Introduction.
E-business.
The information age brought with it a wave of irreversible change across industries. Some functions that were previously a norm were done away with and replaced with simpler ways of accomplishing the same tasks. The field of business is among those that have been adversely affected by the information. How business is being conducted currently is extremely different from the way it used to be before the information age. This transition saw the adoption of e-business. E-business is defined as the infusion of electronic technology in business functions. The extensive use of personal computers in the 1980s and the development of the commercial internet in the 1990s are what triggered the adoption of e-business (Rezaei, Chiew, & Lee, 2014).
Previously, data in business was stored on paper in physical filing cabinets. The limitations of this was that retrieving of information when needed; especially from historical transactions was not easy. The time it took to organize and analyze such data was too much. The probability of losing information was also high. E-business has allowed companies to store much more data digitally on servers. This data could now be easily organized and analyzed using spreadsheets and other computer programs. The speed at which this data can be retrieved is also unfathomable.
The internet has provided a platform through which business can be conducted. Businesses are now moving from the traditional 'brick and mortar' locations to online platforms. This movement allows businesses to be in diverse locations at the same time. With most people having mobile devices and access to the internet, businesses have gone into offering goods and services for sale on their websites. Communication has also been facilitated by the introduction of cheaper telephone calls over long distances and new technologies that provide free video conferencing. E-business has not only enabled easier business transactions but has also seen the introduction of digital products. The most common of these digital products are e-book, MP3 tracks and computer software (Riehl & Kassim, 2014).
Artificial Intelligence.
Artificial intelligence is the set of tools and programs that enables any computer software to undertake tasks that are commonly preserved for intelligent beings (Barr & Feigenbaum, 2014). These tasks may include; learning, speech recognition, visual perception, decision-making and translation of languages. Artificial intelligence simply involves self-learning of computers with the aid of processes such as data mining, recognition of patterns and neuro-language processing. The product of these processes is a human-like response from computers and their software.
The concept of artificial intelligence was first explored in the 1950s though its development was stalled due to the lack of funding and inferior computing power that existed at that time. The actual work on rudimentary artificial intelligence began in the 1980s when funds were availed and the computing power had greatly improved. Computers were faster and had more storage capabilities. Initially, artificial intelligence involved computers learning using experience and the mimicking of decision making processes of a human expert. These, however, were at a basic level. With time, artificial has seen immense growth with a current annual worldwide growth of 12.9%. Countries have been on toes in the production of artificial intelligence with the Europe leading the pack followed by China, the United States and India (Barr & Feigenbaum, 2014).
Artificial Intelligence in E-business.
With all the buzz in artificial intelligence, it is inevitable that it has found itself in the business world. Currently, artificial intelligence is being applied in all the areas of e-business. The first application of AI was seen in the undertaking of repetitive tasks. However, this has been seen to be drastically evolving in line with the rate of growth of AI. The following are some of the ways that AI is slowly disrupting the e-business environment;
Application of Artificial Intelligence in E-business.
Creation of customer-centered search.
Currently, when one searches for a product in an online store, the results are either limited or irrelevant to the consumers' requirement. This is one of the many reasons that drive consumers away from online shopping. Incorporation of search engines that mimic human thinking into websites of these stores improves the search results for the online consumers.
Most search engines have always been limited to the typing in of words in order to get the desired results. In some cases, this method has not been effective since one might lack the right words to describe a sound he has heard or an item he has seen. AI has, however, enabled the development and inclusion of sound and visual search into search engines. With this enabled in a business's website, a customer can easily look for an item whose image they have using the visual search option. In case one needs to purchase a song or an audio file whose title they are not aware of but have a small recording of, they can easily get it using the sound search option.
These improvements in the search feature of a website gives an advantage to the businesses that are in use of it since the customer satisfaction is guaranteed.
Retargeting of potential customers.
Most businesses have tons of unmanageable customer data that they have little or no use of. These data can be used to improve the cycle of sales. In online stores, potential buyers often spend too much time on a category of the items on display. Some go to the extent of adding them to the shopping carts but not actually buying them. This is a trend that can be analyzed by AI software so that products that are frequently viewed by customers are identified. Upon identification, offers can be placed of these products so that their sales increase.
Identification of exceptional target prospects.
Recent AI technology equips e-businesses with timely intelligence needed to overcome their business huddles. Among these huddles is generation of leads. Predictive marketing AI provides e-businesses with solutions for marketing and sales systems. Generation of leads is done by capturing data that is relevant to the needs of a business. High quality prospects are then identified across millions of potential client records. This gives the sales team of a business a competitive advantage to win new clients over its rivals.
Creation of efficient and effective sales process.
Gone are the days when businesses had to ram through the yellow pages to get potential clients and irritate them with endless cold-calling. Different media, from television advertisements to social media have now taken over. Companies are now integrating AI into their Customer Relationship Management (CRM) systems. The AI systems have natural language learning and voice input enabled, which allows CRM to answer clients' questions, solve their problems, and pin point new opportunities for sales teams. These functions can be done simultaneously by the AI-infused CRM systems (Orenga-Roglá & Chalmeta, 2016).
Establishment of new personalization level across devices.
New AI engines help businesses analyze how customers are engaging with each other online. They continuously monitor all devices and channels to decipher the platforms that are mostly used so as to create a common customer view for businesses. This enables businesses to deliver to their customers flawlessly across all platforms.
In case a customer is browsing for a product on a website, they receive push notifications, informing them of flash sale on the product. This prompts them to make the purchase, which saves both the seller and the buyer a lot of steps that would have otherwise been made.
Use of chatbots.
A chatbot is defined as a specific computer program that is made to simulate conversation with human users over the internet. For e-business, chatbots take a huge chunk of the responsibilities that entail running it especially the marketing and operations bit. They automate order processes and are a cost efficient customer care tool.
A chatbot service can also be integrated in a shopping cart. Once embedded with one of your shopping carts, the chatbot scheme can operate with all the platform-based shops. The more chatbot implementation promotes shopping carts, the more prospective clients it has. Specific schemes also need inclusion of shopping carts to obtain data such as item details, volumes and conditions of shipping that chatbots can use to provide clients with precise responses.
Chatbots provide e-commerce distributors with a precious customer support alternative. They stay the easiest and most comfortable way for visitors to obtain responses in many instances (Cui, Huang, Wei, Tan, Duan, & Zhou, 2017).
Empowerment of store workers.
The concept of chatbots can also be used in-store as shopping assistant robots. They perform their duties by welcoming shoppers in to the store, guide them around the store and give relevant information on products. They also help the employees manage inventory. This limits the interaction between employees and customers to important issues.
Use of virtual assistants.
These virtual assistants are integrated into websites and products of several companies. They generally help in performing simple tasks for consumers and businesses. These tasks range from ordering of food and other items from online stores, purchase of tickets to events, telling the weather, arranging transport to and from places via online taxi services and even tracking order status of items in real time.
These assistants can not only be used in homes but also in offices to perform minor repetitive tasks that are still important. In the long run, time that would have otherwise been spent doing these activities are allotted to more important activities (Karov, Breakstone, Shilon, Keller & Shellef, 2017).
Improve recommendations for customers.
Recommendation is highly used by e-commerce retailers to aid customers in finding the best product or service. This is done by using AI to scan through data to predict the behavior of customers. This is key in delivering personalized shopping experience for clients. Several algorithms are put in place that analyzes the clients' account information, preferences, history of purchase. This enables the recommendations to be sent to the clients to be personalized.
Introduction of virtual personal shoppers.
Online shopping is characterized by the marking of many boxes and going through several prompts for one to get the specific product that they need. This is a time consuming factor for most online shoppers and might drive them away from a site before they make a purchase. Online businesses are developing ways of combating this time wastage that might bring about restlessness to the consumers and a lost potential buyer for them. Brands are using AI to develop virtual shoppers to assist their clients online. They help the clients navigate the online store quickly to fetch products that are most appropriate to the shoppers' requirements, just like it happens in brick and mortar stores. This is simply transferring the offline shopping experience to the online platforms.
Virtual shoppers if widely applied, will completely disrupt the current customer engagement techniques. They operate more or less the same as virtual assistants but are specific to the online stores (Karov, Breakstone, Shilon, Keller & Shellef, 2017).
Work with intelligent agents.
This is an instrument that brings together the technology of artificial intelligence and officer. It operates by bringing together customers and distributors, enabling operations, and offering organizational infrastructure. The officers are fully staffed and have complete power over their behavior. They have their own language of communication and not only respond to their surroundings, but they are also able to use their action to generate their own goals.
Bridging the gap between personalization and privacy.
Currently, privacy of personal information has been a major concern for most internet users. This is because some of the social media sites have been selling their personal information to the highest bidder, which goes against their privacy policies. Personalization is also a major issue for e-businesses since they need their clients' information, sometimes from third-party sources like social media platforms, in order for them to personalize the customers' experiences.
However, there is usually a compromise by the internet users if their giving of personal information has a promise of them getting value in return. This can be applicable in the cases of virtual assistants where one needs help with tasks on a daily basis. In case a user is assured of an outstanding experience without them having to input data into the websites, then that is a bargain they are willing to make. This is powered by AI (Pfeifle, 2018).
Generate sales through wearable technology.
Wearable technology such as the apple watch, are capable of collecting more data than is being collected currently by the e-business platforms. Not only do they collect information that you feed into them but they also collect data in line with your physical behavior such as the rate of pupil dilation and statistics of your vitals. With this information, e-business platforms can provide customers with 'hyper-personalized' recommendations which are sure to drive up the sales (Schüll, 2016).
Improve dialogue systems.
With the aid of a category of AI that uses machine learning algorithms, e-businesses can accurately convert customers' speech into text. This helps in the automatic answering of questions that customers pose using AI with content from web pages such as customer reviews and product description.
Tackle fake reviews.
There are so many advertisements that people are exposed to on a daily basis. This is often overwhelming and makes the decision making process difficult. what makes it more difficult when it comes to online shopping is that the product in question is something that one is yet to interact with personally. This is why customer reviews on online products are very important. Most decisions on online purchases depend on these reviews. The more positive the reviews, the more likely a product will be purchased.
However, most e-businesses have received their fair share of fake reviews. Fake reviews can have a negative on an online store to the point of its closure. Thus, AI has been identified as a perfect solution to combat these fake reviews. AI systems boost the prominence and the weight of the reviews that are given by verified customers who have made purchases. These reviews are important since they help build the trust of the customers in companies.
Combat counterfeit products.
Counterfeit products tend to have the same effect on a brand as that of fake reviews. The major problem with counterfeits is that they are difficult to be spotted by consumers especially when being sourced from third-party seller. Machine learning AI can be used in the identification of these counterfeits. Data is gotten from various e-business platforms, and analyzed to determine whether the products are genuine. This helps in identifying the market places that sell counterfeit products so that appropriate action can be taken on the companies and the products removed from the websites.
Case studies.
Amazon.
Amazon's Alexa is one of the most known AI products worldwide. It helps Amazon deliver its targeting market strategy by predicting the most demanded products as per the analysis of customer searches. This has helped Amazon in driving a lot of sales as a result (Chung, Park & Lee, 2017).
Alibaba.
Alibaba uses AI to enhance its competitive advantage over its competitors. The company has a chatbot that handles up to 95% of customer queries. It also uses AI to map out the best delivery routes for ordered products. This, they say, has led to reduction of 10% in the use of vehicles and 30% in the distances travelled (Jia, Kenney, Mattila & Seppala, 2018).
Limitations of Artificial Intelligence in E-business.
As much as artificial intelligence is inevitably disrupting the e-business space, there are several limitations to its implementation for the stakeholders. Among these limitations are;
The availability of data.
Without data, AI is obsolete. The data needs to be accurate and of good quality, which is often not the case. In most cases, data is usually inconsistently collected and managed. AI needs sufficient data from its model stage before it is officially launched to officially operate in e-business. To overcome the shortcomings that are brought about by insufficient and inconsistent data, a company needs to have a well laid out strategy for sourcing data that will be used by the AI from the onset (Harkut, 2019).
Skills shortage.
The availability of staff with the right technical training and experience in AI development is in short supply worldwide. The ones that are available can only do too much in satisfying the current demand. Until the gap can be filled by more data scientists and professionals in machine learning, training of AI models, deep learning and other relevant areas in AI, very little can be done (Harkut, 2019)..
Cost.
Owing to their complex nature, smart technologies are often expensive. In case a business lacks skills in AI, they often have to outsource; which does not come cheaply. Training of data models, repair and maintenance can also prove to be quite expensive (Harkut, 2019).
Bias.
People and data are both often times bias. This bias can be transferred from data to data because of people, sometimes ignorantly or otherwise. Getting to know whether data is bias is not easy. When this data is used in the modeling of AI, its output might not always be correct. Hence for accuracy in AI modeling, there is need to avoid secondary data since its accuracy is not guaranteed (Harkut, 2019).
Conclusion.
Artificial intelligence's portfolio in the e-business environment is beyond reproach. Those that are embracing the change stand to gain a lot while those that are unreactive to change have no choice but to collapse. The effects of Artificial Intelligence in business have started being felt, especially from the big companies in the world like Amazon and Alibaba. However, as much as many e-businesses would want to join the Artificial Intelligence train it might not be possible due to the limitations that may hinder them. Of these limitations the costs of setting up and the lack of skilled professionals seem to be the most prevalent.
References.
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Riehl, D. A., & Kassim, J. (2014). Is Buying Digital Content Just Renting for Life: Contemplating a Digital First-sale Doctrine. William Mitchell Law Review, 40(2), 10.
Barr, A., & Feigenbaum, E. A. (Eds.). (2014). The handbook of artificial intelligence (Vol. 2). Butterworth-Heinemann.
Orenga-Roglá, S., & Chalmeta, R. (2016). Social customer relationship management: taking advantage of Web 2.0 and Big Data technologies. SpringerPlus, 5(1), 1462.
Cui, L., Huang, S., Wei, F., Tan, C., Duan, C., & Zhou, M. (2017, July). Superagent: A customer service chatbot for e-commerce websites. In Proceedings of ACL 2017, System Demonstrations (pp. 97-102).
Karov, Y., Breakstone, M., Shilon, R., Keller, O., & Shellef, E. (2017). U.S. Patent No. 9,772,994. Washington, DC: U.S. Patent and Trademark Office.
Schüll, N. D. (2016). Data for life: Wearable technology and the design of self-care. BioSocieties, 11(3), 317-333.
Pfeifle, A. (2018). Alexa, What Should We Do about Privacy: Protecting Privacy for Users of Voice-Activated Devices. Wash. L. Rev., 93, 421.
Chung, H., Park, J., & Lee, S. (2017). Digital forensic approaches for Amazon Alexa ecosystem. Digital Investigation, 22, S15-S25.
Jia, K., Kenney, M., Mattila, J., & Seppala, T. (2018). The Application of Artificial Intelligence at Chinese Digital Platform Giants: Baidu, Alibaba and Tencent. ETLA Reports, (81).
Harkut, D. G. (2019). Artificial Intelligence-Scope and Limitations.
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