Emerging Technology: Revolutionizing the Customer Experience with Artificial Intelligence

Artificial Intelligence (AI) is ubiquitous, and it has accelerated with the digitalization of processes and activities among many organizations by increasing their capabilities. In terms of corporate language, chatbots technology is a part of human-robot interactions, which offers various opportunities and support firms to discover better insights and provides a better platform for sound decision making. (Luce, 2018) Nowadays, facing challenges and risks are pretty standard in business, both internally and externally. To compete in a new era, firms create a good relationship between customers by providing an efficient service in terms of verbal or physical depending on the affordable product. Focussing on improving customer experience, continual advancements in technology are incorporated to provide better response time and increased quality of interaction (Delamater, 2017). A chatbot can identify consumer needs quickly once when they started interacting with AI-powered bots and proactively start a conversation with them by providing relevant information throughout the entire chats. It can transfer a caller to a service agent if a human is necessary for the loop.
AI algorithms can search through each customer's buying habits, including what they purchased and when they made the purchase. AI improves the shopping experience by making product recommendations based on what the customers are interested in and most likely to buy. AI-enabled chatbots can provide the customers with consistently pleasant customer service and an immediate response instead of being put into a queue to wait for an available support representative. They were making the process of communication as easy and pleasant as possible leads to satisfy customers while at the same time freeing up organizations employees so they can focus their energy and time on other tasks. Consumers today are looking for convenience when it comes to shopping and making payments. 

Using smart speakers such as Echo and Alexa, consumers can make purchases and pay their bills with voice-enabled AI, interacting with any business at a time that's best for them. Sometimes customers want their questions answered after business hours, or they may want to update an order before the business opens the next day. For a small business, hiring employees to be available at all hours is unrealistic and costly. Using AI chatbots can give marketers customers the service they want regardless of what time it is. AI creates a shopping experience that's hassle-free and simple to interact with customers. Consumers are looking for fast and easy interactions when making purchases. AI makes buying smooth and easy, from deciding what product to buy to complete the transaction with fast shipping and delivery.

In the past, phone bots have been automated with limited functionality, usually providing one-word answers and simple directions to consumers. This type of simplicity in business communication can quickly lead to customer frustration. Today's AI phone bots are intelligent and helpful, solving problems and answering questions efficiently and precisely. This means that when customers call the business, they are getting accurate responses to their questions with valuable and intelligent voice interaction (Muhammadian, 2020).

The chatbot is a conversational agent that reproduces the conversation with customers, usually over the internet. They communicate with human users, especially the end-users, through messages via texts and reply accordingly. Even though the technological concept of interacting with the customers is not new, the design of chatbots was made by considering various assumptions. The artificial intelligence developed in the past tends to answer one-liner questions and could not answer any other conversation with the users. Firstly, the chatbot was designed to have limited domain knowledge as one can talk about any topic with the customers (Luce, 2018). Chatbots are designed to focus on specific issues. By the end of every conversation, the customers want to achieve a particular result. This will have an impact on the flow of the conversation. The designers of chatbots can exploit this as some behavioral patterns will arise as a result. 

By 2010, various assistants like Apple, Siri, Cortana, and Alexa came into the market that dealt with a dual conversation with a goal-oriented dialogue. The release of messenger for Facebook is another breakthrough and allowed the agents to discuss non-AI-related companies (Campione, 2021). Chatbots include working with multiple components. When chatbots are receiving a new message, the language identification module will first process the message. The new message and its language, along with any previous conversation, will be retrieved and fed into the classifier module, which will imply the message the user is trying to convey. This will then be used to decide the action sequence. For example, the chatbot reply will be in the form of whether the message is not clear. The proper execution of the situation happens with the module known as an action handler.

Damanvir Kaushal

Keywords

#Emerging Technology

#Customer Service

#Artificial Intelligence

#Conversational Service Automation

References

Campione, R., 2021. HOW DIGITALIZATION IS REVOLUTIONIZING RELATIONSHIPS BETWEEN CUSTOMERS AND SERVICE PROVIDERS IN THE HOSPITALITY INDUSTRY: PERSONALIZATION AND GAMIFICATION. International Journal of Information, Business and Management, 13(1), pp.35-52.

Delamater, N., 2017. A brief history of artificial intelligence and how it’s revolutionizing customer service today. Available in https://images. g2crowd. com/uploads/attachment/file/73099/expirable-direct-uploads_2F469f2619-a917-446d-b2b8-14cf8f8 d2c4e_2FChatBotWhitePaper2017. pdf Disponible el, 17.

Luce, L., 2018. Artificial intelligence for fashion: How AI is revolutionizing the fashion industry. Apress.

Muhammadian, R., 2020. Artificial intelligence in marketing. How AI is Revolutionizing Digital Marketing.

VALUE-KNOWLEDGE MANAGEMENT. HOW IT CAN WORK AND ITS BENEFITS IN AN ORGANIZATION.

Knowledge management is the deliberate method of identifying, structuring, maintaining, and exchanging an organization's employees' knowledge and experience. Knowledge management is necessary because it increases the productivity of a company's decision-making ability. In making sure that all employees have access to the overall expertise held within the organization, a smarter workforce is built who are more able to make quick, informed decisions that benefit the company.

Knowledge management may have a positive effect on individual divisions within an organization, such as the IT support team and the customer service department. Many organizations have incorporated digital applications, such as chatbots, into their information management systems. In this scenario, knowledge management is mainly used to help the IT support team. Knowledge management data will aid some AI ventures in the reverse direction and assists the customer service staff in addressing customer concerns. They compile details on the problems that customers report. They can classify specific problems as well as problems that involve a broad organization by evaluating this collection of data. As a result, they would need to develop new content to aid consumers with addressing their challenges on their own.

Companies can offer more content to their consumers by using knowledge management. This method, regardless of how you use new automation services and chatbots, is even more effective if it happens earlier. If you use these artificial intelligence techniques to create content, it will be better. Automation for content is recommended for businesses that choose to have more human contact. Chatbots may be used for those that are dealing with big problems or issues that concern a large number of customers. Agents will provide content for certain chatbots based on the issues they're dealing with.

 

Benefits and examples of Value-Knowledge management in organizations.

·   Cross Training programs- Mentoring, shadowing, and other cross-training activities allow workers to acquire the company expertise by studying others at work. New employees at Toyota, for example, spend months shadowing seasoned employees, and new plants are originally staffed by both experienced personnel from existing factories and new hires. 

·   Document management system -Organizations can store business records in the cloud, exchange them, and monitor access permissions at a granular level through database management systems like Google Drive and Package. These tools typically have mechanisms for tagging files and incorporating metadata to make it easier to locate content.

·   Content management systems (CMSs) - Teams and individuals can publish, upgrade, and view information on a business intranet using content management systems including SharePoint and Bloomfire.

·   Social networking tools – Teams can connect and interact in a public environment using private social networking platforms like Workplace through Facebook and Slack. However, since these resources preserve all past discussions, they can be used as a knowledge management programs, allowing workers to check for previously shared material.

·   Chatbots- We agree that chatbots are the next logical phase in knowledge management. AI and deep learning are used by chatbots like Banks and airline websites to respond to employee questions and requests for information. Employees don't have to worry about who to ask or where to go for information as they use chatbots. They don't have to search into a CMS, record system, or chat history to discover what they're searching for. They can ask natural-language questions, such as "How do I add a new baby to my insurance?", and the chatbot will reply with the most appropriate information from its knowledge base, regardless of where that information is stored inside the company.

DAMANVIR KAUSHAL

Keywords

#value Knowledge management

#Knowledge management

#Chatbots

#Management knowledge

#Business objectives

References

https://www.atspoke.com/blog/knowledge-management/knowledge-management-importance/

 https://ecommercenewsforyou.com/the-importance-of-knowledge-management-in-marketing/

 https://www.emerald.com/insight/content/doi/10.1108/09544780610659970/full/htm 

 https://www.researchgate.net/publication/228471641_What_is_the_Value_of_Knowledge_Management_Practices 

What are the Benefits of Volume-Data Storage and How it is Beneficial to Digital Marketers?

Data storage is a medium to store a huge amount of Information. Any electronic document can be store in less space than any paper document. This information converts into bits and can be stored in the electric circuit. The storage volume can be removable hard disk but it doesn’t remove physically from computer or storage system. This Volume data storage is flexible and it can contract or expand. In it, files and documents can record digitally and saved in a storage system for future use. If we talk about a business point of view data is the most important asset. So in today’s digital world, the best method of volume data storage is websites, blogs, social media sites. Making a high-quality website for storing data is a good option so that it can include information about things that customers find relevant and interesting. With the help of data storage, it’s easy to get the contact information of the customers. Digital marketers have to deal with a large amount of data on different sources like social media, websites and that collected data helps them to do marketing digitally in the digital world. Not only this there are many other data management or data storage platforms where digital marketing experts can store their data and use it whenever they needed. Here if we talk about different marketing which is called content marketing, in content marketing data storage is very much important because if we don’t have any accurate data or we are not able to make proper and right content and in content marketing strategy data plays a vital role especially when we don’t have any idea about data analytics. By capturing or recording data digital marketers are better to understand what content or marketing strategies and methods are required for getting a better result. The things which come in mind for storing huge amount of data for a long time is optical media like DVD, and external USB - SSD drive for storing last 20 years as well as Network Attached Storage (NAS) with RAID: These have high performance magnetic hard disks and are your best option. Because of RAID, there is failure protection. I am not sure that original disks can last 20 years, but you can replace them (NAS allows hot-swapping of disks). In volume data storage it helps to keep a record of all past and activities of digital transactions. It also helps in data analysis so that any marketer can forecast the trends of the future market. It also provides flexibility and mobility and storage is easy and can move from one place to another, not only this it’s easy to forecast the better strategy formation. With the help of volume data storage decision-making is easy for the management which benefits the company’s business. 

In conclusion, it is not easy to manage and recognize the huge amount of data for the human brain so that with the help of data storage it is easy to keep a record of the day to day activities which increase the efficiency of the employee in many ways as a result easy to analysis the market scenario that helps business winning out in today’s competition.

Damanvir Kaushal

Keywords

#Volume Data storage

#Digital marketing

#Data storage

#Digital Transformation

#Social media

References and Sources :

• https://searchstorage.techtarget.com/definition/volume
• https://techterms.com/definition/volume
• https://docs.oracle.com/cloud-machine/latest/stcomputecs/ELUSE/GUID-6ACE7B13-442B-459C-8868-566F1CB65E3F.htm#ELUSE-GUID-6ACE7B13-442B-459C-8868-566F1CB65E3F
• https://docs.microsoft.com/en-us/windows-hardware/drivers/ifs/storage-device-stacks--storage-volumes--and-file-system-stacks
• https://kt.cern/competences/high-volume-data-management-storage