did they approach a sales rep? Any diff. btw old and young shoppers? Any diff. btw men and women shoppers?
- 20 Men wear 2 yes No. No. Yes Yes
- 40 Grocery 5 No Yes No Yes Yes
- 50 Electronics 1 Yes Yes Yes Yes Yes
- 30 Kids Section 2 No No No yes Yes
- 55 Women Wear 4 Yes Yes No Yes Yes
In the store, the shopping pattern varied mostly depending on age and gender. As observed men were most likely to spend more time on electronics as compared to women. More so in the clothing section, men tend to take less time as compared to women in this section. On the other hand, kids took more time in the kid’s section as compared to other sections. Their chances of checking on the prices were minimal as in most cases their parents paid for the stuff they took interest in. In the grocery section, women took more time there as compared to men. They were more inclined to check the prices of the stuff they shopped for more likely to engage a sales rep as compared to men.
From the outside of the store, the displays and the signs were visible and thus could be read even at a distance. More so they were placed in such a captivating way that they commanded the attention of the passer-by. The window displays were placed in such a way that they formed part of the shopping experience. These signs made it easy for the shoppers to locate the specific stores easily.
References
- Baye, I., von Schlippenbach, V., & Wey, C. (2018). One‐Stop Shopping Behavior, Buyer Power, and Upstream Merger Incentives. The Journal of Industrial Economics, 66(1), 66-94.
- De Montjoye, Y. A., Radaelli, L., & Singh, V. K. (2015). Unique in the shopping mall: On the identifiability of credit card metadata. Science, 347(6221), 536-539.
- Gladwell, M. (1996). The science of shopping. The New Yorker, 4(11), 66-75.
- Underhill, P. (2009). Why we buy: The science of shopping–updated and revised for the Internet, the global consumer, and beyond. Simon and Schuster.
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