Defining Big Data

The literature gives a few meanings of big data (De Mauro et al., 2015; McAffe et al., 2012; Popovič et al., 2018; Provost and Fawcett, 2013). They can be characterized as organized information like authoritative data sets, and unstructured information created by new correspondence advances like the IoT, just as pictures, recordings, sound. These IoT gadgets―regardless of whether they are cell phones, online purchases, interpersonal organizations, electronic correspondences, GPS, or hardware―create deluges of information by interfacing with and observing individuals. In other words, enormous information is only the acknowledgment that buyers are currently generators of both customary and unstructured information (Erevelles et al., 2007). By utilizing the information created by IoT and big data, organizations can settle on more viable choices (McAfee et al., 2012).

Define Consumers in Big Data

The average shopper has become part of a pattern because of advances in technology, structured, transactional, and contemporary behavior (McAfee et al., 2012). Data diversity, as well as high-speed continuous data generation, are transforming marketing decision-making. Quantity, velocity, and variation are the three dimensions that make up big data (IBM, 2012; Lycett, 2013; Oracle, 2012).

Volume

The size of data is measured in petabytes, exabytes, or zettabytes. Walmart is estimated to generate 2.5 petabytes of hourly shopper data; one petabyte is the same as 20 million standard filing text cabinets (McAfee et al., 2012). As the information index grows in scale, this metric will become obsolete. Likewise, in 2013, the advanced universe was estimated to be 4.4 zettabytes (1 zettabyte is equivalent to 250 billion DVDs) (Cisco 2014). The advanced universe must be 44 zettabytes in volume. In this case, the organization endeavors to control the expanding difficulties. On the global demand for programs, software, and administration in storage, data investigations are projected to double every few years (IDC, 2014).

Velocity

This is the subsequent key component of huge information (Lycett, 2013) or uninterrupted data generation speed. Marketing executives with admittance to rich, perceptive, and up-to-date data can improve choices dependent on proof at some random time, not on instinct or lab-based buyer research. There is a big discrepancy between the United States statistical records and the patron information received with the help of a main girls’ clothing company whose advertising heads are continuously aware of the variation in consumer exchanges and what customers do within the interpersonal commercial enterprise. Both types of statistics are detailed, well-sized, and informative. Only the latter, however, equips marketing executives with the tools they need to make new, evidence-based decisions in the face of competition; big data insights will be difficult to compare.

Variety

Several big data sources provide variations where the transition from organized transactional data to unstructured behavioral data is the main difference between contemporary and conventional big data (Integreon Insight, 2012). Marketers have been collecting structured data (scanner or sensor data, documents, files, and databases) for a long time. Textual (blogs and text messages) and nontextual data are examples of unstructured data (videos, images, and audio recordings).

Individuals exchange personal and behavioral information with friends and family on social media, which generates a lot of unstructured data. Semi-structured data is created by combining various types of software that can organize unstructured data. Standard Generalized Mark-up Language software, for example, allows organizations to identify common elements in instructional videos (e.g., a YouTube video shows people using the product).

Scanning Information on Needs Recognition

It is easy for emotional consumers to drive their purchase wants and demands through information networks. Second, as rational consumers, information-rich service products can better meet their rational assessment needs and reduce information retrieval costs (Cao, 2006).

Scanning Information Against Information Seeking

When making online purchases, consumers often gather information. Online shopping is more energy-efficient and knowledge-based than shopping at conventional stores.

Consumers can benefit greatly from the ability to purchase high-quality and low-cost goods.

Scanning on Alternative Evaluations

The primary decision is based on complete information. Buyers, on the other hand, have limited resources (including time, energy, and money). Consumers want to gather information online quickly and comfortably.

Informed Scanning of Purchasing Decisions

When consumers, who have enough time and comfort to analyze prices, quality, and performance, search for goods on the internet, this becomes important in making purchase decisions.

Information Scanning of Post-Purchase Behavior

Consumers may find fascinating information that they can filter and use systematically to affect their product or service assessment. Then, the effect of the security system on post-purchase actions can be seen in the relationship with the shopping network, where the spacetime blocks allow consumers and producers to share information through network availability.

Delivery of products is usually carried out by the logistics company as a third party. All of this has discouraged consumers from monitoring the efforts of the entire trading process. Consumers have no way of knowing if all confidential data is adequately secured during transmission. This will make customers feel nervous, particularly those who have had problems with shopping security in the past. This is a common reason why people don’t worry about the specific IoT devices they have because they don’t consider the data collected sensitive or accept the effectiveness of protecting themselves from privacy or security-related threats.

Credibility Impact and Security System on Consumer Behavior

The following two things are important and need to be considered:

1. The impact of credibility on consumer behavior

2. Credibility in evaluating options

Previous encounters and relationships with other people have credibility. For both sellers and buyers, knowledge is asymmetrical (Zhao, 2012). When buyers prefer high credit scores and better products, they expect vendors to provide high-quality service.

The Buying Decision’s Credibility

The greatest benefit of online shopping over conventional shopping is cost savings. The use of “big data” technologies allows for the transfer of knowledge at a low cost of operation. This has the important benefit of establishing a reputation.

Post-Purchase Behavior’s Credibility

Consumers will display their good online experience after a purchase if they are satisfied (C. B. Li, 2013). Nevertheless, if customers are disappointed after shopping, they are more likely to express their dissatisfaction on social media, and therefore, many potential customers may lose interest in buying the item.

Information Retrieval on the Security System

With the advancement of information technology, collecting, analyzing, and using personal information without permission has become relatively simple. Since an interpretation of commodities on the network can only be achieved by image and text descriptions, there is a possible personal privacy risk if the definition of product information is not clear. Several vague definitions can easily lead to different interpretations.

The Assessment Alternatives’ Safety System

Unlike traditional shopping, online shopping, especially online payments, necessitates the transmission of information over the internet. Unauthorized offenders are likely to tamper with the transmission mechanism. Personal details, such as credit card numbers, have been modified, copied, and removed. If not managed properly, this would enhance consumer fears of the risks of online shopping.

The Security System on Purchasing Decisions

Companies entering and exiting the industry may find their capital exhausted due to networking, and online retailers can suddenly disappear. When compared to traditional shopping, returning items purchased online is inconvenient. Online retail products, on the other hand, are dependent on impersonal electronics stores to complete transactions.

Get to know Customers Better

By applying big data, we collect all information from customers who use our services or business. We can use this collection of information as a reference to understand consumers who we can better provide products to according to their needs and desires. From the data collected in big data, we can see the facts in the field, consumer trends, and their behavior and activities. By using big data, the process can be done faster.

Build a more Effective Marketing Strategy

With all the customer or consumer data that we have today, it will not be difficult to build an effective marketing strategy that can reach every consumer according to our market. Using the right marketing strategy will prevent us from shrinking market shares caused by relationships that have not been fully developed with our customers.

Building Relationships and Consumer Trust in the Business

Our strategies will also affect the risk factors that will begin to decrease along with the implementation of the right strategy. An effective strategy, in addition to increasing consumer confidence, will also increase revenue in the business we are running.

Improve the Consumer Shopping Experience

The amount of data that is contained in this big data can be used to improve the shopping experience of our consumers. Producing products and services based on customer wants and satisfaction as revealed by data inputted into big data. When a consumer visits our website, it does not mean that they will just shop right away, but they are also looking for other product insights that they think they need. Having this consumer data as a business owner can provide product recommendations according to what consumers need and want through their search history. Thus, we can also analyze consumer data from the time they visit our website until they leave the website.

Increase e-Commerce Innovation

Innovation is a necessity that needs to be done by businesspeople and intended to bring the company flexibility in the face of shifting trends. Business actors can see the trends of their consumers through information so that they can take advantage of this tendency to create new, more targeted innovations.

Hereinafter, the recommendation system will view evaluation of commodity information, customer interest, product matching, recommending customers for similar goods (S. X. Wang, 2013).

Recommendation System About Needs

According to research, consumers are unable to shape stable and distinct preferences because they lack an accurate understanding of product details. Consumer preferences are often not set because of knowledge adjustments during the purchasing process. Therefore, a recommendation system provides complete and personal information to consumers. The survey results also show that consumers are influenced by website information and promotions. They think that the recommendation is to provide them with more references (Zhao, 2012).

Recommendation System of Information Search

Information review is the recommendation framework’s greatest strength. The advice offers customers knowledge that is more detailed and more completely personalized. To reduce the cognitive deviation between different brand items, buyers must have a deeper and more detailed assessment of product function, performance, and price of the product.

Recommendation Framework for the Evaluation of Alternatives

The prescribed framework additionally gives data to clients simultaneously such as professional and customer reviews. This will influence the assessment and attitude of consumer products to differing forms. The purchasing decision process is a component of the recommendation system that influences customer preferences, product ratings, and selection strategies.

Recommendation System on Post-Purchase Behavior

This suggestion method will save shoppers time by finding, analyzing, and selecting information, offering more precise and productive data to the buyer. The suggestion system enhances the assortment of items and evaluations; empowers purchasers to have a more noteworthy assortment of merchandise, aligning with the customer’s buying behavior. This improves consumer confidence and enhances trust.