by Online shopping behavior is the process by which consumers search for, select, purchase, use, and dispose of goods and services, over the internet. Online shopping has grown in popularity over the years, mainly because people find it convenient and easy to bargain shop from the comfort of their home or office.
There are two different types of perceived risk involved in determining consumer’s behavior during online shopping process. It is further described as the first category of perceived risk involved in online product and service i.e. financial risk, time risk, and product risk while the other category of perceived risk involved in e-transactions including privacy and security). Many researchers argued that perceived risk like financial risk, product risk, non-delivery risk, time risk, privacy risk, information risk, social risk, and personal risk have a negative and significant effect on consumer’s online shopping behavior. Another dimension of consumer’s behavior is trust and security on e-retailers, the positive shopping experience builds consumer’s trust on e-retailers and reduces the perceived risk.
Factors influencing Online Shopping Behavior
Online shopping behavior is a complicated sociotechnical phenomenon and because of this, it has been the focus of many researchers for the last decade. Speculations about the purchasing decisions made by the online shopper are quite vast and this is because it is elusively hard trying to judge the psychological state of consumers while they are making purchases. Due to this hard task of making generalized conclusions, there have been several studies that have come out hypothesizing different factors.
Apart from speculations, previous research has shown that online shopping behavior is affected by demographics, channel knowledge, and shopping orientation. However, there are many other factors that are observable which can lend to having higher transaction rates and having a glimpse into shopping behaviors. Some of these factors are listed below.
Financial Risk:
For online shoppers, financial risk is always a top concern. Financial risk refers to the perception that a certain amount of money that could be lost while making a purchase of goods or services online. The level of perceived risk differs between age groups, however. For instance, millennial are more likely to be less concerned than older generations, whose behavior is more skeptical when making purchases online.
Product Risk:
One of the benefits of shopping in a traditional brick and mortar store is being able to have the product in front of the customer. This allows for the retailer to manage the expectations that a customer has when they are purchasing a product. In e-commerce, online stores try to limit product risk by giving accurate descriptions of products and the ability to zoom in on the product pictures to give the client an accurate expectation of the product.
Delivery:
Another great factor that influences online shopping behavior is the common fear of not receiving products after making a purchase. Potential loss of a delivery is where goods are lost or damaged and this often creates a fear in customers that they would not receive their goods on the agreed time frame that the business stated. Online stores try and manage this perceived risk by easing customer’s minds on shipping and non-delivery by giving accurate updates on when they should expect the product they ordered.
Convenience:
For online shoppers, convenience is the best aspect of shopping online. In comparison to brick-and-mortar stores with fixed hours, online shopping venues are available to shoppers at any time of the day or night. There are also no lines to wait in or cashiers to track down to help purchases, and shopping can be done in minutes. Moreover, online shopping saves customers a lot of time. Instead of having to go out and take extra time shopping for a product, shoppers can save their time and spend it doing things they want to be doing.
Online Shopping Behavior analysis
To better understand online shopping behavior, an analytics tool is required. The goal of any business analytic tool is to analyze customer data and extract actionable and commercially relevant information that can be used to increase results or performance.
An example of an online shopping behavior analytics tool is Google Analytics. The Shopping Behavior Report within the tool allows online businesses to see visitors’ flow through the various stages of the shopping experience, beginning with the total number of sessions for a given date range, and including product views, cart adds, and checkouts.
Another great tool for analyzing online behavior is Eye Tracking technology. Eye Tracking is often used for website testing. It gives insight into how visitors view and experience a website. It helps gives businesses answers to questions such as “How do people attend to adverts, communication, and calls to action (CTAs)?”.
Online Shopping Behavior and facial recognition
With technology constantly evolving, so is the online shopping market. Websites are smarter, shipping is quicker, and expectations are higher. To keep up with the market, online stores have started to gravitate towards artificial intelligence.
Personalization
By analyzing users’ history, online retailers can offer products and services that a customer is more likely to be interested in, all while getting rid of excessive, and most likely unnecessary, options.
To take online shopping personalization one step further, companies are starting to incorporate artificial intelligence (AI) and machine learning (ML) into the e-commerce experience. Facial recognition is a technology that uses AI and ML, helping businesses build a strong sense of loyalty between customers and brands.
By recognizing consumers faces through a webcam, the rest of the shopping experience can be customized to match their past needs and purchases.
